Host Dr. Davide Soldato and his guests Dr. Ann Wu and Dr. Alexa White discuss the article "Air Pollution and Breast Cancer Incidence in the Multiethnic Cohort Study" and the editorial "Growing Evidence for the Role of Air Pollution in Breast Cancer Development" 

TRANSCRIPT

The guests on this podcast episode have no disclosures to declare.

 Dr. Davide Soldato: Hello and welcome to JCO After Hours, the podcast where we sit down with authors from some of the latest articles published in the Journal of Clinical Oncology. I am your host, Dr. Davide Soldato, Medical Oncologist at Ospedale San Martino in Genoa, Italy. 

Today, we are joined by JCO authors Dr. Anna Wu and Dr. Alexander White. Dr. Wu is a professor of Population and Public Health Sciences at the Keck School of Medicine of UCS, while Dr. White is an investigator in the Epidemiology branch of the Environment and Cancer Epidemiology Group at the National Institute of Health. 

Today, we will be discussing the article titled, “Air Pollution and Breast Cancer Incidence in the Multiethnic Cohort Study,” and the accompanying editorial. 

So, thank you for speaking with us, Dr. Wu, Dr. White.

Dr. Anna Wu: Thank you for having us.

Dr. Alexandra White: Yes, thank you so much for the invitation to be here.

Dr. Davide Soldato: So before going in depth about the results of the study that was published in the JCO, I was wondering if you could give us like a brief introduction and a little bit of background about what was known about air pollution as a risk factor for breast cancer and what was the evidence before this study was conducted.

Dr. Alexandra White: Okay. I can start with that question. So, there's been research for decades looking at the relationship between air pollution and breast cancer. And it's been a really challenging question to address for a number of reasons. One being that it can be really difficult to assess exposure to air pollution and many previous studies have had really limited information on people's residences over time. But in general, what we thought leading up to this study was that evidence was most consistent that exposure to traffic related pollutants such as nitrogen dioxide was more consistently related to a higher risk of breast cancer. The evidence for fine particulate matter or PM2.5 was less consistent. More recently, there have been a few large, well conducted studies that have supported a positive association. This new study in the multiethnic cohort led by Dr. Wu is really important because it really demonstrated that, in this large study of over 50,000 women in California, that they also do see an association with PM2.5. 

Dr. Davide Soldato: Thank you very much for the introduction. So, Dr. Wu, we just want to hear a little bit more about the results. So, what was the association that was observed for PM2.5? And specifically, the study that you ran was focused on a very diverse population, a multiethnic cohort, and so I was wondering if you observed any type of differences when you consider the different populations that were included in your study. And if you could also give us a little bit of what was the composition of the women that were enrolled in this cohort.

Dr. Anna Wu: Thank you for the question. So, the multiethnic cohort study is a cohort of over 200,000 individuals who were enrolled when they lived in Hawaii or California. For the air pollution studies that we've been conducting, we have focused on primarily the California participants. And in this instance for the breast cancer study, it was based on roughly 56,000 individuals out of- there were about 100,000 because half of them were men and they were not included. Of the California participants, 75% of them were African Americans or Latinos and they were self-identified as these racial ethnic groups when they enrolled in the study. And this was a particularly important consideration for us because in most of the studies that have been published so far on-air pollution and breast cancer, as well as other cancer sites, most of those studies were conducted among whites in the US or whites in Europe. And even if they included non-white populations, the numbers tend to be small so that they were not able to conduct racial ethnic specific analysis. So, we were particularly interested in examining these other racial ethnic groups because we know from other studies that racial ethnic minority groups tend to live in communities of low socioeconomic status and those communities also tend to have higher levels of various types of environmental pollutants. And so, it was important for us to actually try to tease apart these various interrelated factors. 

So, what we found was that per 10 micrograms per cubic meter, we had a 28% increased risk overall in all participants combined that meet across the racial ethnic groups. We actually did not see any differences or significant differences in the hazard ratios by race ethnicity and they were in general quite compatible with each other. But we did see a stronger finding among the white participants in our study.

Dr. Davide Soldato: Thank you, a lot, Dr. Wu. So, I think it's very interesting the fact that in the end you observed that air pollution is a significant risk factor across all the ethnicities that were included in the study. But I think that one very strong point of the manuscript and one very strong point of the analysis was that in the end you also corrected for a series of different factors because we know that the incidence of breast cancer can be modified, for example, by familial history or BMI or smoking habits or also alcohol consumption. And a lot of these risk factors were included in your analysis. And so, I was wondering if you could tell us a little bit whether you observed any significant differences when you observed or included also these risk factors in your analysis, or whether the association for air pollution as a risk factor stands even when we consider all of these other elements.

Dr. Anna Wu: Yes. So, we considered all the well-established breast cancer risk factors. And in this situation, we were particularly interested in considering smoking, alcohol intake, use of menopausal hormones, history of diabetes, body mass index, family history, as well as physical activity, because many of these risk factors, such as, for example, diabetes and body mass index, they are risk factors for breast cancer, and air pollution, have also been found to increase risk of these factors. 

So, in our analysis, we first adjusted for all of these potential confounders in a mutually adjusted manner, so all of them were considered. In addition, we also conducted stratify analysis. So as an example, we stratified the analysis to examine whether the hazard ratio associated with PM2.5 provided comparable risk estimate or hazard ratio estimates for never smokers, former smokers, and current smokers. Although we did not see significant heterogeneity by these various subgroups, we did see a significantly stronger effect of PM2.5 among individuals who did not have a family history of breast cancer. 

Interestingly, our finding was also stronger among individuals who were never smokers and light alcohol drinkers, even though the results were not significantly different. So, we surmised that maybe individuals who already had a high risk because of other established risk factors for breast cancer, we were less likely to be able to observe the effect of air pollution. But it's important to note that other studies, such as the ones that Dr. White has conducted, have also looked at various subgroups, and I think part of the limitation that all of us have is that once you subdivide the study population, even if you start out with a large sample size, often the sample size gets cut in half or a third. And so, we still lack the statistical power to be able to observe significant differences. But I think it is important to note that, in fact, the hazard ratio estimates are actually quite comparable, but we did see a hint of stronger effects among never smokers, and people who were light alcohol drinkers. So, I think this is an area that we certainly need to continue to investigate since there are other subgroups, such as menopausal status, such as hormone receptor status of breast cancer, that we need to consider in future studies. There's still a lot of work we need to do to sort this out, to actually figure out who are the women who are the most susceptible to the exposures.

Dr. Davide Soldato: Dr. White, I would really love a comment from you on this specific area and specifically on what still needs to be done. And related to this, a question actually, for both of you, because I think that from a methodological point of view, there is a lot of work that goes into deciding how we are going to assess the exposure to air pollution. So which type of data are we going to use? Which type of data are we currently using in the epidemiological studies that have been conducted and in the one that we are discussing right now in JCO? And what are the caveats for this data that we are using? Meaning, I think that we use mostly residential addresses, which means that we are looking at the exposure where people actually live, which might not be the place where they spend most of their time. For example, if someone is working, maybe they could be more exposed and have higher exposure when they are at work compared to when they are at home. So, I was wondering if you could give us a little bit of an overview as to what is the methodological standard of care right now in terms of this analysis and what can we do better to refine and understand this specific factor as Dr. Wu was mentioning?

Dr. Alexandra White: Yeah, so I'm happy to take a first stab at that question. So, I think it's important to note just how far we've come. I think even a few years ago, air pollution was really not considered a risk factor for breast cancer. And a lot of the work that we've been doing and others have really moved this forward in terms of understanding this as a risk factor. And as I mentioned earlier, there have been a lot of challenges in exposure assessment. And to get to your question, I think that our studies in general are doing better at looking at exposure over more years, residences, more time. We know that cancer takes time to develop, and we can't rely on just a single snapshot of exposure. But as you mentioned, almost all of the studies published have really exclusively focused on residential estimates of exposure. And so, there's a real need to understand the exposures that people are experiencing in other aspects of their life, from their commute to their jobs, to really capture that totality of exposure. 

And then I think one of the points that Dr. Wu was alluding to as well as we know that breast cancer is a very heterogeneous disease, so risk factors for breast cancer vary by tumor subtypes, by menopausal status at diagnosis. And a lot of studies have really focused on considering breast cancer as a combined outcome, and that might be missing some really important signals where we might have a stronger effect for certain subtypes due to the fact that there's different biologic pathways that are underlying these subtypes or by menopausal status. And so having large study populations where, as we discussed earlier, would really give us the power to look among these smaller groups of women who might be more susceptible and those with younger women, we know that incidence of cancer is rising in young people, and we need to understand the risk factors for that. And most of our studies are really focused on older individuals, so I think that's one important gap, as well as having the power to really look at different differences by tumor subtypes.

Dr. Davide Soldato: I think it's very interesting, and I think one point both of you made in the original article and in the accompanying editorial is also the fact that we tend to look at these risk factors in people who are actually aged, while we maybe should be looking at this in an earlier phase of development and potentially during puberty. Do you think that we should design studies that are more focused on this population even though I think that they will take a lot of time to produce significant results? 

Dr. Alexandra White: Yeah. I think that it is really important to consider how exposure during early life is related to breast cancer risk. We know that exposures during pregnancy or even as early as during puberty might be particularly relevant for breast cancer. And I think a lot of our studies have really been up against the challenge of the fact that exposure monitoring for air pollution really didn't start until the 1990s. And so, it's challenging, especially for these older cohorts, to get back at that time period that might be relevant. But I think that's something that definitely newer cohorts are going to be able to address, and I think it's going to be really important, and also will give us some clues to better understand the important windows of exposure, but also that might provide clues for the biologic pathways as well that are relevant.

Dr. Davide Soldato: And just a related question, because I'm not aware of this, but are there right now cohorts that are specifically looking at this in the US or in other parts of the world? If you are aware of that, of course. 

Dr. Alexandra White: There have been some cohorts that have focused on exposure during these hypothesized windows of susceptibility, but I don't think they've been able to follow those women long enough to develop breast cancer. One of the things that we're working on in the sister study is trying to expand our assessment of air pollution exposure back in time to try to get at these earlier windows of exposure. So, I'm hoping that it's something we'll be able to comment on and at least for some of the women in our cohort who are younger. But I don't know, Dr. Wu, if you're familiar with any other populations that are doing this now? 

Dr. Anna Wu: Well, NCI funded several new cohorts in the last couple years that are really focused on trying to get a much more refined exposure assessment. So, I know colleagues at University of Michigan that are peers and also Dr. Wei Zheng at Vanderbilt, they are putting together newer cohorts that are younger and also trying to include a range of exposure, not just air pollution, but really environmental exposures. Those cohorts I think have the potential in the future to try to address some of these questions, but again, it will take at least another number of years before there are a sufficient number of endpoints so that they can actually do these types of studies. 

Another possibility is that there are a number of big cohort studies in Asia. The age of diagnosis tends to be earlier in Asia. I know that investigators in China are very interested and concerned with the air pollution effects in China. I think there are potentials that in other countries where the age of breast cancer diagnosis is actually younger than in the US and if they establish in a manner that allows them to assess air pollution that they may have opportunities. 

And I think the other way to try to address this question, whether there are studies where you can actually tap into either biomarkers or pathology samples so you won't be actually studying air pollution in a large population, but you're actually narrowing it down to try to see if you see any signals in a way that would give you some additional clues and insights as to the mechanism. So I think we're going to have to piece together various types of study to try to answer the questions because one type of study like these observational air pollution studies, will allow us to address one slice of the questions that we have and then we need to put together other studies so that we can address other aspects that we're interested in to put it together.

Dr. Davide Soldato: Thank you very much both of you. That was very interesting. 

Coming back to the results of the manuscript, we really focused up until now on PM2.5. But it's true that inside of the study you evaluated different pollutants. So, I was wondering whether you saw a similar association for other pollutants that were included in the study or whether the association for higher risk was observed only for PM2.5.

Dr. Anna Wu: The results for NO2, NOx, PM10, and carbon monoxide were actually very compatible with the risk estimates that other studies have published as well as from the meta-analysis. So, I would say that our results from the other pollutants are actually very consistent with other results. I think one difference is that our PM2.5 estimates were based on the satellite-based PM2.5 estimates, whereas all the other pollutants were based on monitoring station estimates from EPA sponsored air monitoring stations. So, they are not measured in the same way. And I think different studies over time have used either monitoring station type measures for other pollutants. And I think we were particularly interested in PM2.5 because the measurement of PM2.5 in the monitoring world didn't start until around 2000. So, studies up until that time were less able to actually provide the assessment of PM2.5 as good as we can for air pollution. There's always misclassification. So, I think it's a matter of how much misclassification in the assessment. But, again, we are really limited in really just having exposure over one part of adult life. 

Dr. Davide Soldato: Thank you very much. And one potentially related question. We are speaking in general about air pollution, but I think that since we are considering residential addresses, probably we are capturing more either traffic pollution or pollution that comes from probably industries or stuff like that, which is mostly related to residential areas or the place where people live. But I think that in the end we also think about air pollution as something that can come from different forms. And one very interesting point, Dr. White, that you made in your editorial is also that there is a global change also in the way we are faced with air pollution. For example, you made the example of wildfires in your editorial and how this might potentially change exposure to air pollution, maybe for limited times, but with concentrations that are fairly higher compared to what we generally observed. So, I was wondering if you could comment a little bit on that and also, if there is potentially a way to also consider this in future epidemiological studies.

Dr. Alexandra White: Yeah, so when we talk about exposure to fine particulate matter, PM2.5, we're assessing exposure to particles that are based on the size of the particle, and we're really not evaluating the types of particles that people are experiencing exposure to. And we know that, in general, that PM2.5 composition really varies geographically due to differing sources of exposure. So, like you were saying, there might be a stronger contribution to industry or from agriculture or from traffic. And so that could really change the PM2.5 exposure profile that individuals experience. And so it could be that this is another really important area that this research needs to consider, which could really help us identify what sources of exposure are most relevant.  

Wildfires are a really important growing concern. We know that wildfires are increasing in both intensity and duration and frequency, and we really don't understand the long-term health impacts of wildfires. But we know that wildfire associated PM2.5 might be one of the most dominant contributors to PM2.5 moving forward. And although we've seen historic declines in PM2.5 in the US after the Clean Air Act, those declines have really stalled. PM2.5 itself is projected to increase over the next few decades, so understanding different PM2.5 composition profiles and the sources that drive them can really help us identify the most important targets for any potential interventions. And wildfire PM2.5 in particular may be of concern because it's a combustion byproduct, and so it's thought to have more of the components that might, we hypothesize, are most relevant for breast cancer, such as PAHs or polycyclic aromatic hydrocarbons or metals. And so, these components are thought to act as endocrine disruptors, which may be particularly relevant for breast cancer. So, I think understanding this changing landscape of PM2.5 moving forward is going to be really important in understanding how PM2.5 contributes to cancers beyond just breast, but as well as other female hormone driven cancers and all of the cancers really. 

Dr. Davide Soldato: Thank you very much. So, one closing remark, because I think that in general, we have been really in a field of primary prevention for breast cancer where we were focusing on individual behaviors, for example, smoking cessation, reduction in alcohol intake, reduction of BMI, increase of physical activity. But I think that the evidence that is accumulating in the last three years or so is telling us more and more that we also need to shift the perspective on prevention going not only on individuals, but also as including environmental risk. So, I was wondering, how can we include this new evidence in the policies that we implement and how policymakers should act on the data that we have available right now?

Dr. Anna Wu: I think it's really important that this new information is communicated to all the stakeholders, including our policymakers, so that they are, first of all, really aware that any changes and not actually adhering to current guidelines can have long lasting consequences, deleterious consequences. And I think it's important to also note that over 90% of the world actually live in areas where PM2.5 exceeds the limit. We have observed increases in breast cancer in many middle- and low-income countries, so I think it's particularly important to emphasize that this is really not just a western country issue, it is really a global issue.

Dr. Alexandra White: I agree. And I would just add to that that air pollution is not something that an individual can really change on their own. There are things you can do, you can monitor air quality, you can try to live in a home that's far away from traffic. But really these are large scale problems that really require large scale solutions. And we know that policy changes can be effective here and that this is something that, in my opinion, is not something that we leave to the individual to change. This is something that we as a society should encourage change for the health of everyone.

Dr. Davide Soldato: So, thank you very much again, Dr. Wu, Dr. White, for joining us today on the podcast.

Dr. Anna Wu: Thank you.

Dr. Alexandra White: Thank you so much for having us. 

Dr. Davide Soldato: So we appreciate you sharing more on your JCO article and accompanying editorial titled, “Air Pollution and Breast Cancer Incidents in the Multiethnic Cohort Study.” 

If you enjoy our show, please leave us a rating and review and be sure to come back for another episode. You can find all ASCO shows at asco.org/podcasts.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.  

Guests on this podcast express their own opinions, experience and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity or therapy should not be construed as an ASCO endorsement.

In this JCO Article Insights episode, Giselle de Souza Carvalho provides a summary on  "Navigating Treatment Pathways in Metastatic Hormone Receptor–Positive, HER2-Negative Breast Cancer: Optimizing Second-Line Endocrine and Targeted Therapies" by Bhardwarj, et al and "US Food and Drug Administration Approval Summary: Capivasertib With Fulvestrant for Hormone Receptor–Positive, Human Epidermal Growth Factor Receptor 2–Negative Locally Advanced or Metastatic Breast Cancer With PIK3CA/AKT1/PTEN Alterations" by Dilawari et al published in the Journal of Clinical Oncology. 

TRANSCRIPT

Giselle Carvalho: Hello and welcome to JCO Article Insights episode for the December issue of the Journal of Clinical Oncology. I'm your host Giselle Carvalho, Medical Oncologist in Brazil focusing on breast cancer and melanoma skin cancers and one of the ASCO Editorial Fellows at JCO this year. Today, I will be discussing two articles. The first one is “Navigating Treatment Pathways in Metastatic Hormone Receptor–Positive, HER2-Negative Breast Cancer: Optimizing Second-Line Endocrine and Targeted Therapies,” and the second one is the “US FDA Approval Summary on Capivasertib with Fulvestrant  for HR-positive HER2-negative Locally Advanced or Metastatic Breast Cancer with PIK3CA/AKT1/PTEN Alteration.” 

As we know, 65% to 70% of all breast cancers are HR-positive HER2-negative and this is also the most common subtype of metastatic breast cancer. The current standard of care for frontline therapy of patients with luminal metastatic disease is a CDK4/6 inhibitor in combination with endocrine therapy. However, as new endocrine and targeted therapies gain approval, choosing the best systemic therapy upon disease progression after frontline therapy is a topic of ongoing debate. Nearly 40 to 50% of HR-positive breast cancers have actionable genomic alterations and molecular testing should be a routine recommendation for patients with metastatic HR-positive HER2-negative disease. This can be performed repeating tissue biopsy at the time of progression or from archival tissue. Treatment options after progression on CDK4/6 inhibitors include alpelisib in combination with fulvestrant in patients with PIK3CA mutant tumors as seen in the SOLAR-1 trial, or capivasertib with fulvestrant in patients with a tumor mutation in (PI3K)–AKT–PTEN pathway as seen in the CAPItello-291 study, which will be discussed further. 

In approximately 30% of patients, progression on frontline endocrine plus CDK4/6 inhibitor treatment is caused by endocrine resistance, frequently involving activating mutations in ESR1. For those tumors, elacestrant, an oral SERD is an option as demonstrated in the EMERALD trial. For patients with a BRCA mutation, PARP inhibitors represent another option. If no mutations are detected, everolimus, an mTOR inhibitor, can be used based on the BOLERO-2 results. The phase 2 MAINTAIN and PACE trials, along with the phase 3 postMONARCH trial support changing the endocrine therapy backbone with or without switching the CDK4/6 inhibitor. In less resourced areas, fulvestrant monotherapy is still an option to delay cytotoxic chemotherapy, though its efficacy is limited when used as a single agent. Finally, after progression on at least one line of chemotherapy, antibody drug conjugates including sacituzumab govitecan or trastuzumab deruxtecan may be an option. 

Now focusing on the PI3K AKT PTEN signaling pathway, activating mutations in PIK3CA and AKT1 and inactivating alterations in PTEN occur in approximately half of luminal breast cancers. In June 2023, the CAPItello-291 trial was published and treatment with fulvestrant plus capivasertib, a PTEN AKT inhibitor, demonstrated a 3.6 month PFS benefit compared to fulvestrant alone, regardless of the presence of AKT pathway alterations. However, for those with tumors without AKT pathway alteration, an exploratory analysis showed that although there was a numerical improvement in PFS, it did not meet statistical significance, indicating that the biomarker positive population primarily drove the positive results noted in the overall population. Therefore, capivasertib plus fulvestrant was approved by the US FDA in November 2023 exclusively for patients with PI3K/AKT1/PTEN tumor alterations after progression on an aromatized inhibitor with or without a CDK4/6 inhibitor. The approved schedule of capivasertib is slightly different from that of other agents used in breast cancer. It is 400 milligrams taken orally twice a day for four days per week every week in a 28-day cycle in combination with fulvestrant. Diarrhea, rash and hyperglycemia were the most commonly reported grade three or four adverse events in the interventional group. I would like to highlight that even though the CAPItello trial excluded patients with glycosylated hemoglobin levels higher than 8% or those diagnosed with diabetes who required insulin, hyperglycemia occurred in 19% of biomarker positive patients treated with capivasertib, with nearly 2% of this population experiencing grade 3 or 4 hyperglycemia and some patients experiencing life threatening outcomes such as diabetic ketoacidosis. 

By way of comparison, hyperglycemia of any grade was three times higher with alpelisib therapy in the SOLAR-1 trial, occurring in 64% of the patients and grade three or higher hyperglycemia was seen in 37% of the patients. Diarrhea was the most common treatment related adverse event experienced by 77% of the biomarker positive population. Prompt use of the antidiarrheal drugs when needed, such as loperamide must be encouraged as untreated diarrhea can lead to dehydration and renal injury. Cutaneous rash occurred in 56% of the biomarker positive population in the interventional group and 15% experienced a grade 3 or 4 rash. Nearly half of the patients with cutaneous adverse reactions required treatment and this was the leading reason for dose reduction of capivasertib. 

In the biomarker positive population, the improvement in medium PFS were 4.3 months by investigator assessment. Overall survival data from the CAPItello-291 trial is still immature, but quality of life data was recently published in September this year and was assessed by the 30 item QLQ C30 questionnaire and the QLQ BR23, the breast module. According to Oliveira et al, global health status and quality of life were maintained for a longer period with capivasertib fulvestrant than with placebo fulvestrant except for symptoms of diarrhea which were significantly worse in the capivasertib group. The median time of deterioration of global health status and quality of life was twice as long in the capivasertib group being almost 25 months versus 12 months in the placebo fulvestrant group. These data reinforced the use of capivasertib in combination with fulvestrant for the treatment of HR-positive HER2-negative advanced breast cancer patients with PIK3CA/AKT1/PTEN tumor alterations who have progressed after an aromatase inhibitor-based therapy with or without a CDK4/6 inhibitor. 

Thank you for listening to JCO Article Insights. This is Giselle Carvalho. Don't forget to give us a rating or review and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcasts. See you next time.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. 

Guests on this podcast express their own opinions, experience and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity or therapy should not be construed as an ASCO endorsement.

Host Dr. Davide Soldato and guests Dr. Suzanne George and Liz Salmi discuss their JCO article "Overcoming Systemic Barriers to Make Patient-Partnered Research a Reality"

TRANSCRIPT TO COME

Dr. Davide Soldato: Hello and welcome to JCO’s After Hours, the podcast where we sit down with authors from some of the latest articles published in the Journal of Clinical Oncology. I am your host, Dr. Davide Soldato, Medical Oncologist at Ospedale San Martino in Genoa, Italy.

Today, we are joined by JCO authors Liz Salmi, Researcher and Patient Advocate, and by Dr. Suzanne George, who works as a Medical Oncologist at the Dana-Farber Cancer Institute where she acts as the Chief of the Division of Sarcoma. She is also Associate Professor of Medicine at Harvard Medical School. Today, we are going to discuss with Suzanne and with Liz the article titled, “Overcoming Systemic Barriers to Make Patient-Partnered Research a Reality.”

So thank you for speaking with us, Suzanne, Liz.

Liz Salmi: Thanks for having us.

Dr. Suzanne George: Yes, thanks.

Dr. Davide Soldato: I just want to make a brief introduction because I think that the concept of patient partner research is very wide and I'm not sure that all of the readers of JCO really have a deep understanding because I imagine that there are a lot of ways we can involve patient and patient advocates in the research process. And so I was wondering if you could give us a little bit of an introduction about the concept.

Dr. Suzanne George: Sure. I think the point that you raise is really important because there are many terms that are used, patient-partnered research, patient advocacy, but I don't think that there's a single definition as to what that actually means. In the context of our work, we’ve sort of summarized our experience through something called the PE-CGS or the Participant Engagement and Cancer Genome Sequencing network. And in that project, which is a Moonshot funded network, the intention is to have participants in research be true partners working with traditional academic research teams in order to develop networks specifically focused on cancer genomics. So what we've done, every center is a little bit different in the network, but we're really having research participants not just act, but really work on the research team from the beginning of the project inception all the way through the research project.

Liz Salmi: What brings me to the PE-CGS network is my 17 years experience as a person living with a low grade glioma, brain tumor or brain cancer and involving patients in the co-design of research is super critical because patients bring unique lived experiences that can shape research questions, study designs and outcome measures in ways researchers might not anticipate. And we're finding this through our network. So through my work, including my patient experience and brain tumor focused study designs, I've seen firsthand that patient insights can drive more practical implementations that ultimately benefit both patients and the researchers. And so the particular project I work on in the network, we've got like five different arms and different groups of cancer types that are being represented, so I'm basically focusing on the OPTIMUM study around how brain tumor patients can help in this study design. So in this project I serve as not just a participant in the research, but also as a patient co-investigator.

Dr. Davide Soldato: That is very interesting. And I think that we really captured the essence of patient-partnered research by having both of you here talking with us about the PE-CGS. And the second question that I wanted to ask is: I really think that the network focuses on something that is quite important right now and currently in medical oncology - so cancer genome sequencing, access to novel therapies - and I think that it's really challenging to imagine a way in which we can really get our patient and get patient advocates to help us designing new trials who are looking into this. And I just wanted to know, do you think that there is something that is particularly challenging when we are speaking specifically about cancer genomics and access to this type of drugs that are targeting specific molecular alteration? Because I think that in general it might be a little bit easier, maybe I'm biased on this, so you can also tell me if I'm wrong, but I think that it's a little bit easier when we are trying to design, for example, behavioral intervention or things that are more commonly found in oncology and a little bit more complicated when we are speaking about genomics.

Dr. Suzanne George: So I think that's part of what this network is trying to address, which is really what are the barriers and the opportunities around cancer genomics from the patient perspective and how do we make sure that that perspective is included as we're thinking about study design and inclusion? As Liz mentioned, this network has five different networks within the network, five different centers, and each center is slightly different with the population that it engages with. And so there's diversity there in terms of reaching out to different patient communities and partner communities around potential barriers for genomics research. I think one of the things though that we're finding across the network is that people want to be part of this work. People that have a lived experience of cancer want to help move the field forward. And what we ended up writing about was some of the barriers that get in the way of that. It's awesome to have people like Liz that are like all in and then there's people who are on the other end of the spectrum that want to share their information to help move the field forward around genomics, but then there's all these barriers at the systems level that get in the way of that. So I think that that's one of the challenges we're trying to overcome and learn about across the network.

Liz Salmi: Yeah, I think I bring this really interesting, I can't say I'm really interesting, but I think I bring this really niche perspective. Not only am I a person living with a brain tumor and I'm a co-investigator but also like a participant in this study. I also, in my day job, I'm an investigator as part of the director of communications and patient initiatives on the OpenNotes lab at Beth Israel Deaconess Medical Center. And our lab really focuses on how open, transparent communication between doctors and patients improves care. And that's been going on for longer than I've been around on our team. But what I bring to that lab is I focus on engaging both patients and clinicians in spreading the awareness about the power of how easy access and transparent communication, access to information across healthcare settings helps patients feel more involved and informed in their care.

And I work specifically, it's a really niche area. I work on projects that aim to expand access to notes and test results in diverse care settings, really helping tailoring initiatives so that various patient communities can understand how they can be involved in these types of research projects. Ultimately that's what brought me into this space. I might be one of the first generation of patients that actually starts helping co-design studies on things like this. And I think that across a lot of healthcare settings cancer is really what we're focused on. But patients are now increasingly being involved as research collaborators. And there's many different funding institutions such as the NCI but also PCORI they now mandate that funders reflect a shift towards more patient centered research frameworks. So it's like the PE-CGS network isn't the only group that's being funded to do research in this way. And I think other investigators, even outside of the cancer space, but specifically in cancer, need to learn how to do research in this way.

Dr. Suzanne George: Yeah, I agree. And I think the other thing that we need to do is if people want to participate and that participation in many of these networks has to do with record sharing and data sharing, the system needs to accommodate that. If people want to share their information in order to allow research to be performed, then we need to make sure that that can happen, and that it's not that the institution systems don't connect with someone else's systems or that you to pay X, Y and Z dollars for the data to go A, B and C, or that some places are on this EHR and some places are on that EHR and so, sure, you can share it, but you have to go through all of these hurdles in order to make it happen. When a patient signs a consent form that says, “I want my data to be used,” we as an investigator community, we owe it to that patient to make sure that their information is being part of the data set that will be used for learnings. And that's part of what we wrote about, is the lots of behind the scenes things that just get in the way and that we need to work towards improving.

Liz Salmi: Both Suzanne and I are really passionate about this stuff. And as a person living with a brain tumor for the last 17 years, I'm a chronic research participant. I always, always, am really curious. I'm like, “Yes, let me contribute my data. Whether that's electronic health record data or maybe I'm being interviewed about certain aspects of the cancer care experience.” And the one thing that bummed me out for like the first 10 years of being this chronic research participant is I would enroll in things, I'd be interviewed for things, I'd fill out these surveys and then I never heard anything about what happened with that information and that time I spent. And people would send me like a $10 gift card to Amazon, like, “Thanks for participating,” but really what I wanted to know is like, did you do anything with that? How did that inform things? So that really annoyed me to the point where I was like, I'm just going to be part of the research process and really figure out how we share that information back to everybody who had spent so much time. And so my participation in this space is like, “Let's change it. Let's give people information back.” And now I know it takes a really long time to have a finding that could be published somewhere that we then get it back. But closing the loop on the communications gap is something I'm really passionate about.

Dr. Davide Soldato: Do you think that we are changing a little bit this perspective? I feel like we are getting a little bit better in creating patient communities of patients who are included in specific clinical trials. And then we do the effort of creating a community, of keeping people really involved with the research that they are participating in. I think that we are not quite there yet, but I think that we are making some kind of steps in that direction. For example, trying also to inform patients to participate in the study when the publication that is related to that specific study comes out. What is the benefit? What have we discovered? I think that we are not quite there yet. There is a lot of room for improvement, particularly in the way I think we communicate these to patients who participated in research. But I have the impression that we are making some steps forward. So I don't know. Do you share the same thoughts?

Liz Salmi: So Dr. George talked about the PE-CGS network and then there's five different cancer types being studied. So the thing I can reflect on is what we've done in the, this is a really long acronym but, Optimizing Molecular Characterization of Low Grade Glioma. Say that 10 times fast. So our particular group is people who donate tissues about their brain tumors. We're really collecting data from people with multiple brain surgeries over time, which is really complicated and to make that process easier. And then once those tissue samples are stored somewhere, studying that information about what changes in the brain tumors over time and then also giving those results back to people so they can take that research level data and bring it back to their neuro oncology team and say, “Hey. Here's what I found out, “and having a conversation.

So, this is a long multi touch point study and in order to do that, to even make that possible is the individual patients need to understand what's in it for them. They're donating precious tissue in order to make the research process work. And so in order to do that, it's not just the investigators saying, “Hey. Give us your brain tissue, peace out.” It is we have a whole research advisory council of people living with these particular tumor types who help us co-design how do we do that outreach, how do we explain why this is important, or how do we message the importance of this work so they understand,“Oh, this is what's in it for me and this is what's in it for other people like me.” And from there then with that process, which again I mentioned, all of these multi-step processes, once we're able to understand how patients want to hear that information, what's in it for them, then we bring it back to like those bench scientists, investigators going, “Okay. And here's how this workflow should work for the patients,” and design everything around the patient experience before we even care about what's happening from the scientist researcher perspective.

Dr. Suzanne George: I agree. I think to your point, I think the fact that we're all here today talking about this is just like you said, is that we are making progress, right? Like we're even here having this conversation. Just like you said, I think there's opportunities to improve and further refine the communication and the involvement back in the patient community. When I think- if I put on my clinical investigator hat, I'm very involved in PE-CGS, but my primary research interest historically has been clinical trials and drug development. And I think that our approach in communicating results back has just not been consistent. But I do think that there's opportunities, just like you said, to provide summaries of information to loop back. I don't think that we've completely solved: What do we do? How do we provide information back to loved ones of patients that may no longer be alive that participated? How do we provide information to people who maybe we don't have their contact information? What if we lose track of them? How do we also make sure that we give people the choice to know? Do you want to know about this or would you rather just participate and then give space to that research? Because maybe that's how people's best for them. So I think that you're right, we're making progress, but I think that there's also a lot more that we can do. So I'm glad we're talking about it.

Dr. Davide Soldato: How much do you think that directly involving patients in this process, like asking them directly and co-designing the trial from the very beginning and understanding the level of information? This might also be another question inside of the question. So first, how much co-designing this type of research helps, and then do we also need to further refine at that level of communication, different communication depending on the level of information that different people want to have? Because I think that that's another level of complexity that we need to work towards at a certain point. We need to work on that first level of giving back the information. But then I think that there is also the other point of providing the information and information that should also be probably adapted to the cultural belief of different patients, to the ethnicity or to whatever cultural background or social background or whatever they may place their most interest in.

Dr. Suzanne George: So I think that you're 100% right on all of those points. I think those are all topics that need to be considered. We may be able to get to a certain degree of granularity around those communication points, but on the other hand, we also want to be able to communicate broadly and accessibly as possible.

One of the interesting things about PE-CGS, as Liz was mentioning, is each of the five centers has a slightly different focus. For example, one of the centers is focused on American Indians and Tribal Nations, and the communication practices coming out of that center are really unique and really very special and something that's been really, I think for me, very fascinating to hear about. Because to your point, like, just the strategy and what's considered appropriate is just different. I think if we hope to build a research world where our research participants and research data come from a broad swath of the population that really represents the population, the only way that we're going to be able to do that is find ways that bring meaning across the population as well. And that may be different based on where people are coming from and where people are at in their own journeys and in their own lives. But it's on us to be open to that and like to hear that, so we can do the right thing.

Dr. Davide Soldato: And I think that this is one of the objectives of the PE-CGS, really trying to bring this type of research participation to really diverse and underrepresented populations, not only in terms of cultural background, but I also think about different types of tumors. Like Liz was referring about brain cancer or low grade glioma, which is a very niche population. And I also think about sarcomas, for example, the degree of variability that we have in that specific type of disease is such that we really need to probably find different ways to communicate also inside of this diversity in terms of single patient and experiences, but also in terms of single diseases.

You were speaking a little bit before about the fact that the manuscript is really on the barriers that we would need to identify and then to change to make this system a reality. We were talking a little bit about consenting information and consenting the sharing of information, and I think that you make a very interesting point about the consent process when we are designing research. Could you give a little bit of your impressions about giving informed consent? What we need to change, how can we improve?

Dr. Suzanne George: The bottom line is the consent process needs to be simple, clear, and transparent. And sometimes I feel, because the traditional way that we've always gone about consent is frequently consent is as it should be in many ways. These consent forms are developed from a regulatory framework. What are we required to do to consent and how do we meet those requirements? Sometimes that becomes directly at odds with how do we do this simply, clearly and transparently? And I think as a research community, we have to be able to find a common ground there. That has to include regulatory requirements, that has to include IRBs. When we think about consents and work with our patient communities on this, everybody agrees the consents need to be more simple, except the IRB or maybe the IRB agrees, but it's this tension between how do we make it simple, clear and transparent and not get so bogged down in the regulatory that we lose that intent.

Liz Salmi: It's complicated. As a person, I mentioned, I'm a chronic research participant living with a brain tumor for 17 years. I remember enrolling in studies and seeing things that are just so complicated. I'm like, “Well, I'm just going to sign off.” I imagine somewhere somebody who knew more than me said, “I should just fill out this thing.” And then as I switched to the research world, I spent more time digging into, “Wow, this is a really complicated consent,” versus, “This is a really streamlined consent and I love this.”

And throughout my work with Dr. George and others on the PE-CGS network, an example of a good consent that's easy for people to understand is what the NIH All Of Us research project did, where they're trying to get a million people, more than that, signed up to be in this longitudinal study. And their consent is to go to their website and they have a whole bunch of short YouTube videos. There's a kind of like a quiz involved and they're animated, they have multiple languages involved. And I signed up for that study and I was like, “This is a beautiful consent.” And it's a very plain language. And more consents like that. If you're looking for a good example, go there. I have not been paid by them in any way. I'm a participant in their study.

I'm not sure if you guys and your listeners are aware, but there was I think, October 19th of this year or 2024, there was a special communication published in JAMA on an update on the Helsinki Principles for Medical Research involving human participants. And what they're saying is an ethical update is patient engagement in research, which emphasizes the need for continuous, meaningful engagement with research participants and their communities throughout the research life cycle, before, during and after studies. And so this is what we're talking about here. And it's now been embedded in these updated principles.

Dr. Suzanne George: That's really great and I agree with you. I think the All Of Us consent process is very accessible. It feels like you can understand it. But the other thing is that, again, I also am not directly involved with All Of Us, but the other thing about it is that they also have a high-touch way to consent where they have navigators and people that will go into communities in a very resource intensive way. So there's all different ways to go about it. We need to find a way that we can balance the complexity around regulatory and the simplicity and transparency that we need in cancer research.

Dr. Davide Soldato: Do you think that in terms of patient engagement we are doing better in academic sponsored research compared to sponsored research? A little bit of a provocative question maybe.

Dr. Suzanne George: I think that's a really interesting question. I think this idea of participant engagement and involvement is being infused across the research community. And in part, the FDA has prioritized it as well. I think the industry sees the FDA prioritizing this as well. And I think that there are many companies that are involving participant and advocacy communities in different ways in the study design, in the study process early on. So I think it's happening.

Liz Salmi: I'll be spicy. I've been a participant, I've been an investigator, co-investigator on studies and I have been reached out to often by pharma of, “Hey Liz, brain tumor patient advocate, would you be kind of like the poster child of our study or be involved in that way?” And I personally want to have no work in that space. I have no interest. However, I am approached, and other people living with cancer have been approached, by industry about lending their likeness or being commercials. And I don't think there's enough education to patient advocates of what that necessarily means, pros and cons. But I also can't speak on behalf of all of the patient advocates who might want to see that's a way that they could lend their voice and advance research. I personally think that there needs to be more involvement from the academic side of creating spaces where patients can be involved in the co-design of research and they also get compensated for their time fairly at the same level or some version of it in a way so they don't just jump to the pharma side of things. But that's an opinion that I have. Opinions.

Dr. Suzanne George: I think it's really interesting the point that you make about providing more awareness or information about what it even means to do these things from a patient side. I certainly don't know that side as well, but I do see, often, the term patient advocate used very frequently in many different contexts that mean many different things. And I think that there's an opportunity there for understanding more about what that really means and what it can mean.

Liz Salmi: Yeah. We want to involve patients, we want to do patient engagement. The BMJ or the British Medical Journal, have this new policy in place for patients as reviewers of research. And what I find interesting with the BMJ is they also ask patients to declare their conflicts of interest. So this is kind of a new space. If you're involved in patient research or perhaps working with pharma, patients, if you're involved at that level, should also be declaring their conflicts of interest if they're getting paid by a pharma. Or do I have a conflict now that I'm doing this cool ASCO podcast? Maybe. But do we want to overburden patients with tracking all this information? So it's a new world. The more we have access to information, the more we share information, the more we can read studies and we co-design, there's a new space I think over the next 5 to 10 years where how do we define this in a transparent way.

Dr. Suzanne George: Yeah, I think you're right. I know that we're getting long, but I just want to say one other thing about that, which is that you're right. If we're bringing patients in to be partners, then we have to treat each other that way. We have to acknowledge- I think this issue that you raise about compensation and about paying people for their time or acknowledging people for their time, I think that's really important and very under-discussed. Liz and I were at the annual meeting for the PE-CGS and someone was there giving a talk about- this was a guest speaker that was giving a talk about a very large high impact grant and that included a patient advocacy kind of module, let's say. And they put in a specific funding and budget for that component that included compensation for the people- from the people in the advocacy community that were spending their time. And the PI of this project, again, not to get into the details of it, but they were sharing that they got a fair bit of pushback on that. But the PI pushed back and said, “Listen, we're compensating other people for their time. These guys, we want them to be partners, we need to treat them as such.” And I think that also again, kind of we're in a new space, but if we're going to do it right, then we have to acknowledge that we're partners.

Dr. Davide Soldato: But I think that maybe an experience like the PE-CGS probably can be also a network for expanding awareness for patient advocates and also for creating sort of a new culture about what does that mean and how can we also improve on that part. Because in the end, if we want to engage, we also need to provide patients with the instruments to engage in a way that we think it's both useful for them, that can make research better, but can also make them at the exact same level as everyone who is participating in that research, which I think it's the bottom line of all the concepts that we are discussing right now.

Liz Salmi: Yep.

Dr. Suzanne George: Yes, I agree.

Dr. Davide Soldato: So I think we have covered a lot of things. Just wanted to make one last reference to a point that Suzanne mentioned earlier, which is the interoperability of systems. And I think that when we come to the cancer genome, that is very important, being able to share information, especially for those diverse and less common cancer types that we were discussing earlier. There is a lot of work in gaining all that information and we need to be able to gather all of that information in the same place to advance research. You were mentioning before that the process is actually very complicated and I was wondering if in the network you are already working on some potential ways to address this type of issue.

Dr. Suzanne George: I think our first step is really just calling it out, acknowledging how hard this is and what the barriers are. Oftentimes I think in research, we don't talk enough about what our methodologic barriers are. We talk more about what our results are, but not like how hard it is. But like in our projects, the Count Me In project, my network that I'm involved with, we're doing rare tumors. We can only do the United States and Canada because of privacy issues. And we're doing a completely web based platform. So we have the technology. But the privacy laws are impeding our ability to involve other parts of the world. And even within the United States, it's not as easy as we would like to get records. For example, despite the fact that people are saying, “Yes, use my records.” But then it's like, “Okay. Well, that's not that easy. How are we going to get them?” We had to hire a third party vendor in order to get the records, in order to manage all the different consents and releases that were needed across all these different hospital systems. So I think the first question is just calling it out and then from there working together as a community to try to see what the solutions can be, because we need to come up with those solutions.

Liz Salmi: Yeah, we're in the same camp as Dr. George and the fact that of the five partners, we're not associated with one particular institution. So we can reach out around the country and get access to those records. And we need them at multiple points in time, over time and it takes a lot of effort and work. And it's not like you could just, say, call hospital A and they have all the information. It's like all of the calls to all of the other sites. And it's not just from one surgery, it's from two or more surgeries. But also the way that people stay involved, and, by people, I mean patients and family members, there's this promise that at some point you're going to get some sort of information in response. Like, it's the “what's in it for me?” aspect of it. We do interviews with those who've been enrolled in the study, those who could be potential enrollees in the future because they've only had one surgery. And what we're learning overall is there's this altruistic nature that people have of- they want to participate in the research because they're like, “Here's my horrible cancer experience. I know other people are going to go through this as well.” There's this guiding light of “I want to do something, and I'm not going to be the person that creates the cure, discovers the genome or whatever for this particular cancer type. But my little bit of participation in this multiplied by 20, 30, 100, 1000 people, is what is going to lead us to the next phase in development and is going to move the needle for this particular tumor type or other cancer types.” And so what I think the impact in this space and participant engagement isn't just something we figure out, like a little research method and a little finding for one small tumor type, it's like the methods to do that is the big impact. The method around participant engagement can impact even beyond the cancer community.

Dr. Davide Soldato: Yeah. As Suzanne was saying, we need to be in a system that really helps us and allows us to do that. So I think that you really have a lot of things to work on inside of the network.

Dr. Suzanne George: I think one thing that I would say is I think that this issue of interoperability is acknowledged as a challenge. We refer to several different initiatives across the US where this is supposed to ideally change over time. I think people want it to change over time. I think investigators at the ERTC want it to change over time. I think different countries are working on this. And I think, again, the first step is getting us at the table talking about it, and then figuring out ways to move it forward. And I think it's there. I think that there is the will. We just have to figure out the how and continue to work on that together, because there's just a tremendous opportunity. I live in the rare tumor space, and between the FDA and the EMA and the regulatory, the national and the international research groups, the patient communities, people want this to be solved and I do hope that we will be able to get there.

Dr. Davide Soldato: So I would like to thank Liz and Suzanne for joining us today.

Dr. Suzanne George: Thanks for having us.

Liz Salmi: Thank you.

Dr. Davide Soldato: Suzanne, Liz, we appreciate you sharing more on your JCO article titled, “Overcoming Systemic Barriers to Make Patient-Partnered Research a Reality.”

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DISCLOSURES

Liz Salmi

Speaking Honoria: Medscape. Research Funding (Inst): Abridge AI, Inc., Yosemite.

Dr. Suzanne George

Honoraria CStone Pharmaceuticals Consulting or Advisory Role Blueprint Medicines, deciphera, Bayer,  Lilly, UpToDate, Research to Practice, MORE Health, Daiichi, Kayothera, Immunicum, BioAtla   Research Funding Blueprint Medicines, Deciphera, Daiichi Sankyo RD Novare, Merck, Eisai, SpringWorks Therapeutics, TRACON Pharma, Theseus Pharmaceuticals, BioAtla, IDRx, NewBay Pharma, Acrivon Therapeutics   Patents, Royalties, Other Intellectual Property Company name: UptoDate

Stock and Other Ownership Interests Abbott Laboratories and Pfizer Recipient: An Immediate Family Member

In this JCO Article Insights episode, Rohit Singh provides a summary on "First-Line Nivolumab Plus Relatlimab Versus Nivolumab Plus Ipilimumab in Advanced Melanoma: An Indirect Treatment Comparison Using RELATIVITY-047 and CheckMate 067 Trial Data", by Long et al, published in the November issue of the Journal of Clinical Oncology. The article provides insights into the use of the two dual immune checkpoint inhibitor regimens in patients with untreated advanced melanoma.

TRANSCRIPT

Rohit Singh: Hello and welcome to JCO Article Insights. I'm your host Rohit Singh, Assistant Professor at the University of Vermont Cancer Center and today we'll be discussing the article “First-Line Nivolumab Plus Relatlimab Versus Nivolumab Plus Ipilimumab in Advanced Melanoma: An Indirect Treatment Comparison Using RELATIVITY-047 and CheckMate 067 Trials,” authored by Dr. Georgina Long from the Melanoma Institute of Australia and her colleagues. 

So as we know, nivolumab plus relatlimab and nivo plus ipi, I'm going to refer to as ipi-nivo moving forward, are dual immune checkpoint inhibitors regimens that are approved for treating patients with advanced melanoma based on the phase 2 and 3 RELATIVITY-047 and phase 3 CheckMate 067 trials respectively. Nivo plus relatlimab is the only dual PD-1 and LAG-3 inhibitor regimen approved for treating patients with advanced melanoma and relatlimab is the first in class human IgG4 LAG-3 blocking antibody. Ipi plus nivo is a dual PD-1 and CTLA-4 inhibitor regimen. 

So this paper basically is an indirect treatment comparison using a patient level database from these trials and this pretty much was conducted because of the absence of head to head trials looking at different regimens in advanced melanoma in first line setting. In this trial, the authors tried to compare these two trials. However, it's always hard to compare two different trials and we usually don't do cross trial comparisons. The problem is that the groups might be different to begin with. For example, one group might have younger patients, healthier patients, while the other might have older or sicker. These differences can make it hard to tell if the treatment caused improvement or if the groups were different to begin with. In this trial, researchers use inverse probability of treatment weighting to adjust the baseline differences between the two patient groups or between these two trials. Inverse probability of treatment weighting is a method used in research to help make a fair comparison between two groups when studying how a treatment intervention works. Basically, IPTW helps level the playing field between the two groups or like two trials for this paper. So, it calculates the likelihood of receiving a treatment. For each person, for each patient, researchers estimate the chance they would have gotten the treatment based on their characteristics like age, health, condition, their baseline staging, and based on that they create weights. People who are less likely to get the treatment but did are given more weight, and those who are very likely to get the treatment are given less weight. The same is done for the group that didn't get the treatment, and then they rebalance the groups. By applying these weights the group becomes more similar in their characteristics as if everyone had an equal chance of getting the treatment. This way, IPTW helps researchers focus on the effect of treatment itself and other differences between the groups. It's like adjusting the scales to make sure you are comparing apples to apples. 

The key outcomes the authors are looking at in this one was progression free survivals, overall survival, confirmed objective response rate, melanoma specific survival, and treatment related adverse events. Looking at the results of this cross comparison trial, first looking at the PFS or progression free survival, both regimens ipi plus nivo and nivo plus relatlimab, showed similar PFS. At 36 months, PFS was 36% in nivo-relatlimab versus 39% in the ipi-nivo regimen with a hazard ratio of 1.08 indicating no significant differences. Looking at the overall survival at 36 months, overall survival was 57% in both the treatment regimens with a hazard ratio of 0.14, again, indicating no significant differences. Now looking at another confirmed objective response rate, confirmed objective rates were similar between both treatment regimens after weighting, 48% versus 50% with an odds ratio of 0.91 suggesting comparable response rates between the two regimens. Looking at melanoma specific survival at 36 months it was 65% versus 62%. Both treatments had similar melanoma specific survival with a hazard ratio 0.86. 

An interesting thing in these results was subgroup analysis. Subgroups showed larger numerical differences in efficacy which favored ipi-nivo over nivo-relatlimab that included acral melanoma with a hazard ratio of 1.42 and OS with a hazard ratio of 1.72 in favor of ipi-nivo. Similarly for BRAF mutant melanoma, it showed a confirmed objective response rate with odds ratio 1.54 and same applied to mucosal melanoma with odds ratio of 1.59 and patients who have high LDH more than two times upper level limit. Looking at the safety and adverse side effects, nivolumab plus relatlimab had fewer grade 3 or 4 treatment related adverse effect which is 23% versus 61% and fewer any grade treatment related adverse events leading to discontinuation which was 17% versus 41%, which means 41% of the patients in the ipi-nivo arm lead to discontinuation. However, I would like to add to that that ipi-nivo was conducted much earlier and at that time we were still kind of assessing and trying to understand the immunity adverse effects, how to manage them, which probably could have made discontinuation more common compared to a nivo-relatlimab trial. By that time we definitely had much more experience dealing with immunity adverse effects.A couple of things mentionable in this, notable rates of hepatic and GI grade 3 or 4 treatment adverse events were lower in nivo plus relatlimab than with ipi-nivo, although the onset of any grade endocrine GI hepatic or skin related treatment related adverse events occurred most frequently in both treatment arms and in less than three months from randomization. 

So looking at all this data and looking at all this, it definitely seems like both the trials are very comparable in terms of efficacy, though nivo plus relatlimab seems to have a better safety profile. This trial does have some strengths. It does use the patient level data from two large well conducted trials allowing for a robust comparison and inverse weighting which would definitely better help balance baseline characteristics, enhancing the reliability of the results, and it does lead to comprehensive assessment of both efficacy and safety outcomes, and provides a holistic view of the treatments. Given all this, definitely the fact that it's a cross comparison trial which leads to a big limitation, as I already mentioned, like definitely two trials, it's hard to compare two trials which can have its own inherited biases. So it has some differences in trial design, conduct and follow up times. Small size subgroup analysis definitely limits the ability to draw definite conclusions from those groups. There's definitely some inherent uncertainty with direct head to head cross comparison trials. 

Looking at the future direction I would take from this trial, if we can have a direct head to head trial because both of the treatments are proven first line setting, it will be comparing these two regimen that can definitely provide more definite evidence and further research is needed to explore the efficacy of these regimens in specific subgroups. As I mentioned in this, some subgroups showed increased benefit in the ipi-nivo regimen, however, they were very small sample size so we need more research exploring those subgroups. One other part in both these trials, patients with active brain mets were excluded. However, there's a phase 2 trial looking at ipi-nivo in active brain mets patients. So I think assessing patients with active brain mets moving forward is also a crucial part looking at, because often, patients with advanced melanoma develop brain mets. It does lead to some unanswered questions like long term survival and quality of life. How do these regimens compare in terms of long term survival and quality of life? While the study provides data on PFS and OS, long term survival and quality of life metrics are essential for understanding the full impact of these treatments. Optimal sequencing strategies: what are the optimal sequence strategies for these patients who progress on one regimen? There is data suggesting that patients may respond to alternative regimens after progression, but more research is needed to establish the best treatment sequence. And real world performance: how do these treatments perform in real world settings outside of clinical trials? Real world data can provide insight into the effectiveness and safety of these regimens in a broader patient population. 

So, in summary, nivo plus relatlimab offers similar efficacy to nivolumab plus ipilimumab but a significantly improved safety profile, making it the potentially preferable option for patients with untreated advanced melanoma. However, results should be interpreted with caution due to limitations of cross trial analysis for certain subgroups like acral melanoma, mucosal melanoma, BRAF mutant melanoma, and patients with high LDH more than two times off upper normal limit. The trial showed that there's a trend definitely with ipi-nivo may be more beneficial. Also, today data on the use of nivolumab plus relatlimab in active brain mets has not been reported. Based on these existing data, ipi-nivo remains a standard immunotherapy for patients with active brain mets. Further research, including direct head to head trials is needed to confirm these findings and explore optimal treatment strategies. 

Thank you for tuning into today's episode. We hope this detailed summary of the study comparing Nivolumab Plus Relatlimab and Nivolumab Plus Ipilimumab in advanced melanoma has been informative. This is Rohit Singh. Thank you again for listening to JCO Article Insights. Don't forget to give us a rating or review and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcasts.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. 

Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity or therapy should not be construed as an ASCO endorsement.

Host Dr. Davide Soldato and Dr. Aaron Mitchell discuss the JCO article "Quality of Treatment Selection for Medicare Beneficiaries With Cancer"

TRANSCRIPT

Dr. Davide Soldato: Hello and welcome to JCO After Hours, the podcast where we sit down with authors from some of the latest articles published in the Journal of Clinical Oncology. I am your host, Dr. Davide Soldato, medical oncologist at Hospital San Martino in Genoa, Italy. Today, we are joined by JCO author Dr. Aaron Mitchell. Dr. Mitchell is a medical oncologist working at Memorial Sloan Kettering Cancer Center where he is also part of the Department of Epidemiology and Biostatistics. Dr. Mitchell specializes in treating genitourinary malignancy and has a research focus on improving how the healthcare system helps people with these and other cancers. So today, Dr. Mitchell will be discussing the article titled, “Quality of Treatment Selection for Medicare Beneficiaries with Cancer.”

Thank you for speaking with us, Dr. Mitchell.

Dr. Aaron Mitchell: Well, thank you for inviting me. I'm very glad to be here.

Dr. Davide Soldato: So I just wanted to introduce the topic by asking a couple of questions, very general, about the background of the article. So basically you reported the data using the SEER-Medicare to assist to assess the determinants of optimal systemic therapies delivery and selection. So, in particular, you focused on individuals that were diagnosed with cancer who were Medicare beneficiaries and in particular were part of the low income subsidy, which is also known as LIS. So I just wanted to ask you if you could briefly explain to our listeners how this program works, and what was the rationale of the study, and if there is any element of novelty in your study compared to what was done before the study was published.

Dr. Aaron Mitchell: Yeah. So that's a lot to cover, but yeah, a lot of opportunity to introduce the low income subsidy program which is a very important part of the Medicare program for prescription drugs, but often one that flies under the radar a little bit in the policy discussion. So this subsidy was created synchronously back with the Medicare Part D Program, which was created in 2006. There was some anticipation that for some high cost drugs, not all patients would be able to afford them even with the Part D program insurance as it was being created. And so they created a pathway to give an additional subsidy to some patients who had low income, who were anticipated to being at need and needing that assistance to afford high cost drugs. As the number of high cost drugs has really risen since 2006, this program has played an important role in helping patients afford drugs, especially those who need very expensive cancer drugs. 

And what this program does is, once you meet the eligibility requirements, which require patients to have both quite a low income. So if you're single, that is at 135% of the federal poverty limit or below, and it also places some restrictions on assets. You also have to have low assets, so low income and low assets in order to qualify for the subsidy. But then once you do, the subsidy is really quite large. Patients who qualify for the LIS at the full subsidy level will pay about $10 per month per drug, even for specialty cancer drugs. So if you think about drugs such as those that we use to treat prostate cancer, my specialty, drugs like enzalutamide or XTANDI that run $15,000 to $20,000 per month, the out of pocket cost for a low income subsidy beneficiary is $10. So that is a huge discount. $10 isn't nothing, but even for someone with a low income, if they've got one or two cancer drugs that are at this rate, it's something that they can often afford. 

This program applies to Part D cancer drugs that are prescription drugs basically. By and large, these are oral pills that patients are taking on a daily basis at home. These are the drugs that the low income subsidy program applies to. So if a patient needs a drug like that to treat their cancer, then they are able to receive it at very low cost. And what you'll see is a patient- in the studies that have been done, when a patient has low income, low enough for them to be able to qualify for this program, they then have better access to these drugs. You see increased adherence rates, you see increased prescription fill rates. And then when someone, when their income is just high enough to no longer qualify for this program, and they go back to regular Medicare Part D coverage, that's when the problems arise. So it's like as your income moves up the scale, you actually get more problems affording your cancer drugs. So that's the state of the literature so far. 

And what we realize though, is that all these studies that have looked at the low income subsidy have really focused on just the Part D drugs themselves, the oral drugs. And that's certainly not all of cancer care. There is a growing number of oral drugs, but for many cancers, especially when you're talking about immunotherapy drugs or new systemic radioligand therapies, these are not Part D drugs, these are Part B drugs. And so even if you are low income and you're qualifying for this subsidy, it's not going to help you if you need a Part B drug. Yes, there are certainly a whole host of other programs and different avenues that we can get patients assistance, but some percentage of them, even though they're low income and high need, would not have assistance with a Part B drug. 

So now, in coming back, the long answer to your question, our rationale was, let's look at these Part D low income subsidy patients and let's see what their access looks like, not just to the oral drugs, but to cancer care writ large. And can we study where they're fitting into the system, not only when they need oral drugs, but when they need any kind of cancer care across the board?

Dr. Davide Soldato: So basically, just to summarize, it was an extension of previous literature, but specifically evaluating whether novel regimens that use, for example intravenous drugs, they were covered at the same level and whether there were any inequities in access to cancer treatment under this specific program, which is the LIS.

Dr. Aaron Mitchell: Yes, I'd say that's a fair summary.

Dr. Davide Soldato: Okay. So more or less, you included 9,000 patients inside of the study and 25% of them were beneficiaries of the LIS program. And you specifically looked at factors that could be associated with not receiving therapies at all, and also whether the quality of care that these patients were receiving were any different compared to those who were not part of the LIS program. So I just wanted to see if you could guide us a little bit in the results, whether you see any kind of differences when we look at access to any type of systemic therapies and whether being a part of the LIS program modified access to the drugs.

Dr. Aaron Mitchell: Let me take this opportunity also to highlight a feature of our study that differentiates us a little bit from previous work that's been done. And this is around the specific definition of quality that we use. I know quality is in the title of the manuscript, but I think it's important to emphasize exactly what we mean in this study when we say quality, and it's something very specific. So our measure of quality references back to the NCCN guidelines, which I don't think our audience needs much of an introduction to that. It's the most worldwide recognized standard of care guidelines for oncology practice. And we specifically looked not only at the NCCN guidelines, but at their evidence block scoring system. So what we did was we looked not only at one set of guidelines, but we looked at guidelines across time. We looked at guidelines across our full study period, which was, give or take, 2015-2018, depending on the cancer. And we looked at each point in time to see what was the treatment regimen that was recommended by the NCCN guidelines as being preferred. Some of them make that designation, some of them don't. If there was not a designation of preferred, then we turned to the evidence blocks. And the evidence blocks, we then apply several different measures to kind of rank treatments from those that get high scores for efficacy and safety to those that get low scores for efficacy, safety and the quality of evidence. So we basically come up with a kind of a rank list of the recommended treatments at each point in time. And then we look at the ones that are the highest, we say which are the most highly recommended treatments at any given point in time. That then becomes our definition of quality treatment. And I'm saying this with air quotes, we use the term “optimal treatment” in the study. Did they get that treatment? If there were ties, you could have gotten either of the two treatments that got the equally good score, did you get that treatment versus did you get anything else? 

So then getting back to our analysis, what we really did was kind of a two-stage study. First, we put all of our patients into our pool, into one big analytic model. And we looked to see what are the factors that predict or are associated with a patient either getting no systemic therapy or any systemic therapy. And then as a second question, we look at the patients who got some form of systemic therapy, and then we ask, again, what percentage of those got the optimal treatment or high quality treatment as opposed to one of the more lowly recommended treatment regimens? So that's how we asked it. We found that patients who were low income subsidy recipients, the low income ones, they were both less likely to receive any systemic therapy. And then even the ones that receive systemic therapy, the ones who made it in the door to see their doctor or their part of the system, they still were less likely to get the optimal treatment that was recommended for their cancer type at the time that they were diagnosed.

Dr. Davide Soldato: So basically, even when you are a part of this subsidiary program, you still have a lower access to any type of treatment. And even if you get treatment, you kind of get the ones that were not the preferred according to the NCCN guidelines, or at least they were not scoring as well as those specific regimens. But I think that what our audience might be wondering about is that frequently there are also some other types of characteristics, for example, age or number of comorbidities, which can be associated with having a low socioeconomic status. So I was wondering whether in the analysis you kind of looked specifically also at patient factors, for example, income rather than age or comorbidities, and whether you found any significant association with those and whether it was something that you planned to do in your study.

Dr. Aaron Mitchell: Yes. So we looked at many patient factors and those included age and they included the degree of comorbidity. And what we saw with respect to those characteristics was not too surprising. We saw that patients who were older were less likely to receive systemic therapy. We saw that patients who had more comorbidities were also less likely to get systemic therapy. And then across our different designations of treatments, we saw that those patients were also less likely to get the optimal treatment for their cancer. This result though, we would say it certainly needs more study in the future, but it's not immediately concerning. And that is because for patients who have more age, more comorbidity, those often correlate with frailty. And so it could be that these patients aren't getting optimally treated or it could be that their oncologists are just making clinically appropriate decisions about patient selection. 

We saw as we were doing this work that the treatment regimens that are often getting the highest recommendations from the NCCN, hence, it would become our definition of high quality optimal treatment, are often ones that are aggressive. They're often ones that are multi-drug combinations. They're often ones that it's not just your old antineoplastics, it's the antineoplastics plus an additional immunotherapy or plus a targeted drug. So it's the ones that are more aggressive by and large, and that might be in some cases more than a patient who is older, more frail, could be able to tolerate. And so the oncologist might be making inappropriate judgment to say I'm going to do something a little bit less aggressive here and make an appropriate trade off between anti cancer efficacy and safety. 

I think we've got kind of a bookmark there and we can look at those trends in the future. So we saw that kind of as expected, and then we turned and looked towards the low income subsidy. And our premise there is, well, your income shouldn't predict what you're getting clinically. In an ideal world, you'd be able to get the appropriate treatment for a patient, and not depend on whether their income is above or below 135% of the poverty limit. So that one seems more like on its face an immediate concern.

Dr. Davide Soldato: Thank you very much for the explanation. I was just wondering, did you make some kind of selection when you were analyzing specific diseases or settings where you included just metastatic patients or you also included patients with early stage neoadjuvant treatments? Because I think that it is also very interesting from the perspective of the objectives that we have as oncologists when we are administering systemic treatments.

Dr. Aaron Mitchell: Yeah, thank you for bringing that up. That was also one of the goals of our study was to be broad. And we wanted to look for factors, whether it be low income subsidy, whether it be age, socioeconomic background, etc., things that would be broad predictors of outcomes, and by which I mean care delivery outcomes across the board. So not just for, let's say, metastatic breast cancer, but also across any cancer that a patient might walk in the door with, what are the systemic predictors. And so when you mentioned before that our overall cohort is approximately 9,000 patients, that's 9,000 patients split over a variety of what we call clinical scenarios or clinical indications. And that includes multiple solid tumor as well as liquid tumor malignancies. It includes both patients who are initiating systemic therapy with palliative intent for metastatic disease. It also includes several groups of patients who are getting adjuvant therapy. So we want it to be as broad as possible. Our selection of those scenarios was really done with the goal of being as broad as possible and really bringing in everything that we could within the constraints of our data source. And that was really the only limitation that we applied in concept was tumor types that are common enough to have a meaningful sample of patients to analyze. So, one, are there enough patients? And then two, are you able to identify this specific group of patients within SEER-Medicare data? Because when the NCCN divides groups of patients by biomarkers that are not available in SEER-Medicare, we can't really say, “Oh, we're going to study this group of patients.” That would then be one that we have to leave on the side and not include. But everything else where one of those things didn't apply, we tried to include it as best we could.

Dr. Davide Soldato: Thank you very much for the explanation. And among the scenarios that you included in the study, were there any striking differences in terms of access to treatment and access to quality treatment the way you define the study?

Dr. Aaron Mitchell: Yes, there were differences between these different cancer types, these different cancer indications, but they're not differences that I want to over interpret or read too much into. Certainly, every cancer indication is going to be different, but when we start getting into the individual cancer types, the sample size does get smaller. And we've not done formal tests of comparison or heterogeneity among cancer types. So I don't want to say that the differences which we certainly do see, like numerically, there are differences in the proportion of patients who are getting optimal treatment versus no treatment. I don't want to say that it's because the low income subsidy status or patient age has a bigger impact, let's say for lung cancer than breast cancer. I want to say that is heterogeneity for potential future study when we are able to do a similar follow up analysis with say a larger sample size. I don't want to over interpret those differences at the moment.

Dr. Davide Soldato: I was just wondering in case there was anything in particular that you wanted to highlight. But in the end, I think that we also have to acknowledge that the data are based on claims data, observational data. So maybe you're right when you say we should not over interpret this type of difference. 

And this is just to speculate a little bit, do you think that if you would look at this same specific question in a more contemporary diagnosis frame, like for example, you refer to the fact that most of the diagnoses were between 2016 and 2018. Now that we have more and more of these drugs that would qualify as Part B in the adjuvant or new adjuvant setting, do you think that you would see more differences compared to what you observed in the current study or do you think that it would be more or less the same? Of course this was not part of the analysis that you did, but it's just to have your opinion on the topic in general.

Dr. Aaron Mitchell: My expectation would be that since not much has changed with respect to the low income subsidy program from the time period of our study until now, my baseline expectation would be that those results would hold. On the other hand, it is the case that there have been improvements to the standard Medicare Part D benefit since the time of our study. So the low income subsidy patients would be paying the same low out of pocket costs that I mentioned before, about $10 a month give or take, for a specialty cancer drug. But what has started to happen is that for everyone else, their coverage has improved. Because in the US we're in the process of closing, or I think now we finally finished, but you know, a few years lag in claims data, we've closed what used to be called the donut hole, where there was this big coverage gap where patients had to pay a large amount out of pocket for drugs. So there might therefore be a narrowing of the difference, let's say between our low income subsidy participants, the lowest income patients, and then everyone else. But not so much because the low income subsidy status improved or changed, but just because the baseline level of coverage for everyone else may have improved, narrowing that gap. So I'd say that would be very possible. 

And if your question is more geared towards not so much policy changes, but treatment landscape changes, I would say the big thing that I would maybe guess, and again, this is very much speculation, but you introduce the speculation in TBD on follow up. I think the big change in the landscape has been the broadening indication and uptake of immunotherapy drugs, our PD-1, PD-L1 inhibitors, for a variety of cancer types. And I think the way that that would manifest in our data, were we to repeat it in a more contemporary data set, would be, I think that the access for, let's say, that any systemic therapy among older patients might change. And that is because rather than just having your cytotoxics in hand, the clinical oncologists now know that for many cases there's if not first line therapy, then second line therapy for patients who don't qualify, you can go straight to it, to someone who's not a chemo candidate, you've got a much more tolerable treatment in your back pocket. And so I think that for patients who are more old or more comorbid, we might start to see that a greater proportion of them receive some systemic therapy, it just might not be the cytotoxic agent that is still most highly recommended. It might be, say a single agent, PD-L1 inhibitor, because their oncologist wants to be able to give them something. So I wouldn't be surprised if that gap starts to narrow as well if you're measuring no systemic therapy versus any systemic therapy.

Dr. Davide Soldato: And going back to the policy part of the study that you did, do you think that the results of the study that you published in the JCO can better inform policy makers on how to make these treatments more available and be sure that the largest possible proportion of patients gets a systemic treatment and gets the optimal systemic treatment?

Dr. Aaron Mitchell: Yes, I do think that this study has some direct and indirect policy implications. I think that our finding is one to highlight the low income subsidy program and maybe help it not to fly under the radar so much anymore. I think all the work that has been done on how much it has helped patients who need oral cancer medications is great, and it shows how beneficial this program can be. We're now shining the light kind of everywhere else and saying, “Okay. That's great. Here's how well it can work when it covers an oral drug, but we've got this group of low income patients who are still at need and they're still very clearly not able to access everything else. When it's not axitinib that they need, it's a pembrolizumab, they're still very much behind the curve and they need some help.” So I think that's one thing just to call attention to this as an ongoing problem. Low income patients, it's not a solved problem yet. It's something that needs further attention. 

And then for direct policy implications that are on the table, I think we're about to see the Medicare program be able to start negotiating not just Part D drugs, but also in future years, Part B covered drugs and try to lower the price for everyone, both for insurance, both for Medicare itself. And then to the extent that that boils over to the patient's out of pocket responsibility, it'll start to reduce the patient out of pocket costs as well. So I think we can look forward to hopefully an aggressive negotiation program by Medicare to start to directly lower the prices of Part B cancer drugs that these patients are unable to afford.

Dr. Davide Soldato: Thank you very much. You did the research you published in the JCO, but you really seem very passionate about the topic of care delivery and quality of care and policy. So I just wanted to ask on a personal note, how did you come to this area of research which is frequently not one that is very cared for by oncologists? It's more frequently something that biostatisticians or public health scientists put their attention to. I just had this curiosity and I wanted to ask you if you could explain a little bit how you came to this area of research.

Dr. Aaron Mitchell: Thank you for asking. That's a great question. I'll tell my favorite story about my journey there. I entered medical school planning to be a clinical investigator or maybe even a basic science researcher, and I had some background in that. I went to medical school at NYU where the teaching hospital is Bellevue, which is a large, well known public hospital within New York City. And my eyes started to open regarding the inequities in the system. You always hear about it, you read about the problems in the US healthcare system, but then when you see it on a day to day basis and you can walk four blocks from a private, very well resourced hospital to see a patient with a similar condition four blocks down the road at a under resourced public hospital getting very different treatments and receiving very different outcomes, the injustice in the system really hits you on a visceral level. And it was really, I would say, as soon as I started my clinical rotations in medical school that I realized maybe that's where I can make the most impact with my career and just really fell into it. By the time I was done with medical school, I then knew that I wanted to do something that was in the health policy space. And then by the time I was done with residency, I was like, “Oh, someone had mentioned the words health services research” and the light went on. It's like, “Oh, that's me. That's what I want to do.”

Dr. Davide Soldato: Thank you very much. That was a nice story. And I really think that we should all work towards trying to make sure that the inequities inside of the system are eliminated as much as possible. 

So I think that this concludes our interview for today. So thank you again, Dr. Mitchell, for joining us.

Dr. Aaron Mitchell: You're very welcome and thank you so much for your interest.

Dr. Davide Soldato: We appreciate you sharing more on your JCO article titled, “Quality of Treatment Selection for Medicare Beneficiaries with Cancer.” 

If you enjoy our show, please leave us a rating and review and be sure to come back for another episode. You can find all ASCO shows at asco.org/podcasts.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. 

Guests on this podcast express their own opinion, experience and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity or therapy should not be construed as an ASCO endorsement.

In this JCO Article Insights episode, Alexandra Rojek provides a summary on "Post-Transplant Cyclophosphamide–Based Graft-Versus-Host Disease Prophylaxis Attenuates Disparity in Outcomes Between Use of Matched or Mismatched Unrelated Donors" by Schaffer et al published in the Journal of Clinical Oncology July 17th, 2024.

TRANSCRIPT

Alexandra Rojek: Hello and welcome to JCO Article Insights. I'm your host, Alexandra Rojek, and today we will be discussing an original report published in the October 1st issue of JCO titled, “Post-Transplant Cyclophosphamide–Based Graft-Versus-Host Disease Prophylaxis Attenuates Disparity in Outcomes Between Use of Matched or Mismatched Unrelated Donors,” by Shaffer et al.

The CIBMTR registry study set out to compare outcomes of patients undergoing allogeneic stem cell transplantation hematologic malignancies by HLA antigen matching status as well as by the type of GVHD prophylaxis regimen received either calcineurin inhibitor-based prophylaxis or post-transplant cyclophosphamide or PTCy. This study included patients reported to CIBMTR from January 2017 to June 2021 with AML, ALL or MDS, and required that they have undergone allotransplant with either a calcineurin inhibitor based so tacro or cyclosporine, GVHD prophylaxis, or PTCy, which included a calcineurin inhibitor or sirolimus with or without MMF and ATG. Matched unrelated donors were defined as an 8 out of 8 HLA match. And mismatched unrelated donors were defined as HLA mismatched at any single locus or 7 out of 8. The primary objective of the study aimed to compare overall survival or OS and GVHD and relapse-free survival (GRFS) within and between matched unrelated donors versus mismatched unrelated donors separated by calcineurin inhibitor versus PTCy based GVHD prophylaxis.

GRFS was defined as survival without grade 3 to 4 acute GVHD, moderate to severe chronic GVHD requiring systemic therapy or relapse. 10,025 patients were included from 153 centers, with a median follow up of over 36 months. Mismatched unrelated donor recipients were made up of 22% minority ancestry patients as compared to just 8% of patients receiving a matched unrelated donor allo transplant, showing an enrichment for patients of minority ancestry in the mismatched unrelated donor group. Just under 10% of patients were of minority ancestry in the study overall, reflective of challenges in transplant care for these patients, which may include inferior access to care, fewer available and suitably matched donors, among other factors. 54% of all patients were transplanted for AML and 29% for MDS. 45% of patients received myeloablative conditioning, 25% received regimens containing ATG, and 23% overall received PTCy with either a calcineurin inhibitor or sirolimus as well as MMF.

Among patients receiving PTCy, the authors did not find differences in overall survival by degree of HLA matching, whereas among patients receiving calcineurin inhibitor-based prophylaxis, there remained survival differences by HLA matching status. When comparing matched unrelated donor calcineurin inhibitor patients with PTCy matched unrelated donor patients, the PTCy arm had better OS, and the mismatched unrelated donor group who received PTCy had similar OS as well. For GRFS, matched unrelated donor and mismatched unrelated donor PTCy patients had no difference in GRFS, similar to the trend the authors see with overall survival. But these patients also had better GRFS than matched unrelated donor patients receiving calcineurin inhibitor-based prophylaxis. Within each prophylaxis arm, there was no difference in GRFS by HLA matching status. HLA mismatched patients receiving PTCy were less likely to experience GRFS than HLA mismatched patients receiving calcineurin inhibitor-based prophylaxis.

The authors saw similar differences in comparative trends when subgrouping patients based on conditioning intensity and additionally did not find differences in GRFS and OS by ATG exposure. When looking at patients with minority ancestry, those patients who received a match unrelated donor or mismatched unrelated donor with PTCy had comparable outcomes to non-Hispanic white patients. Additionally, among minority ancestry patients, there was a significant benefit in both GRFS and OS in the PTCy groups as compared to calcineurin inhibitor-based prophylaxis. When examining other specific toxicities included in the composite GRFS endpoint, such as GVHD rates among PTCy patients, the authors note that patients receiving a matched unrelated donor had similar rates of grade 3 to 4 acute GVHD but lower rates of moderate to severe chronic GVHD requiring systemic therapy. There appears to be signal that among PTCy patients, HLA matching reduced rates of moderate to severe chronic GVHD compared to mismatched unrelated donor patients receiving PTCy. These same trends also held when the authors looked at non relapse mortality with no significant differences within the PTCy groups by HLA matching status but reduced non relapse mortality compared to both calcineur and inhibitor-based groups.

However, notably, there was a greater risk of relapse among matched unrelated donor PTCy patients than matched unrelated donor calcineurin inhibitor patients, although this risk was comparable between mismatched unrelated donor patients by type of prophylaxis. The authors note that this has also been observed in other retrospective cohorts and may be confounded by differences in conditioning intensity between these cohorts of matched unrelated donor patients, affecting the risk of relapse. Finally, the authors also evaluate whether expansion of donor search criteria to mismatch donors from full HLA matching would increase availability of young donors from minority ancestry patients, and the study noted striking increases for all subgroups examined.

This study fits nicely with the BMT CTN 1703 trial published in the recent past, which has showed the superiority of PTCy with the calcineurin inhibitor and MMF when compared with conventional calcineurin inhibitor based immune prophylaxis for reduced intensity matched related donor and matched unrelated donor allotransplant. Of note, very few patients with one HLA antigen mismatch were enrolled on that study. However, others have shown the feasibility of PTCy in the mismatched unrelated donor setting, which has led to its adoption in practice. Although less than a quarter of patients included in this current study received PTCy overall, the findings clearly are aligned with the BMT CTN 1703 study, which is likely to change clinical practice in the longer term in this field.

As the accompanying editorial in JCO, written by Dr. Chakravarty nicely lays out, the differences between this study and the EBMT registry study, also published in this issue of JCO are subtle but worthy of note. While both studies show that mismatched unrelated donor patients had worse OS and GRFS than those receiving matched unrelated donor transplants, and then among matched unrelated donor patients the addition of PTCy improved GRFS and OS, there is discordance between the studies whether the addition of PTCy abrogates the effect of HLA mismatching on GRFS and OS. As this editorial points out, there are strikingly different rates of T cell depletion with ATG between the US and Europe, which may account for differences in comparator arms that lead to this discordance. There are several very exciting clinical trials ongoing that will aim to answer some of these outstanding questions regarding comparisons of PTCy and T cell depletion, which the field eagerly looks forward to reviewing.

In summary, this registry study of patients receiving allo transplant with matched unrelated donor or mismatched unrelated donor and calcineurin inhibitor or PTCy based GVHD prophylaxis, most notably shows that for patients who may not have a matched unrelated donor available, the addition of PTCy to a mismatched unrelated donor allo transplant allows for improved outcomes after transplant in toxicities and survival. This is most significant for patients of minority ancestries who usually have fewer matched unrelated donors available in registry searches. Improving the transplant options available to these groups of patients is of critical importance in improving equitable access to care for all of our patients. And this study, although retrospective in nature, provides an important understanding of our progress to date and suggests directions for future investigation may indeed be very feasible to continue to close these gaps in care for patients in need of an allo transplant for hematologic malignancies.

This is Alexandra Rojek. Thank you for listening to JCO Article Insights. Don't forget to give us a rating or review, and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcasts.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.

Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

Dr. Shannon Westin and her guest, Dr. Brian  Slomovitz discuss the article “Pembrolizumab or Placebo Plus Adjuvant Chemotherapy With or Without Radiotherapy For Newly Diagnosed, High-Risk Endometrial Cancer: Results in Mismatch Repair-Deficient Tumors” recently published in the JCO and presented at the 2024 International Gynecologic Cancer Society.

TRANSCRIPT

The guest’s disclosures can be found in the transcript. 

Dr. Shannon Westin: Hello, and welcome to another episode of JCO After Hours, the podcast where we get in depth on manuscripts and literature published in the Journal of Clinical Oncology. I'm your host, Shannon Westin, gynecologic oncologist and JCO Social Media Editor by trade. I am thrilled because we are going to be talking about gynecologic cancer today. So, this is my jam. And specifically, we're going to be talking about a manuscript that's a simultaneous publication in the Journal of Clinical Oncology and presented at the Annual Meeting of the International Gynecologic Cancer Society on October 16, 2024. And this is “Pembrolizumab or Placebo, Plus Adjuvant Chemotherapy, With or Without Radiotherapy for Newly Diagnosed High Risk Endometrial Cancer: Results in Mismatch Repair Deficient Tumors.” This is affectionately the KEYNOTE-B21 trial, also known as the GOG-3053 trial and the ENGOT-en11 trial.

And we are joined today by the primary author in this manuscript, Dr. Brian Slomovitz, who is the Director of Gynecologic Oncology at Mount Sinai Medical Center in Miami Beach, Florida, and the clinical trial advisor in uterine cancer for the Gynecologic Oncology Group foundation.

Welcome, Brian.

Dr. Brian Slomovitz: Hey, thanks, Shannon, so much. It's a pleasure to be here. And thanks for giving us the opportunity to discuss this trial.

Dr. Shannon Westin: Yes, it's a great trial and I'm so excited to talk about it. And I think we'll start just because this is a broad group that listens to this podcast, they're not all GYN oncologists, experts like yourself, so can you just level set a little bit and speak a bit about the incidence and mortality of endometrial cancer overall and the recent trends in this disease?

Dr. Brian Slomovitz: Yeah, sure. So, and it is nice to speak about gynecologic cancers, as we know, endometrial cancer was and still is the most common of all gynecologic cancers. The numbers are going up. Right now, there's about 65,000 to 70,000 cases each year in the US diagnosed with endometrial cancer. The numbers are going up. A lot of its obesity related, some other factors, but as the population gets less healthy, those are some of the risk factors for the disease. The thing that, however, is quite surprising is that we're seeing the deaths due to endometrial cancer going up as well, while for other diseases, we're making slow, steady steps to try to decrease the mortality we're actually seeing an increase in mortality. And the most discouraging point, Shannon, as you know is the number of deaths from endometrial cancer is going to outnumber the number of deaths from ovarian cancer if it hasn't done it already. I mean, now's the time. So, we really need to come up with better treatment strategies to everything to decrease the incidence of disease, to help with prevention, but for those poor women who are diagnosed, to come up with better treatment options so we don't have to keep this increasing trend in mortality.

Dr. Shannon Westin: Absolutely. And I think some of that is related and we don't need to get on a soapbox here, but the amount of funding that goes towards research in endometrial cancer, and of course you, you have been leading the way and really trying to get a ton of trials in this space and getting our industry partners and our government partners to really support this. So really just commending you on how much you've worked on, on this area. And to that end, we've had a huge renaissance with immunotherapy and endometrial cancer, a lot of really big trials. Why don't you give the audience a rundown of where, so far, this seems to be best utilized for people with endometrial cancer?

Dr. Brian Slomovitz: Thanks for that. And as you sort of alluded to, it's been a revolution, really, with immunotherapy. We started off at immunotherapy looking at microsatellite instability or the dMMR patients. What we found is similar to other disease sites in the second and third line setting that we saw good activity with the single agent checkpoints, pembrolizumab dostarlimab, that's based on the earlier KEYNOTE data and the GARNET trial. Really, a landmark study in the second line was Vicki Makker and her colleagues put pembrolizumab and lenvatinib combination for those patients with the cold tumors. Not the dMMRs or MSI Highs, but the proficient mismatch repair. And that study in a second line setting found that it was better than chemotherapy for an overall survival advantage. So right there, we know that it works in the second line setting in the dMMR population, and we got an indication in the PMR population saying that immunotherapy works in all women with endometrial cancer at some point, then we really had the groundbreaking trials. And Shannon, thank you. You are the leader on one of the four trials that happened, to DUO-E, AtTEnd, GY018 and RUBY trial, all very similar studies showing that the combination of immunotherapy with chemotherapy in the first line, metastatic or recurrent setting had a better outcome for patients than if given chemotherapy alone.

That actually led to amazing things. We had three of those drugs have FDA approvals, pembrolizumab for all comers, dMMR and PMMR in the first line metastatic setting with chemotherapy; Dostarlimab, PMR, dMMR in the first line or metastatic with chemotherapy. And Shannon, in your study, I think we still have to learn a lot from your study. DUO-E, chemotherapy plus minus dostarlimab. And you also added a PARP inhib, and those patients with a PARP did better. So I'm really looking forward to your data, to the subgroup analysis to figure out which of those patients, depending on the biomarker, do better with PARP therapy. And right now, you have a dMMR FDA indication. But who knows? The future is really exciting to see- to be splitters, not lumpers. And I really want to see how that data pans out. And so that's how it came into the first and second line setting and that led us really to come up with the idea for this trial to put it into the adjuvant setting.

Dr. Shannon Westin: Right. And so, I think this would be really important because we're so ingrained in this. We see this on the day to day. Can you kind of tease out a little bit what's different about those patients that would be treated in that advanced recurrent setting versus the patients that would be potentially treated in this B21 study?

Dr. Brian Slomovitz: Yeah, so the first step, we demonstrated the efficacy in patients that really the treatment options were an unmet need. In the second line setting, we didn't have good treatment options. Those are the patients with measurable disease, with symptomatic disease giving immunotherapy. And not only did we see the efficacy, which was better, but we also were able to give it with limiting the side effects as seen with chemotherapy, which is nice. And then we know that the first line therapy, traditionally for endometrial cancer with carboplatin paclitaxel, response rates about 50%, progression free survival about a year, really something that we needed to improve upon. So, adding immunotherapy to the platinum backbone therapy really demonstrated an advantage. But now what we want to do is we want to see if we could prevent, in the high-risk patients, those without disease, what can we do to help prevent the disease from recurring and help patients live longer without really the need for really lifesaving types of treatments? We want to prevent it from recurring.

Dr. Shannon Westin: Yeah, I think that's essential. We know that if we can sit on that prevention side and kind of invest all the time and effort that we need to upfront, that really does yield the longer survival. So why don't you just walk through the overall design of this trial, please?

Dr. Brian Slomovitz: Yeah. So, this was an all-comers trial, meaning in individuals that had high risk endometrial cancer, high risk for recurrence, that included, in endometrial cancer, we have aggressive histologic subtypes, serous histologies, clear cell histologies, any stage, as long as there was some myometrial invasion. We also, for the first time, included patients looking at the molecular subclassifications. So, if there was a P53 mutation and they were stage 1 with myometrial invasion, they were included. And then in all comers, any patients with stage 3 or up to 4a disease, as long as the surgery was for a curative intent, and they had no residual disease after surgery, then they were allowed to enroll into this trial.

One of the things is that this is the first time we've done an adjuvant trial this large. I think one of the reasons that helped us succeed in doing a trial like this is that we left radiation as investigator’s choice, because a lot of times going into a trial like this, people feel strongly, we know our radiation oncology colleagues, rightfully so, feel that radiation could help prevent disease from coming back. And we also have the camp that says they don't need radiation. We took that question out of this study. We let investigators decide whether or not they're going to get radiation. It was for patients to get chemotherapy, who are going to normally get chemotherapy for their high-risk disease and randomize them to chemotherapy plus placebo or chemotherapy plus pembrolizumab, a PD-1 inhibitor, in order to see if we could prevent the disease from coming back.

Dr. Shannon Westin: And the primary results of this study were just presented at ESMO and published in the Annals of Oncology. Can you give us just a quick overview of what that was, what they found?

Dr. Brian Slomovitz: Yep. So, we enrolled 1100 patients. The primary objective of the study was to look at the ITT population, progression free survival and overall survival. And the overall study was negative. Okay, so the hazard ratio in the ITT population was 1.02, not demonstrating a benefit of adding pembrolizumab in this population. I would say disappointing, but at the same point, something that we could really learn a lot from and somewhere that we know that in the whole population, we need to come up with better strategies to help prevent recurrence of disease, better adjuvant treatment strategies. But there's also information that we learned from this trial and that we're reporting on that we're actually super excited about and we feel may be game changing.

Dr. Shannon Westin: Yeah. So, let's go to that. This is the good news. Your manuscript in the JCO, thank goodness you published it here, was focused on that subset of mismatch repair deficient. So, tell us what you found.

Dr. Brian Slomovitz: So, in this study, we found that the first stratification factor was dMMR versus pMMR. Now, in the pMMR group, those patients had further stratification factors, but dMMR by itself was a stratification factor. Amongst those patients that had dMMR tumors, we found the hazard ratio to be 0.31 benefiting those patients who received pembrolizumab in the adjuvant setting. Really something that when we look at the treatment studies, the GY018s, the RUBYs, the atTEnds, the DUO-Es, in a dMMR setting, we see a similar hazard ratio of 0.3, 0.4. But to get that hazard ratio, which was statistically significant, obviously, is something that we were quite pleased with and something that we felt was worthy of reporting further. I will say it was a pre-specified endpoint. We didn't allocate alpha to it. So, at the beginning, it was a pre-specified endpoint, but at the same time even though we didn't specify alpha towards that outcome, it still, we feel is clinically meaningful and can definitely add to affect the standard of care and the management of these patients.

Dr. Shannon Westin: Yeah. I'm very intrigued to see what kind of people do with this. It makes sense, mechanistically, it makes sense if there was a population that was going to benefit, if not everybody does, this is the group that will. I mean, do you feel like there's enough data? What are you going to do? FDA approval aside, obviously, those kinds of things. But how do you feel about this? Is this something you're going to offer to your patients?

Dr. Brian Slomovitz: The first answer is yes. I think it's something that I would like to offer my patients. As you know, we need one of two things: we either need an FDA approval or for a lot of our payers required to be in the NCCN listings. I don't serve on the committee. I have no influence on NCCN. I'm excited to see how they'll respond to not only the Annals article, but obviously in today's release of the JCO article, I hope that they'll look upon it favorably. It's a drug that we’re used to giving. Pembrolizumab, we have a lot of experience with it. It's interesting. We didn't see any new safety signals, Shannon.

Dr. Shannon Westin: Yeah, I was going to ask - that’s great.

Dr. Brian Slomovitz: There was nothing, nothing additional that we found in this trial. So, I feel that it can definitely improve the outcome of those patients, in my view, with high risk for recurrence, treating pembrolizumab in this setting.

Dr. Shannon Westin: Yeah, I think it's important, of course, to look at the safety. What about quality of life? Any new findings there?

Dr. Brian Slomovitz: Yeah, we did that quality of life as part of the phase 3 trial. No difference between the two arms. No difference between the two arms. When we looked at a couple of the other analyses, we found that the benefit is the same on stage 3, 4 tumors. We saw that the benefit was there as well. So, there were less patients in the stage 1, 2 group. But I think really, for all comers, for the patient population, I would definitely consider giving pembrolizumab, again, for those patients with a deficient mismatch repair.

Dr. Shannon Westin: It's really exciting, and I think you mentioned some of the statistical limitations. Anything else that gives you pause about the study or things you wish you did better? I know we always like to armchair quarterback ourselves after we do these kinds of studies.

Dr. Brian Slomovitz: Yeah, it's interesting. When we designed the study years ago, we used the best information we had at that time to come up with the study design, and we're happy with it, and we really don't think that we could have done it much better. I should say, this was a great partnership that we had here between the GOG, ENGOT and with sponsor Merck, Toon Van Gorp was the lead PI of the global trial. When he gave me the good opportunity to present it at the IGCS and to be the lead author on this, it was really a great partnership. And when we came up with a trial years ago, it was the best trial that we thought at that time. And based on the information now, I think it's really something that we're excited about these results, even though the overall trial was negative.

Dr. Shannon Westin: Yeah, I agree with you. I think it's interesting, it's informative to think about, “Well, what would we do now or then if we knew what we knew now?” But still, you design the trial the best way you can. I think the results are super intriguing. I'm hopeful at the way they'll be reviewed. I agree I don't have any inside information about the NCCN committee, but I do hope that they'll consider the overarching data to support immunotherapy and mismatch repair deficiency and the findings of this study.

And then I guess the last question I would just ask, as you're an expert here, what are you looking forward to seeing coming next in this space? What's the stuff you're intrigued about in endometrial cancer?

Dr. Brian Slomovitz: I think, Shannon, you and I have talked about this for a while. I think we're getting really close to eliminating chemotherapy for some of the patients who suffer from this disease. So, I'm not sure if we'll do a follow up to this trial, but I think a logical type of follow up would be to see: what if we just took away chemotherapy altogether and we did pembro in the adjuvant setting, pembrolizumab versus chemotherapy? We don't have that trial in the adjuvant setting, but actually, we completed accrual of that trial in the recurrent setting and we’re anxiously awaiting those results. That's KEYNOTE-C93, where in the dMMR population we studied pembrolizumab versus carboplatin paclitaxel. How those results may translate into this setting, I'm not sure. Right now, it's exciting what we have, but yeah. And I think future is bright for this. Just to highlight, in the two arms, there's 140 patients approximately in each arm; there were 25 recurrences in those patients who received placebo. Only eight recurrences in those that received pembrolizumab. Really, when we talk about numbers, it's really remarkable and it shows you the benefit it really had on the patients.

Dr. Shannon Westin: Well, this was great. It flew by, as it always does when I'm having conversations with you. I just really want to thank you again for taking the time to share your knowledge with our listeners.

Dr. Brian Slomovitz: Thanks, Shannon.

Dr. Shannon Westin: And listeners. Thank you all for taking the time to hear about endometrial cancer. Again, this was “Pembrolizumab or Placebo, Plus Adjuvant Chemotherapy, With or Without Radiotherapy for Newly Diagnosed High Risk Endometrial Cancer Results in Mismatch Repair Deficient Tumors.”

And this was the JCO After Hours. If you loved what you heard, please check out wherever you get your podcast to see what else we have to offer. Have an awesome day.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.

Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

In this JCO Article Insights episode, Subodh Selukar interviews author Dr. Robert Maki on "Combining Response and Toxicity Data to Implement Project Optimus" by Maki, et al published in the Journal of Clinical Oncology September 11, 2024.

TRANSCRIPT

Subodh Selukar: Welcome to this episode of JCO Article Insights. This is Subodh Selukar, JCO's editorial fellow. Today, I am interviewing Dr. Robert Maki on his recent editorial, “Combining Response and Toxicity Data to Implement Project Optimus.”

At the time of this recording, our guest has disclosures that are available in the manuscript and will be linked in the transcript.

Dr. Maki, welcome to our podcast.

Dr. Robert Maki: Hi, Subodh. It's a pleasure to be able to take part.

Subodh Selukar: Yeah, thank you.

So, to start us off, would you give an overview of your article?

Dr. Robert Maki: Yes. Well, it's not my article, but it's just an editorial which is a commentary on an article by authors Cheng and Associates. It's called, “Exposure-Response-Based Multiattribute Clinical Utility Score Framework to Facilitate Optimal Dose Selection for Oncology Drugs.” That's a very technical title and so forth, and yet it's a JCO article because we think that it makes an important point that in oncological trials, we talk a lot about primary endpoints, oftentimes of overall survival or progression free survival, sometimes even just response rates, but most of the time, we don't take into account the toxicity of an agent. So, you can imagine that if a drug is relatively nontoxic, then what you see is what you get. Progression free survival could be associated with what is called some sort of so-called clinical benefit. However, if a drug is really toxic and you're just laid up on the couch all day or bed bound, or need transfusions three days a week, where is that really beneficial for the patient? But, by the same token, there's no quality of life without life itself. You have to have some sort of evidence that someone is going to be around for a longer period of time as an indication of benefit. So, these are ideas that have been played out to some degree for the better part of a quarter of a century.

There's a biostatistician at MD Anderson named Peter Thall, who's one of the first people to think about this idea of combining toxicity data and response data as some sort of a combination primary endpoint for a trial. And where this comes into play for Project Optimus, this FDA initiative to come up with not just necessarily one dose or one dose and schedule, but rather a range or multiple doses and schedules for a drug based on the toxicity that's seen, is that this new paper by Dr. Cheng and colleagues provides one mechanism for doing this, for combining not just traditional clinical outcomes data, but also toxicity data.

Subodh Selukar: So, you mentioned Project Optimus is an important component of all of this. So, can you tell a little bit about what Project Optimus is and maybe a little bit potentially about how Project Optimus has affected you so far?

Dr. Robert Maki: I'd say it's having an effect mostly in the earlier phases of drug development. I'm not certain, but I think it was an outgrowth of some of the toxicity that was seen in some of the studies that were done over the course of the last 10 to 15 years with kinase-targeted drugs. The overall goal from the FDA Project Optimus was to work with companies, with academia, groups like ASCO and regulatory authorities, as well as patients to try and come up with dosing for everyone basically based on patient characteristics that they're focusing not just on those outcomes, such as progression, pre survival, overall survival, but also looking for quality of life and adding that into the mix in terms of how you choose a dose. So that's an effort that's been going on for the last several years now. There's been some nice articles on that from FDA on that and perhaps we could provide some links to those as well for people who are interested in some of the more introductory core information about Project Optimus.

Subodh Selukar: Yeah, for sure. And so, I mean you're on the editorial board at JCO and you've written this editorial, but has Project Optimus affected your clinical research yet?

Dr. Robert Maki: It's just beginning to. So, in phase 1 and 2 clinical trials, especially in phase 1, the goal is not necessarily to look for activity, but just to come up with a recommended phase 2 dose and schedule of a drug. Well, Project Optimus says, “Okay. Well, maybe there's more than one dose and schedule that should arise.” And as I was alluding to earlier, this may have arisen out of what was seen previously where a number of the multi targeted tyrosine kinase inhibitors were developed. But when you got to the phase 3 trial, it was necessary to have dose reductions in 30%, 40%, 50%, 60%, even 70% of patients in some situations. So that to me represents a drug or a development pathway for that drug that was in essence incorrect. Yes, we talk about in traditional chemotherapy of trying to get the maximum dose we can, but is that always the best thing for the patient? And we recognize that there really is a plateau usually for systemic therapies we give, that there is a limit to dose escalation even within an individual patient to try and achieve that same benefit. At some point you're just going to add toxicity. The idea is to bring some element of toxicity into the decision making for a recommended phase 2 dose and schedule or schedules in that case.

Subodh Selukar: And so, building on that, so I think one advantage of these different approaches is that they might identify a single optimal dose, or maybe they'll recommend this range of doses that maximize some maybe clinical utility score combining these different aspects. In the current paradigm, it seems like probably response and toxicity are just these separate concepts that aren't typically linked together. But we typically do have a single recommended dose. But like you said, they might in subsequent trials have a lot of dose reductions and stuff like that.

So how do you think about the process now where this is a single recommended dose of, but there are deviations from that recommended dose in the research process. Like you said, in subsequent trials or within a trial, maybe patients are needing their own dose reductions as well. And then separately once a product is approved, what do you think about deviating from the recommended dose for your standard clinical practice?

Dr. Robert Maki: Oftentimes a work in progress. So even after phase 1, maybe having only treated 30 to 50 patients, they may be relatively homogeneous and that they have to be healthier to qualify for phase 1 trial. Once the drug is released to the whole wide world, then it becomes a different scenario, and you may have patients with poor performance status to start with. Can they still get the same benefit as the patients who got the medication in the context of a clinical trial? And it may not be the case.

And I think this is where Project Optimus and the idea of giving more than one dose or schedule may be useful and say, “Okay. Well, you can give 20% less,” and what's the trade off? Maybe the drug doesn't work as well, but it is less toxic. On average, do you really lose a whole lot as a matter of a few weeks of median progression free survival? Or does the response rate really drop off as you decrease the dose intensity of your drug? One concern about having more than one dose and schedule is could you potentially be underdosing patients by the same token? Since we usually have some amount of time, at least a few weeks, to work out what's tolerable for our patient, at least the parameters of having more than one dose and schedule to choose from can be useful.

Subodh Selukar: So then thinking about potentially maybe we would have a range of doses to recommend, what do you think are going to be challenges once that starts to be incorporated into clinical practice? What kind of complications do you think might happen explaining this to a patient?

Dr. Robert Maki: That's a really, really good question and something that we- I think, just have a difficult time with just the regular consent form. It used to be that maybe you had a couple of information sheets on a standard drug, or if it's a clinical trial, then you'll have a relatively modest consent form that's supposed to be at, whatever, 7th, 8th, 9th grade reading level. But now you start adding this form with complex text to a consent form for a clinical trial. What are people really signing up for? They get a 40-page document, and I don't think they really understand that.

So, the idea that you're trying to relate to them, pushing as hard as you can, but by the same token watching out for that toxicity, I think really does speak to those endpoints of the program, that it really can be a patient-friendly idea. Are we going to necessarily get it right every time? No. As I was mentioning previously there, if you're only treating 30 to 50 patients, you may only have partial information and you come up with some sense of dose and schedule to give. And then you move that into phase 2 and phase 3, and you may have to, you see that maybe one dose and schedule is a lot more effective as you get into a randomized portion of a phase 2 trial before you move to phase 3, for example, or you see that the toxicity is much greater with no better evidence of progression free survival. So those two scenarios could certainly rise. You can't predict them in the early phases of development of a drug, but you have to be able to react or be able to react with a solid clinical trial design that allows you to have that flexibility to make those decisions later. This is where discussion with the regulators, obviously is very important to make sure that what you're doing really still fits these guardrails, as it were, of traditional clinical trial design, or these ideas of adding in the toxicity-based information from Project Optimus.

Subodh Selukar: One of the challenges in early phase trials is, like you said, we might have 30 to 50 patients at the end of the study. I think in the editorial, you mentioned that some of these newer metrics might require more and more patients. Maybe we need 30 to 50 patients on a single dose in order to have reliable understanding of these clinical utility scores. Whereas right now a sample size at a single dose might be six patients, it might even be fewer. What are your thoughts on that aspect of it?

Dr. Robert Maki: That’s an important point, too. When you're doing, let's say, a quick and dirty, as you might say, 3+3 design, which has very large error bars in terms of the confidence intervals around a dose and schedule compared to some of the newer Bayesian-based designs, yes, you can get a phase 1 trial quote done, especially if it's a ‘me too’ sort of drug, so say, another checkpoint inhibitor, you kind of know the characteristics of those over another inhibitor of a specific kinase, you know the toxicities to expect when you block, let's say, EGF receptor. So, if you have some idea, and therefore you're able to more rapidly get to that recommended phase 2 dose from a phase 1 trial, if it ends up being a new drug, then maybe 30 to 50 patients isn't enough. And you really do need to continue that assessment of both response and toxicity as the trials move forward into phase 2 and phase 3.

So, it's kind of one of those ideas of continuous process improvement that if we are going to do this, we really do need to include it, not just in early phase trials, but especially for agents that are acting through a new mechanism of action, that we look at that holistically across the drug development spectrum. And now that trials are kind of being smashed together, phase 1 and 2, now phase 2 and 3, that really increases our need to also add in the assessment of toxicity, and maybe not just on the basis of our own evaluations or lab evaluations of toxicity, but patient reported outcomes, which is something that wasn't addressed in the Cheng article and really hasn't been well addressed in clinical trials in general, I would offer.

There are precious few trials that incorporate patient reported outcome data as a means to determine what's too toxic for a patient, for example. So how do we do that? As you know, we do have patient reported CTCAE clinical toxicity criteria that are based on patient reported outcomes. And wouldn't it be interesting, at the very least, as an academic project, but even more importantly, later on, to use those as the key means to determine whether a dose is too toxic or not in the development of the drug. That, to me, would be really, really interesting and kind of turns the idea of some of the data that we collect on its head. I guess, yes, we do need to collect things like liver function tests and so forth. It is one metric of toxicity of a drug. But patients have a lot of fatigue, we really do a poor job of documenting that as clinicians, and not to mention the elements that go into what that fatigue is. To be able to capture that through PROs would be another noble effort that I think has been underutilized and underappreciated in oncology clinical trials overall.

Subodh Selukar: And so, what do you think are barriers to doing it now?

Dr. Robert Maki: We tend to, for lack of a better term, cut and paste from what we've done before, to develop new, let's say, by patient reported outcome score or metric or worksheet for a given diagnosis. That can be hard, that takes a lot in and of itself, and perhaps has been one of the barriers that we don't have enough disease specific PROs, at least for some diagnoses. For others we do. And the fact that we do have PRO-scored CTCAE sorts of score tables, now, certainly makes it easier to validate and use these tools in clinical trials. So, I would love to see more of that, even if it ends up being secondary tertiary endpoints on phase 1, 2, and 3 trials. It's a pretty easy thing to add, even if you're doing that for the first time. Get some experience with it, and it can only help patients get through a trial or even just assessing it as part of a standard of care that will help our patients in the longer run.

Subodh Selukar: Yeah. And so, thinking about other metrics of success, you mentioned a couple in your article. These aren't necessarily patient reported outcome ones, but like RECIST and RANO. I was curious. I think the Cheng article, maybe I would think about it as a general framework for combining response and toxicity together, whereas some of these other metrics are a lot more disease specific, potentially, or agent and disease specific, maybe even. Do you think that clinical research will end up settling on these metrics that are kind of increasingly specific, or do you think that there's a possibility for general frameworks?

Dr. Robert Maki: Yeah, that's a tough question. I'm just trying to think of some of those patients reported outcomes. They've got kind of the general assessment ones, and then you do have ones that are more disease specific, just like we do have response criteria that are different for, let's say, lymphoma versus brain tumors versus colorectal cancer. We do have different ways of measuring those outcomes, and we all complain that those are imperfect measures. You can always find circumstances where that patient was responding, but it was called progression or vice versa. So even from these more objective tools like RECIST and the like, it’s a challenging field, that's for sure.

We keep going around and trying to find ways of improving those sorts of systems. But let's say, for example, you used - this is part of the reason we moved from two dimensional measurements in WHO criteria versus one dimensional RECIST - if you have two dimensions, well, you have that much more variability in the measurements of the lesion. So, it turned out that we just didn't gain anything by having those bidimensional measurements. Now, since we have the ability to measure tumors better in three dimensions, should we be using volumetric assessments? Part of it depends on the size of the tumor. If you're dealing with a tumor that's 1 cm versus 8 cm, well, then the volumetric changes, you have a lot more variability, the small ones, than the big ones. Not to mention the fact that you have shapes that are not just an ovoid mass in a lot of cancers. There's just so many pitfalls in these sorts of data. What really matters at the end of the day, one thing that's underappreciated, and again is underscored by Project Optimus, is getting back to the patient.

Subodh Selukar: Your editorial made me have this one thought, and so bear with me, it's like a multi-part question. One of the reasons that we're becoming more and more interested in these alternative approaches, these clinical utility scores and everything, is that these new agents are being proposed, where there's a hypothesis that there's more complicated relationships between dose, response and toxicity. And so, 50 years ago, researchers probably didn't hypothesize that these complicated relationships were happening. They probably thought that they were more straightforward. What do you think would have happened if we had had these conversations that we're having today if we'd had them 50 years ago, what do you think would be different? Do you think that maybe we would have different therapies that kind of ended up becoming standard today? Maybe would we interpret or run studies differently today?

Dr. Robert Maki: I like that question as well. Now, if we go back to the Charles Moertel studies back from the 1970s, the whole reason that we have tumor measurements as a criterion are really based on his work, where he got a series of clinicians together and he put these masses underneath a piece of rubber sheeting, and they tried to determine how well they could determine the difference between a mass that they could palpate. And this is when we came up with the idea that a partial response was a 50% decrease in the cross-sectional area of a mass. That came from that very crude but important work from about 50 years ago. And of course, that was also a time when there really wasn't any imaging. Maybe the best you would have would be x-ray tomography to look at a lung nodule or something like that. It was a little bit of a different era. We didn't know how our drugs worked very well. We had at least some biochemical reason to use chemotherapy, and we tried to leverage that. But it was always the idea of more is better, finally disproved later on, in let's say the era of breast cancer, looking at the AC combination or doxorubicin as part of a treatment for breast cancer, that there was a ceiling to the benefit of doxorubicin in the adjuvant setting. Even then, it was clear that we needed to think about dose and schedule. We also didn't have the variety of drugs that we have now, or the different metrics that we have, circulating tumor DNA or something along those lines. Those sorts of things just never existed then either. So, we need metrics that are appropriate for their time, and we have more tools to work with.

I suspect that we'll have more specialization in oncology along disease lines, or even molecularly characterized subsets of diagnoses as well. All the detailed classification that we now need for a lymphoma, for example, or different flavors of triple negative breast cancer, all of those things are impacting how we even put a person on a trial. Similarly, since these patients are also going to get different classes of drugs that are relatively unique to them, there are a lot of drugs now that are available that really are only approved for one diagnosis. Then you really have to drill down pretty deeply in order to be able to focus on that clinical scenario. But I think we have the means to do so. Nonetheless, the general idea of these frameworks, again, the idea of combining response and toxicity data that can apply across essentially any cancer or neoplasm that we want to study.

Subodh Selukar: Okay. So, I want to move a little bit to aspirational, like where we want to move forward now. And so I think you've talked a little bit about this so far already, but would you tell me a little bit about when you're seeing a patient, interpreting results that have been given in clinical trials, are there results, metrics, summaries of trials that you wish you could communicate to them, metrics that actually already exist but don't really get implemented? You already mentioned quality of life is something that doesn't seem to be there but are there other things that maybe quality of life might not just be collected enough yet. But are there metrics on data that we have and we just don't really report them at all?

Dr. Robert Maki: That may be the case, or maybe the data end up in a secondary and tertiary publication, so they don't really become part of the lingua franca of the oncologist. I think it really speaks to just having the experience as an oncologist that you try the FDA-approved dose for medication for somebody and you run into trouble if they're, let's say, in their 80s, whereas the study population was in their 40s and their 50s with better bone marrows or better renal function on average, and things like that. So, another untested waters are geriatric oncology. What are the maximum tolerated doses when they're 80 versus when they’re 40 or 50? It's a real challenge. Probably they had the most experience of that with things like prostate cancer, where we do treat largely an older population of men compared to other diagnoses, potentially.

I suspect we're going to see just more specialization, just like we do with the medications. We do need more specialized assessments for those adverse events and or quality of life that will be diagnosis specific. If you have GI cancer, abdominal pain is going to be a bigger issue or obstruction sorts of questions. And the symptoms that you may have from having a tumor within the abdomen versus, let's say, another diagnosis, which may tend to give you more, let's say, lung metastases. So those little subtleties can't come out. And the toxicities of the drugs that we use in those diagnoses are also going to differ as well. So those should be kept in mind as we come up with, let's say, disease specific toxicity metrics that we want to combine with those outcome data. So, I think we're going to see more and more specialization of that over time.

You have to create the tool and you've got to validate it. So, all these things will take some time. But again, people have been interested in this for a long, long time. There are any number of careers that are built around quality of life and cancer, or for example, long term survivorship in pediatric cancer patients. And all of these things can be very useful and just require our attention, both as clinical investigators as well as clinicians, when we face our patient’s day to day.

Subodh Selukar: And so just one last question before we close. Is there anything that we haven't had a chance to talk about that you like to share with our listeners?

Dr. Robert Maki: If it's anything it’s that I'm really heartened as I get older with this very large influx of new clinicians and new investigators. Oncology continues to get more interesting and more sophisticated. We need more people- we still don't have enough oncologists, even for our population here in the United States. We'll have plenty to do for a very, very long time. So, I'm excited to see a new generation of young oncologists such as yourself and the trainees that I see here, the new fellows, junior faculty who are all beginning to answer these questions, thinking about them. And as me and some of my more senior friends can help promote this kind of idea and help together to answer some of these questions. We're still trying to figure it out and there are just so many variables and clinical scenarios that we need to chase down in terms of clinical research. It is going to be an ongoing discussion and hopefully this article is just one example towards the goal again of finding the right dose for our given patient.

Subodh Selukar: Thank you so much for sharing and yeah, I'm very excited to be a part of this as well.

This has been Subodh Selukar interviewing Dr. Robert Maki on his recent editorial, “Combining Response and Toxicity Data to Implement Project Optimus.” Thank you for listening and stay tuned for the next episode of JCO Article Insights.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.

Guests on this podcast express their own opinions, experience and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity or therapy should not be construed as an ASCO endorsement.

 Dr. Robert Maki Disclosures:

Consulting or Advisory Role: Deciphera, PEEL Therapeutics, Eisai, GlaxoSmithKline, Medtronic, Boehringer Ingelheim Speakers' Bureau: MJH Life Sciences  Research Funding: Amgen, Astex Pharmaceuticals, Boehringer Ingelheim, BioAtla, C4 Therapeutics, InhibRx, Regeneron, SARC: Sarcoma Alliance for Research though Collaboration, TRACON Pharma Patents, Royalties, Other Intellectual Property, Uptodate Travel, Accommodations, Expenses Company name: Stand up to Cancer, Fondazione Enrico Pallazzo

Host Dr. Davide Soldato and Dr. Shelia Garland discuss the JCO article "Randomized Controlled Trial of Virtually Delivered Cognitive Behavioral Therapy for Insomnia to Address Perceived Cancer-Related Cognitive Impairment in Cancer Survivors."

TRANSCRIPT

The guest on this podcast episode has no disclosures to declare.

Dr. Davide Soldato: Hello and welcome to JCO After Hours, the podcast where we sit down with authors from some of the latest articles published in the Journal of Clinical Oncology. I am your host, Dr. Davide Soldato. I am a Medical Oncologist at Ospedale San Martino in Genoa, Italy. Today we are joined by JCO author Dr. Sheila Garland. She's a Professor of Psychology and Oncology at Memorial University, and she's the director at the Sleep, Health, and Wellness Lab and Senior Scientist at the Beatrice Hunter Cancer Research Institute. Dr. Garland will be discussing the article titled, “Randomized Controlled Trial of Virtually Delivered Cognitive Behavioral Therapy for Insomnia to Address Perceived Cancer-Related Cognitive Impairment in Cancer Survivors.” Thank you for speaking with us, Dr. Garland. 

Dr. Sheila Garland: Thank you so much for having me.

Dr. Davide Soldato: So, Dr. Garland, you designed a study that relied on cognitive behavioral therapy to treat insomnia, and then you assessed whether improvement in insomnia would be associated with an improvement in cancer related cognitive impairment. So I wanted to ask if you could give us a little bit of context and explain the rationale between these studies. So how common are these symptoms among cancer survivors, and why do we think that improving insomnia would also improve cognitive function? 

Dr. Sheila Garland: Yeah, thank you very much. That's a really, really good question. And so cognitive behavior therapy for insomnia has been used to successfully treat insomnia in cancer survivors for quite some time. I think JCO was one of the first publishers to really demonstrate the potency of this intervention to improve insomnia. But as we know, patients will often present not just with insomnia, but insomnia comorbid with pain, fatigue, and very commonly cognitive impairment. If we take a look at the experimental research in sleep, we know that sleep quality and quantity is associated with very important cognitive functions. And so we've had clear sleep deprivation studies where if you're not able to successfully get sufficient quality or quantity of sleep, you're going to have impairments in attention and concentration and memory. So it really makes sense that if we're able to improve sleep in cancer survivors, that we're also able to address maybe some of the other concerns that they would have related to sleep. So this is an important clinical question for the patient's quality of life, but I also think it has important system implications where if we're looking at like resources and efficiency of allocating those resources, if we have an intervention that can treat multiple problems, that means that we can more effectively address lots of symptoms and use fewer resources in doing so. So that was the thought in designing this trial.

Dr. Davide Soldato: Thank you very much. That was very, very clear. So you spoke about the intervention that you implemented in the clinical trial. So I was wondering if you could give us a little bit of context. How long was the intervention? What were the main points addressed? Because you said that, in the end, we already have some data regarding cognitive behavioral therapy for treating insomnia. So I was wondering, did you personalize in any way, the program or the intervention to fit more to the cancer survivors population? 

Dr. Sheila Garland: Yeah. So it is based on a protocol that has been well researched and has a great deal of evidence of efficacy. But we delivered this intervention over a course of seven weeks. So individuals had individual sessions with a trained therapist, and those sessions lasted about an hour and were over roughly about two months or so. Seven sessions over two months. And because they were delivered individually, there was some adaptation based on the clients’ presenting problems. So while there's sort of a standard protocol, if the client is also presented with levels of fatigue or pain or anxiety or depression, the therapist was able to integrate those concepts into the therapy as well. There was nothing for cognitive impairment. So there was no additional intervention for cognitive impairment at all. We weren't doing any memory training or anything like that. So it was strictly the sleep and other symptoms looking at the impact of improving that on not only your perception of your cognitive abilities, but also on performance on a number of neuropsychological test measures.

Dr. Davide Soldato: So thank you very much for the detail. And I think that it's very interesting what you said, that the personalization of the intervention would also allow to treat some other symptoms that are distressing for cancer survivors. Like, for example, you mentioned fatigue or anxiety or depression. And I think that this goes back to the first point that you made about the intervention. So being able to treat different symptoms all at one in one single intervention, I think that that is a very intelligent use of resources and also to promote and implement, potentially some interventions that are beneficial for survivors of cancer on different domains and potentially different symptoms. So, going to the results a little bit, what did you observe regarding specifically insomnia with the intervention that you delivered?

Dr. Sheila Garland: Yeah, so, of course, we wanted to make sure that we were effective in targeting the primary outcome of what the trial was supposed to do, which was we were supposed to treat effectively, treat insomnia, and then determine whether treating that insomnia was related to improvements in cognition. So we were expecting that the intervention itself was going to be successful at improving insomnia, and we were. So we were able to not only demonstrate a statistically, but also a clinically meaningful improvement in insomnia severity. Usually that's measured by a change of about 8.4 on a measure called the insomnia severity index. And the change that we were able to produce was over 11 points. So it was clearly over the clinically meaningful change threshold.

Dr. Davide Soldato: Going back a little bit to the design of the study, this was a randomized clinical trial. And how did you allocate the participants of the study into which arms? And can you guide us a little bit in the study design? 

Dr. Sheila Garland: Yes. A lot of thought went into the study design. We ultimately decided on having a waitlist randomized controlled trial, and this was because there is no other intervention for insomnia that has comparable efficacy. And we felt it would be unethical to not give people the standard treatment that we know works to treat insomnia. So that's where having them wait for a period of time and then receive the treatment was ultimately what we decided on. Overall, we were able to recruit 132 participants, and those were randomized into either receiving treatment immediately or receiving treatment after a two month waiting period.

Dr. Davide Soldato: So you mentioned that the intervention was actually very effective for treating insomnia. You reported an improvement in the insomnia severity index of almost 11 points. And as you mentioned, this is both clinically meaningful and it was also statistically significant. Did you see any improvement also on cognitive function, and how did you measure this outcome? Was it self reported, or did you also have some objective measure to see, for example, working memory or some other type of cognitive function?

Dr. Sheila Garland: Yeah. Also, a lot of thought went into choosing the primary outcome for this. And there's people who have argued compellingly that self reported cognitive function should be the primary target because we know, based on past research, that objective and subjective ratings of cognitive performance do not always correlate well with each other. And taking a very patient oriented approach, we wanted to make sure that we prioritized the patient's perception of their own function. We used one of the subscales of the functional assessment of cancer treatment cognition scale. So it was the Perceived Cognitive Impairment subscale that was what we used as our primary, but we also reported the two other subscales, which was the Perceived Cognitive Abilities and the Impact of Cognition on Quality of Life. We were able to not only discover that there were clinically significant improvements on all three of those subscales, but actually translated into, again, the clinically meaningful change threshold that's been established for the perceived cognitive impairment subscale is, I think it's around, like 5.9 points. So, using that cutoff, 75% of the participants in the trial reported clinically meaningful improvements in their perceived cognitive impairments, compared to just 43% of those participants in the wait list group. And we looked not only at the immediate intervention effects, but also on whether they were durable. So we had follow up assessments of both three months and six months after completing treatment, and the effects on insomnia, as well as the cognitive dimensions, they were maintained. 

Dr. Davide Soldato: Thank you very much for this last remark, because I think that one of the worries I would say that we have when implementing this type of behavioral intervention is that in the end, the change that we produce and the behavioral change that we produce might be effective in the immediate time after completing the intervention. But frequently we sort of see the loss of this benefit that we produce with the intervention at later time points. And I think that this is very important that you also looked at the benefit that was maintained over time for the three and six months after the end of the intervention. And it's true that before we add some data regarding other types of behavioral intervention, for example, for weight loss or some other symptoms and other toxicity that we frequently target with this type of intervention, I was wondering, do you think that it's something specific to cognitive behavioral therapy and the specific symptoms that you were treating, so insomnia, that in the end, produced a durable and meaningful benefit over time? 

Dr. Sheila Garland: So I do think that there's something really specific about this type of intervention. With insomnia, you're really changing the person's fear of not sleeping, and you're giving them tools to be able to both prevent the reocurrence of insomnia and also if the reocurrence should happen, they know what to do then to address it themselves. I was very curious about the impact that it might have long term. I actually wasn't sure whether it would have an effect immediately, considering that people do accumulate kind of a sleep debt after having insufficient sleep for a period of time. So I didn't know whether we would see anything immediately. I thought maybe we would need the long term follow ups to see some of the effect. But I guess maybe not surprisingly, at the end of the trial, thinking about when somebody has a good night's sleep, they're feeling the effects even the next day.

Dr. Davide Soldato: Thank you. That was very insightful. Regarding the duration of the intervention, because in the end, this was very short, because it was just seven sessions weekly, and usually also when we design or implement this kind of behavioral intervention, we frequently go for a longer period of time where the patient is subjected to this type of behavioral intervention. Frequently, we see around three, six months of intervention. And so I think it's really amazing the effect that you had on this specific symptom with such a short intervention. So I think that that is also something that speaks to the possibility of further implementing this type of intervention and this type of program for symptom control.  

And going back a little bit to what was one of the main questions of the trial that you designed and the results of the article that you published, did you observe a mediating effect of the improvement of insomnia on the cognitive function? So, you said that insomnia improved, and so improved also your primary outcome, which was the scale of the FACT-Cog questionnaire. But did you see whether this improvement in cognitive function was really related and associated to the improvement that you observed in insomnia?

Dr. Sheila Garland: Yeah. So that was a very, very important question. We needed to first demonstrate that there was a relationship between the intervention and insomnia, and then there was a relationship between insomnia and cognition. And then we did some mediation analyses subsequent to determining both of those, and we found that the change in insomnia was a full mediator of the change in cognition. So we were able to say that it's not just time or it wasn't related to something else, that improving sleep did have this direct effect on the improvement that patients reported in their cognitive impairment. 

Dr. Davide Soldato: We spoke a lot about the subjective improvement in cognitive performance. But you said that you also evaluated some specific and objective scale with, for example, I imagine some neuropsychological tests. Did you also observe some improvement for those specific tests, and did you observe the same amount of benefit or the same improvement, we could say, between the subjective and the objective weight of measuring cognitive function? 

Dr. Sheila Garland: I think that's where the outcomes become a little less clear. So, we did measure performance based cognition at all of the time points, and we were very careful in selecting these measures. So we followed the guidance provided by the International Task Force on Cognition and Cancer. They had some very specific recommendations about how and what measures we use. So we made sure to use measures that were able to be repeated, so that had multiple forms, that had very identifiable ways to indicate improvements. So we used the Hopkins Verbal Learning Test to measure word recall, both immediately and delayed. We used measures to look at verbal fluency and working memory. Overall, we had six different specific aspects of cognition that we were looking at, immediate word recall, delayed word recall, word retention, verbal fluency, word recognition, and working memory. Some of those presented with a different pattern of change overall. So a little bit trickier to interpret than the person's perception of their own cognition.

Dr. Davide Soldato: That's very interesting because it's important to have this kind of objective assessment. But in the end, what we are really trying to target is a symptom that is distressing for cancer survivors. I'm not even sure that sometimes we need all of this detail, or at least that even if these outcomes that are more objectively measured, we do not observe the same amount of benefits. Still, if we are able to produce an improvement in the symptoms and the perception that the survivor or the individual or the patient, whoever we are trying to help in that specific moment and for those specific symptoms, reports an improvement, I think that is already very important. And I totally share the patient oriented approach that you followed in the study. 

Going back a little bit to the population, because I think that this speaks a little bit also to potential avenues for further research. You included a population of cancer survivors who completed treatment at least six months before being enrolled in the trial. And relating to the population, I had two questions. So the first one is, do you think that you would have the same kind of results, so the same benefit, also among a population of patients who's in active treatment? And then the second one is a little bit more speculation, but do you think that we will arrive, or do you envision research where we kind of deliver this type of intervention in sort of a preventative way? So if we would be able to identify those patients who might later develop these types of symptoms, could we use this type of intervention sooner? So can we prevent these symptoms even before they appear? And could this be potentially associated also in a less symptoms developed over time and less need to treat these symptoms when they become more severe? 

Dr. Sheila Garland: Those are two very, very good questions. The first one is regarding the population. You're right. These people were at least six months out of treatment, and we wanted to make sure that if there was any temporary disruption, that would have maybe been stabilized over that. But most of the people in this trial, and I will mention that we didn't focus on any specific cancer type or site. So this was really a heterogeneous group of cancer survivors, both male and female. The most prevalent diagnosis that we had was breast. But some of these people who were enrolled in the trial had advanced cancer, and as long as their cancer treatment, their regimen was stable, they were eligible to participate in the trial. So I think that's a very important point. If somebody is on a very intensive round of chemotherapy, it can be tricky to implement some of the more aggressive behavioral changes that can come with some of these insomnia treatments, because their level of wellness just isn't there. So during active treatment it can be challenging, but it is definitely not impossible. We would just tweak things a little bit to accommodate their physical well being at that time. 

To your next question, though, this is where I think we really need to be going. Just like they've done in the area of, like, physical activity, trying to really strengthen people prior to treatment is the way to go. Because some of my other research looked at symptoms prospectively from the time of diagnosis over the first year, and it's roughly about half of people, at least, this was in my work with women with breast cancer, about half of women with breast cancer come into treatment with clinically significant sleep problems. So, a proportion of those people just continue to have sleep problems or even get worse after it. So there's definitely a role for that, sort of like rehabilitation, not only for maybe physical fitness to try and ward off fatigue, but also getting their sleep on track. I think people are really focused, especially in that early time, about like, “I want to eat right, I want to exercise,” but I say it as many times as I possibly can, that you're not going to make healthy food choices, and you're not going to be getting out there and working out if you're not getting sufficient sleep. So we really need to have sleep there as the foundation and what supports all of those other healthy lifestyle behaviors that people are trying to change.

Dr. Davide Soldato: So sort of comprehensive intervention for people undergoing treatment where we kind of identify symptoms that are already there at the beginning, and we deliver some sort of intervention that can target a lot of those symptoms, maybe not all of them, but maybe improving also the way that treatment is perceived or the toxicity that they might develop over treatment.

Dr. Sheila Garland: And that's what I think. I think that if you're taking people who are already coming into treatment, that are looking after their health in ways that they can, they may be able to tolerate more aggressive treatments, they might be able to complete more rounds of chemotherapy, just getting them strong, going into treatment that way. 

Dr. Davide Soldato: Also still focusing on that very patient oriented perspective that I think it's very important in general for oncologists and also for patients. I think that you were very wise in choosing an intervention that could be also delivered virtually, and this was one of the bases of the intervention. And regarding also the way the intervention was delivered, I had a question regarding the fact that this was actually an intervention that was delivered by professionals. But we also have some, maybe initial evidence, that suggests that some of this cognitive behavioral therapy can also be experienced, or at least the benefits can be obtained by the patients, even when it's self directed. So programs where patients are not actually interacting with a professional, but they are just following these types of programs. So do you think that there is room for both of those? And maybe should we suggest this type of self directed programs for all patients or all survivors and then just refer only those with a more significant or important symptom severity for the intervention with professionals? And this, I think, also goes to the discussion that we had at the very beginning about allocation of resources and ability also to tailor these types of interventions to the needs of different individuals.

Dr. Sheila Garland: I think that's really important to consider when looking at what's available for patients. They did a survey in the US of NCI Cancer Centers where they looked at the availability of CBT-I, and it was very low. I think around 20% or so of NCI Comprehensive Cancer Centers had the ability to refer to in-house CBT-I. If we had sort of a stepped care model like you're talking about, we may be able to more appropriately allocate people to the level of care that they need. A line of my research now is going into a specific app delivered cognitive behavior therapy for insomnia tailored to cancer survivors. And so looking at that very point, not everybody needs a provider, but I think that a self help manual or an app is also not going to work for everybody. So you're not going to completely take out the person. And depending on the complexity of the situation that the patient finds themselves in, they may really need that provider to consider all of the other factors. They might need it to encourage adherence or address maybe some of the barriers that would be getting in the way. So having different levels of care and being able to match people not only to the level of care, but also maybe by their preference. So, “I'd like to use an app.” Great, we've got an app for you. Or “I'd like to see somebody.” And I think matching it to people's preferences automatically encourages or enhances their engagement and their motivation to complete because they're getting what their preference would be.

Dr. Davide Soldato: And I think that at least if we could use a little bit more of these types of apps or tools or whatever we have out there, maybe we could increase at least that 20%. For example, if only 20% of NCI Cancer Centers, which are already places where care is delivered, probably with a higher attention to these types of symptoms for survivors compared, for example, to community hospitals or to smaller private clinics. So if we could at least have sort of a base and then refer only those that maybe have a higher need for a provider directed therapy or intervention, that maybe would also improve outcomes for a larger part of the population of survivors.  

And one other thing that I wanted to ask you is, do you think, in your experience, because this was not really in the trial that you designed, but do you think that we also need cultural adaptation of these types of programs? Meaning, do we need to diversify based, for example, on ethnicity or level of education or, I don't know, just the background that the patient is experiencing?

Dr. Sheila Garland: Yeah, very, very good points. There are some studies currently being conducted out of the United States that have looked at cultural adaptations of CBT-I specifically. So there was a trial looking at CBT-I for African American women survivors of breast cancer, and also the Latinx population as well. From the results of those trials, it didn't necessarily improve the effects of intervention, but it improved the engagement, so people were less likely to drop out. So it wasn't always the content. It was how the content was presented. So people were able to visually see themselves more, they were able to relate more to the content in just the way it was presented, which made them go, “Oh, okay. This is why I should be here.” And I think that that's part of the argument that I used for sort of adapting the cognitive behavior therapy for insomnia treatment that's being used in the general population, specifically to people who have had cancer, because people want to know, “All right. You know what? Is this safe for me to do? Will this work for me to do? How do I also do this when I have cancer related fatigue, or how do I do this when I also have pain?” So they want to know that, “Alright. This is right for me.” That's probably, again, relating more to getting people and keeping people engaged with the treatment, maybe even convincing them to do it to begin with, talking about getting buy-in from important leaders in their community to say, “This is something that I would recommend or I would endorse.” And those sort of community level endorsements maybe are just breaking down barriers to get people willing to engage with an evidence based treatment. 

Dr. Davide Soldato: And I think especially with cognitive behavioral therapy, because I think that when we propose drugs for treating symptoms or, I don't know, intervention for losing weight or to be more physically engaged, well, the latter that I mentioned might be also a little bit more complicated, depending on the cultural context. But drugs are very easy to accept for the patients in most cases. But I think that cognitive behavioral therapy also has some type of cultural resistance, maybe among some of our patients and cancer survivors. 

Dr. Sheila Garland: And I would also include oncologists in there as well. So, some of the treatment providers are not even exactly sure why would talking about this help. So I think separating it out, it's not just I'm going to talk about my sleep, it's that I'm going to engage with my sleep differently and breaking down maybe some of the stigma that, just because we're referring you to cognitive behavior therapy doesn't mean your problems are all in your head, but it means that there's ways that you can think about your sleep and ways that you can behave differently, which will reduce the things that are getting in the way of your sleep functioning the way that it should normally. I think when I talk to patients, and also when I do training with providers, I talk about how we can condition our bed to be associated with things other than sleep. So if we repeatedly snack in front of the tv, even though we've just had supper maybe a half an hour before, if we go and sit down in that chair that we always snack in, we're not hungry, but we find ourselves reaching for something to eat. The same thing can happen at night, where if you repeatedly pair your bed with things other than sleep, if you're thinking in bed, if you're planning, if you're worrying, if you're ruminating, if you know you're doing anything, if you're on your screen or you're watching tv or you're doing anything that's arousal producing, people can find that they're so tired, they're nodding off on the couch. They go up to bed, and all of a sudden, bang, they're wide awake and their mind is turning and they're thinking and they're like, “Why is this happening to me? I was just tired. I was so tired.” People with insomnia can relate to that very easily. That, “Oh, okay. So there's this conditioned association between my bed and wakefulness. How do I get rid of that?” That's where what we think and what we do around our sleep, we can change to be able to make our bed someplace that is strongly associated with sleep and not all of those other activities. 

Dr. Davide Soldato: Thank you for the remarks on oncologists and sometimes our resistance to accept this type of intervention. I think that this also speaks to the merit of the Journal of Clinical Oncology, which publishes high level evidence also on symptom management, and these types of interventions that are, in the end, effective for our patients. 

So I think that this concludes our interview for today. Thank you again, Dr. Garland for joining us. 

Dr. Sheila Garland: Thank you Dr. Soldato.

Dr. Davide Soldato: Dr. Garland, we appreciate you sharing more on your JCO article titled, “Randomized Controlled Trial of Virtually Delivered Cognitive Behavioral Therapy for Insomnia to Address Perceived Cancer-Related Cognitive Impairment in Cancer Survivors.”

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The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. 

Guests on this podcast express their own opinions, experience and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity or therapy should not be construed as an ASCO endorsement.

In this episode of JCO Article Insights, Dr. Giselle de Souza Carvalho interviews Dr. Hatem Azim and Dr. Ann partridge on their JCO article “Fertility Preservation and Assisted Reproduction in Patients With Breast Cancer Interrupting Adjuvant Endocrine Therapy to Attempt Pregnancy,”

TRANSCRIPT

Giselle Carvalho: Welcome to the JCO Article Insights episode for the August issue of the Journal of Clinical Oncology. This is Giselle Carvalho, your host. I'm a Medical Oncologist in Brazil focusing on breast cancer and melanoma skin cancers, and one of the ASCO editorial fellows at JCO this year. Today, I will have the opportunity to interview Dr. Hatem Azim and Dr. Ann Partridge, two of the authors of the POSITIVE trial. We will be discussing their trial on “Fertility Preservation and Assisted Reproduction in Patients With Breast Cancer Interrupting Adjuvant Endocrine Therapy to Attempt Pregnancy,” which was published in May this year. 

Hello, Dr. Azim and Dr. Partridge. Welcome to our podcast.

Dr. Ann Partridge: Hi. Thanks.

Dr. Hatem Azim: Hello.

Giselle Carvalho: So, beginning with our interview for breast cancer survivors, in addition to the treatment itself, aging is one of the major contributors to infertility. The optimal duration of adjuvant endocrine therapy in patients with hormone positive early breast cancer ranges from five to ten years, depending on patient and tumor characteristics. This time interval can be critical for women who wish to attempt pregnancy. One of the main concerns in daily breast cancer oncology practice is whether breast cancer recurrence rates are increased either by temporary interruption of endocrine therapy for pregnancy or by the use of assisted reproductive technologies.

Dr. Azim, what about assisted reproductive technology is worrisome regarding breast cancer outcomes? And how do the POSITIVE study results address the concern about worsening breast cancer outcomes either with assisted reproductive technology or endocrine therapy interruption?

Dr. Hatem Azim: So, in the primary analysis of the POSITIVE trial, we tried to address one of these questions, whether temporary interruption with endocrine therapy affects breast cancer outcome. And what we found was that interruption did not appear to have a detrimental impact at the median follow up of 41 months. So in the current manuscript, we addressed the second question, whether assisted production of fertility preservation has an impact as well on breast cancer outcome. And we did not find any worsening of outcomes in patients who underwent these procedures compared to those who had a spontaneous pregnancy. Of course, we have relatively short follow up, but at least the outcomes at the median follow up of around 3 to 4 years appears to be reassuring.

Giselle Carvalho: I see. Thank you. These are really important outcomes regarding premenopausal patients.

So, moving on, results from your study show that after 24 months, 80% of women under 35 years old had at least one successful pregnancy, while the same was true for 50% of women aged 40 to 42. These results are particularly impressive considering that over 60% of women over 35 had undergone chemotherapy. 

Dr. Partridge, other than age, what factors did you find were associated with a successful pregnancy? 

Dr. Ann Partridge: Yeah. The biggest factor, other than age, that was associated with successful live birth pregnancy was use of assisted reproductive technologies. So either having gone through IVF prior to diagnosis and banking eggs or embryos prior to diagnosis and then using them during the study, for undergoing stimulation of the ovaries during the study and then using it during the study. And that's what we also looked at in this most recent analysis of the initial POSITIVE data. 

Giselle Carvalho: I see. Thank you. The group of patients who underwent embryo oocyte cryopreservation at diagnosis were more likely to be nulliparous and treated with chemotherapy. Presumably these represent the patient group most afraid they will be infertile, as they would be receiving chemotherapy, and most desirous of pregnancy, as they had not yet had any children. Fertility preservation techniques are expensive and not easily available for all patients, particularly in less wealthy countries. Is there any group of your breast cancer patients with a high enough likelihood of pregnancy without assisted reproductive technology that you would not recommend this? 

Dr. Ann Partridge: Sure. So we are so glad to have assisted reproductive technologies available in many places, but as you know, they're not available everywhere. And even where they're available for some people, it's either inaccessible for a number of reasons or it doesn't feel right emotionally or ethically. And then finally, sometimes people need fairly quick treatment and they just don't have the time, even though we don't think there are long delays. And so we do and are able to know who can get pregnant after standard chemotherapy. Not perfectly, but we can give estimates. And the gestalt is, the younger a woman is, the less likely she is to become amenorrheic and the associated infertile, although it's not a perfect match in terms of amenorrhea being a surrogate. And then there are particular chemotherapy regimens that are more gonadotoxic than others. The more cyclophosphamide, for example, or alkylating agent, the more anthracycline, the higher the likelihood generally of causing at least amenorrhea and likely infertility. The huge caveat there is that for some of our newer therapies, we have no good information about how they might impact on menstrual status, let alone the actual rates of fertility. So we need to collect those data. But certainly, if someone's very young, they're going to get four cycles of TC or they have inflammatory breast cancer, we often take kind of a let the chips fall where they may approach, because they just aren't able to access it and we'll often do something like ovarian suppression through the chemotherapy to help support them and hope that it improves their menstrual functioning in the long run and/or fertility.

Giselle Carvalho: Thank you for your insight. So you found that pregnancy incidence over time differed by age group, although incidence of menstrual recovery over time was similar across all age groups, which I conclude that menstrual recovery does not translate into fertility. The addition of gonadotropin releasing hormone analogs to chemotherapy was not associated with time to pregnancy. However, of course, such use was not randomized. 

Dr. Azim, if assisted reproductive technology is not available to patients for reasons such as socioeconomic factors, would you recommend using GnRH analogs with chemotherapy for the purpose of fertility preservation? 

Dr. Hatem Azim: Yes. The short answer is yes. Of course, POSITIVE study was not designed to address the question around GnRH analogs, but we do have several randomized studies and meta analyses that have shown clearly that the use of GnRH analogs with chemotherapy reduce the risk of premature ovarian insufficiency. And subgroup analysis of some of these studies have shown a trend towards higher pregnancy rates as well. So, of course, if a patient does not have access to assist reproductive technology, GnRH analogs in combination with chemotherapy represent a very good alternative. 

Giselle Carvalho: I see. Thank you. Thank you for your response. At enrollment, 93.2% of women on POSITIVE trial had stage 1 or 2 disease and 66% had no negative disease. Therefore, one possible bias is that investigators might have been more comfortable with temporarily interrupting endocrine therapy if the risk of relapse was low.

Dr. Partridge, what recommendations would you have for women with stage three hormone receptor positive breast cancer who desire to attempt pregnancy?

Dr. Ann Partridge: Yeah, thank you. That's a really good question. It comes up in our tumor boards and discussions about patient care all the time, and I think, as you know, only a small proportion, about 6%, had stage 3 disease. Those patients are at higher risk of recurrence by nature of their stage. Not that all stage 3 are created equal, because, of course, if someone had a complete pathologic response to preoperative therapy and their stage 3 disease at diagnosis went to a PCR, then that person may have even better outcomes in the long run than someone who had postoperative treatment, and we don't know their likelihood even with stage 1 or 2 disease. But someone that you're concerned about their risk of recurrence, they still remain at risk of recurrence. And while we do not think, based on the POSITIVE data and all the data that we've had from retrospective studies and other data sets collected for other reasons, that a pregnancy would worsen their outcome, we certainly don't believe that a pregnancy at this point in time will dramatically improve their outcome or as a treatment for breast cancer. That's when I have a heart to heart conversation with the patient, really acknowledging they still remain at high risk. And most of my colleagues tend to want the patient to get more endocrine therapy into their system before they take a break. We've kind of discussed this, and we want someone to get more like at least three to five years. That may be a little bit paternalistic, because, as we know, taking the break for people with a little lower risk didn't seem to worsen outcomes. Maybe it's fine. I don't know that a break at five years is any better than a break at two years. I don't know. Hatem, how do you handle this in your practice?

Dr. Hatem Azim: Well, I completely agree with you, Ann. I mean, it's very much decided on a patient by patient basis. The level of uncertainty that some patients accept to take is not necessarily like others. And sometimes we as physicians, we adopt this. I agree with this paternalistic approach. Nevertheless, it's very important for the patient who is 32, is not necessarily counseled like the patient who’s 39, and her acceptance and the feasibility of waiting a bit longer as well in order to attempt pregnancy - the success of pregnancy afterwards is not necessarily the same. So I'm not sure we could adapt a one size fits all approach here. And I do not necessarily tend to factor much the elements around the stage. I think my point to patients is usually, well, you do have give and take this amount of risk of relapse, for example, and whether we accept to take such, what we could refer to as relatively unconventional approach of temporary interrupting endocrine therapy, and when we are comfortable to go ahead with this journey, depending on the feasibility of getting pregnant afterwards as well. So, yeah, I completely agree. It's very customized, based on and tailored according to the patients’ situation.

Giselle Carvalho: Thank you. I really appreciate your response to this. So, moving forward, tamoxifen alone was the most commonly prescribed endocrine therapy, followed by tamoxifen plus ovarian function suppression. The latter was preferred over aromatase inhibitors ovarian function suppression in the selected population. Endocrine therapy prescription changed in the second half of the recruitment period after July 2017 across all continents, likely due to the results of the SOFT and TEXT trials. It demonstrated absolute improvements in all disease outcomes by escalating endocrine therapy, which was more clinically meaningful in patients with high risk disease. Dr. Azim, how do you imagine this change could impact positive outcomes?

Dr. Hatem Azim: Honestly, I'm not necessarily sure that it impacts significantly the way you interpret the data and the way we counsel our patients. So, in our study, some 50% of patients received GnRH analogs and around 15% received AI. And most of the patients, I would say, were recruited in the second half of the study after we had the results from, for example, SOFT and TEXT. Furthermore, as we alluded to earlier, we had 60% of patients who received chemo. So most of our patients had a stage 1 and 2 disease in which you would argue that the absolute difference between the different hormonal therapy options is not necessarily massive. Whether or not this would impact much, I'm not sure. I think the main counseling recommendations would apply, that patients who receive endocrine therapy would be asked to interrupt it for at least three months and then they attempt pregnancy afterwards.

I don't know what you think, Anne, but I'm not sure that if we have more patients, and this is pretty much the case now, we have more patients treated with AI. I tend to do this a lot, especially if I'm thinking of interrupting, so I think I'm giving them maybe the best option first. I'm not sure this is necessarily, I mean, affecting me much, while interpreting that it does not appear that temporary interruption on the short term has an impact.

Dr. Ann Partridge: I completely agree with your strategy. Depending on the patient and their tolerance, if they have enough risk to warrant ovarian suppression with AI or tamoxifen, of course I recommend that. And yet, at the same time, I agree with you in this group that was in POSITIVE, I think the groups are relatively low enough risk. Although 40% had no positive disease, the majority got chemo, so they weren't that low risk. And so I think over time, these kinds of patients are more and more going to get ovarian suppression. I'm doing that more in my practice as tolerated. And I hope that all that means is that their breast cancer outcomes will be better independent of a pregnancy.

Giselle Carvalho: And on the topic of women with higher risk disease, CDK4/6 inhibitors are now used in the high risk adjuvant setting. How do you envision this impacting fertility?

Dr. Hatem Azim: Well, this is a very good question. Of course, this is something, this is an area of research that we have to address. Some analysis from some of the adjuvant studies, for example, the PENELOPE-B, I think they reported on some of the results of their study in which they were evaluating palbociclib in the adjuvant setting and did not appear that there was significant differences in terms of the level of estradiol levels and FSH and anti-Müllerian hormone, for example. I think these were the parameters that were evaluated in this study. So, of course, more information. Of course, palb is not the CDK4/6 inhibitor approved in the adjuvant setting. So we need more information as well about the other CDK4/6 inhibitors and longer follow-up. 

In my view from a counseling perspective, I think maybe you would have a certain level of uncertainty regarding whether or not this could have a mental impact on fertility. But the concept as well of possibly proposing a temporary interruption as we adopted in POSITIVE, would still apply. These patients would be treated as well, often, because if they are receiving CDK4/6 inhibitors in the adjuvant setting, it means that they have a high stage disease, so often they will be treated as well with GnRH analogs. I would counsel them pretty much the same, acknowledging a certain level of uncertainty regarding the data we have today on CDK4/6 inhibitors.

Dr. Ann Partridge: Yeah, if they got a full course, they would generally be further out than many people on POSITIVE, because we treat with, for example, the abemaciclib for two years and then you want to wash out and things like that. In POSITIVE, the average was two years. And so you'd expect people of higher risk to be a little further out, which I think would make everybody a little more comfortable too, because someone who's very high risk, you'd worry about very early bad recurrence, too.

Giselle Carvalho: Yeah. Thank you.

So, Dr. Partridge, regarding adherence to endocrine therapy resumption after the two year break, what was the percentage of patients who resumed treatment and which strategies would you suggest to increase adherence in this case?

Dr. Ann Partridge: That's a really great question. In the study, it was well over 70%, which is actually higher than you see in the general population of breast cancer survivors, especially young women. So in some cases, and I can tell you anecdotally, I experienced in my clinic that patients were more likely to start and take their endocrine therapy when they had the promise of the POSITIVE trial, to take a break to have a baby, because some of them don't want to start it, let alone stay on it, if they're told they have to take a full five to ten years. So it actually promoted adherence, ironically. And then for the people who got back on in the real world, the data suggests that by four years, somewhere close to half to 30% to half are no longer taking it. And so in POSITIVE it was, I think, 74% got back on, and that was only at the time point cut off when we did the initial primary data report. And of course more people will have gone back on because some people were still having babies and in the middle of things. And so I think that it's not as much of an issue with POSITIVE. In part, these are very compliant people, right? They're participating in a clinical trial to share the data with the rest of the world. They could have gotten pregnant on their own and they want to do it with their doctors. And so I think this is a little bit of a different group, but it was very reassuring to see that most people got on hormonal therapy after their interruption.

Giselle Carvalho: And recurrence of hormone receptor positive breast cancer may occur late. How long do you plan to follow patients enrolled in the POSITIVE trial?

Dr. Ann Partridge: So our plan is to follow them for at least 10 years. And it's interesting because we're starting to get close to that. We started enrollment in 2015, so I saw someone earlier this week who will have her 10 year mark next year because she got on in 2015. And that's very exciting. Obviously, it would be great to follow them even longer because ER positive breast cancer can recur many years later. But I do think that we feel as though at least 10 years will give us a good, very evidence-based feeling about the safety.

Giselle Carvalho: Thank you. Thanks for sharing. With enrollment occurring at 116 institutions in 20 countries across four continents, this representation of different races and ethnicities provides strength to support this recommendation for this group of patients worldwide.

Dr. Azim, what are your hopes for future analysis from this study and what future research in the area are you planning or would like to see performed? 

Dr. Hatem Azim: So Ann mentioned, of course, it would be crucial to conduct the long term follow up of these patients, and provide more reassuring evidence on the safety of this approach of adjuvant endocrine therapy. So this is something we're really looking forward to. Other analysis that we are working on is the breastfeeding analysis. So looking at patients who underwent breastfeeding and how far the feasibility of this approach, obviously, but how far as well this had an impact on their breast cancer outcome. So this is something that hopefully we are going to report on soon, expected end of this year. As well, we are working on evaluating, we had a large translation research program within POSITIVE, addressing several questions, including the evolution of ovarian function parameters over time and the ovarian reserve. Also, we are working on reporting on this information. We hope that this could happen maybe in the coming year.

Giselle Carvalho: Great. And finally, what advice do you give young women in your clinic who have been diagnosed with early stage hormone positive breast cancer and who are hoping to attempt pregnancy.

Dr. Hatem Azim: We address these kinds of questions relatively early in their treatments and often they are very much concerned about their chance of future fertility. Usually early on, for example, before going for chemo and so on, I just share the information that this is something that we certainly could discuss and certainly there are the possibility that we could consider in the future that it's not a ‘no go’ at least. And definitely it's something that we could work on once treatment is completed and recover from the adverse events of therapy. And because throughout the journey of treatments as well, women's wishes evolve over time and their perception of their pregnancy project as well evolve and change over time. So I think it's important to acknowledge, in my view, it's very important to acknowledge that this is feasible, this is possible, and because this as well provides an important psychological boost for them. And then as the patient comes over for their follow up after therapy and so on, start understanding, getting a little bit deeper into these kind of questions regarding feasibility, timing. If they are ER positive, then if it's okay to interrupt, not to interrupt, to explain a bit better and to consider a bit better regarding what kind of risk we're talking about. Articulating better, what do we mean by risk? So that sometimes you have a patient that is willing to accept a 10% risk, although others 1% risk for them represent a major threat. Also, it matters nulliparous versus a patient who already has two or three kids. So I think I tend to go a bit more granular in this kind of information as patients are out of chemo and on hormonal therapy and start addressing these matters. But I think it's important early on to share the information that nowadays we do have sufficient information not to discourage women who would like to have a pregnancy in the future.

Giselle Carvalho: Thank you. Thank you. Dr. Partridge, would you like to add some final comments on this?

Dr. Ann Partridge: Yeah, I think this is just such an important issue for our young breast cancer survivors and cancer survivors diagnosed at a young age, regardless of the type of cancer. So I think paying attention to this at diagnosis and through their survivorship is critical, both for their thriving in survivorship as well as for their long term health and cancer outcomes. Getting back to that adherence issue, people, if they're unhappy, won't do all the right things for themselves, sometimes medically and emotionally. And we know that infertility can be associated with long term distress for patients with and without cancer. So we need to pay attention to this and I'm really happy that ASCO is doing a podcast on this and I'm really happy that JCO is doing a podcast on this. 

Giselle Carvalho: Thank you. I really would like to thank you both, Dr. Azim and Dr. Partridge for attending this interview.

This is Giselle Carvalho. Thank you for listening to JCO Article Insights. Don't forget to give us a rating or review and be sure to subscribe so you never miss an episode. You can find all ASCO shows asco.org/podcast.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. 

Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity or therapy should not be construed as an ASCO endorsement.

 Dr. Azim Employment Company name: Pierre Fabre, EMERGENCE THERAPEUTICS Stock and Other Ownership Interests Company name: Innate Pharma, Diaacurate Travel, Accommodations, Expenses Company name: Novartis Dr. Partridge Research Funding Company name: Novartis Patents, Royalties, Other Intellectual Property Company name: UpToDate

Host Dr. Davide Soldato interviews Dr. Sana Raoof to discuss the JCO article Turning the Knobs on Screening Liquid Biopsies for High-Risk Populations: Potential for Dialing Down Invasive Procedures.

TRANSCRIPT

Dr. Davide Soldato: Hello, and welcome to JCO After Hours, the podcast where we sit down with others from some of the latest articles published in the Journal of Clinical Oncology. I am your host, Dr. Davide Soldato, Medical Oncologist at Ospedale San Martino in Genoa, Italy. Today, we are joined by JCO author Dr. Sana Raoof, Physician at Memorial Sloan Kettering, to talk about her article, “Turning the Knobs on Screening Liquid Biopsies for High-Risk Populations: Potential for Dialing Down Invasive Procedures.”  

Thank you for joining us today, Dr. Raoof.

Dr. Sana Raoof: Thank you so much. It's lovely to be here.

Dr. Davide Soldato: So, Dr. Raoof, I just wanted to start a little bit about the theme of your article, which is really centered around multi-cancer early detection tests. And this comes from the results of several studies that showed their reliability and efficacy in identifying cancer in the average risk population. But I just wanted to ask you if you could give us and our readers a brief overview of how these tests work and how they were designed for this specific population.

Dr. Sana Raoof: Of course. Well, there's an interesting story. The origin of multi-cancer early detection tests actually begins with insights that come from the field of obstetrics and gynecology. So about six or seven years ago, in the peripheral blood of pregnant women, we discovered that you can actually find fetal DNA floating around. And that was an early discovery of cell free DNA coming from the baby into the mother's bloodstream. But in some of those young, otherwise healthy women, we also discovered that there's another clonal signal, unfortunately not coming from the fetus, but coming from an undiagnosed tumor. And that led to the entire field of circulating tumor DNA and all of its applications. 

Of course, scientists in the last six or seven years have harnessed the fact that DNA and the methylation patterns on the circulating tumor DNA, as well as other analytes like glycosaminoglycans, proteins, and other analytes, are secreted by tumors into the peripheral blood in order to try and screen for tumors, hopefully at early stages, when there are still curative, definitive interventions that are available. There's several different tests now that are providing the ability to detect cancers at many stages, including early stages. They're in different phases of preclinical to clinical development, and one is even commercialized and available by prescription in the United States.

Dr. Davide Soldato: Okay. So I think that in most of these tests, they really look at the tumor DNA, so they identify mutations or, for example, methylation patterns. But do we also have some tests that integrate some other type of biomarkers that we can identify in the blood? Like, are they integrated all with the others, or are we just relying on circulating tumor DNA?

Dr. Sana Raoof: It's a great question. There's a lot of really fascinating biology that different companies predominantly are using in order to find signs of early cancer. One of the analytes that I find really interesting, other than looking for small variants in circulating tumor DNA and looking at methylation patterns, as you mentioned, is looking at fragment length. So, for example, the company DELFI looks at the different patterns of the length of DNA fragments that are floating around in the peripheral blood. And not only is fragment length tissue specific, so in theory, a fragmentomics based multi-cancer early detection test could tell us what is the tissue that this aberrant signal is coming from, but they can also tell you if there's likely a cancer present, because there's a difference in fragment length patterns in cancer versus non cancer. 

There are also other analytes. I mentioned glycosaminoglycan. There's another company that doesn't yet have prospective data, to my knowledge, that is making a test that looks at these analytes instead. There are other companies, again, without prospective data yet, that are looking at circulating tumor cells. And I'm sure that in the next few years, we're going to start getting prospective data from all of these players and also hear about other analytes that scientists have found can predict cancer from non cancer and maybe even protect tissue of origin based on artificial intelligence.

Dr. Davide Soldato: So you mentioned artificial intelligence. So, basically what you're suggesting, but correct me if I'm wrong, is that when we use this test, we are actually measuring something in the bloodstream, but at the same time, we are actually applying some type of artificial intelligence to actually interpret these results and then give us the definitive results, or what we would call like a positive and a negative of the tests, is that right?

Dr. Sana Raoof: Yeah, absolutely. And it's an important distinction that you're making, we are measuring something in the blood, but we're not just measuring it. We're using machine learning algorithms that have been trained on thousands and thousands of patients with cancer and thousands and thousands of patients without cancer, and have measured various analytes and analyzed the patterns, for example, of DNA sequence, or bisulfite sequencing of methylation patterns of patients with and without cancer, and have been trained to look for the differences between them. And so the analyte that we're looking for is not a specific mutation per se, but is a pattern that looks like patterns that you typically find more so in cancer patients.  

There's many different companies, they are trained on different types of cancer. So some companies, like GRAIL, have a test that looks for a very expanded list of over 50 cancer types. Other tests have a narrower focus and were trained and validated on a smaller list of cancer types. So there's just a great diversity in this space. These tests are trained to look for different types of cancer. They're trained and validated on different populations of interest. So, for example, some of the populations that these tests were trained on are predominantly white, and that will have impacts, potentially on how these tests perform in non-white populations. And that's a really interesting area of future research. These tests may or may not have included cancer survivors in their populations, and that could ultimately impact how these tests perform in those populations. 

So there's just so much to learn, so much data that's going to be coming out in the next few years from all of these different key players in the multi-cancer early detection space. But one thing that I'm sure of is between all of the different analytes, all of the different training and validation studies, and all of the different prospective studies, we're going to learn a tremendous amount about the potential clinical utility of using multi-cancer early detection tests to complement the few standard of care surveillance cancer screening tests that we have recommended today.

Dr. Davide Soldato: So just taking a step back and going back to the fact that we actually use machine learning algorithms to identify a pattern that can give us an idea of whether cancer is present or not, I believe that there is also some room for calibration of these types of tests. And I think that this is one of the key arguments that you make in your paper where you say that we can actually personalize a little bit more these types of tests to understand and then to decide what we are looking for. Is that correct and can you expand a little bit on that?

Dr.Sana Raoof: Yeah, absolutely. This is the central concept of the paper that we're discussing. Because these tests are machine learning based, as I said, they're trained to say cancer versus not cancer, and some of them are further trained to say, coming from this organ or coming from that organ. But what does it mean to say cancer or not cancer? There are specific thresholds that are defined to say, above this threshold of signal detection, we're going to say this is a positive cancer signal detected, and below it we're going to say negative. And so right now, these tests are kind of designed to have this binary output, and the concept that I wanted to put forth in the paper is it doesn't necessarily have to be binary, and the thresholds don't have to be static. So, for example, you can imagine that in an average risk population where the pretest probability of cancer in your lifetime for Americans, it's pretty high, roughly 40% for lifetime. But at any given moment in time when you're getting a test, it's lower. For example, in Americans, 50 to 80, the chance of having cancer at any given moment is just under 3%. So you don't necessarily want a test that is very nonspecific, you don't necessarily want to tell a lot of perfectly healthy people that are asymptomatic screening populations that they have cancer if they don't. And so these tests were designed to have very high specificity, predominantly across the board, across the different companies making them at the cost of, in some cases, having lower or moderate sensitivity in early stages.  

And it's important to keep in the back of your mind that we cannot ever expect the types of early stage sensitivities from multi-cancer early detection tests that we're used to thinking about for single cancer screens that are just optimized for one single organ. They work in a completely different way. So I don't expect a future where the sensitivity of a mammogram, which is only for breast cancer, is going to be analogous to the sensitivity of a blood-based test that's looking for all cancers in your entire body. I don't think it's fair to expect that. But I do think it's possible to imagine a future where we do change the thresholding of these tests that were trained and validated in average risk screening populations, and say, “Let's turn the knob on the dial and let's take the sensitivity a little bit higher, even if it means the specificity drops from 99%, for example, which is the very high number of the gallery test, down to 98%, down to 97%. Let's see how this affects the positive predictive value and the negative predictive value of the test.” And how having a higher negative predictive value by having a higher sensitivity may or may not make it more clinically useful for higher risk populations that have higher pretest probabilities, in which case we are kind of more interested in being sure that we're ruling out cancer. 

Another concept that I talk about in the paper, aside from just turning the knobs, is to make it a continuous variable rather than a binary report. Rather than saying signal detected or not signal detected, I can also imagine a future where we personalize the output of multi-cancer early detection tests to return a score, for example, from 1 to 100 or 1 to 10, and give physicians the ability to use that continuous variable in addition with other clinical findings, physical exam findings, other labs, symptoms, patient’s past medical history, family history, all of that together to make decisions about should we pursue further workup, should we do an invasive biopsy. This is kind of the way that we use other scoring tests in oncology, like the oncotype tests for breast cancer, decipher test in prostate cancer. And I think physicians like having continuous variables to work with and to help them make very personal decisions for patients' diagnostic workups.

Dr. Davide Soldato: To summarize a little bit, what you're arguing in the paper is that we could potentially modify a little bit these tests as they fit the type of population that we are looking for. For example, if we are looking at the average risk person in America, there we just want to be sure that we are just doing additional workout and additional follow ups and additional invasive procedure, for example, biopsy, when we have a very high probability of finding that cancer. At the same time, if we have someone who has a baseline risk which is higher, like cancer survivors, in that case, we are more interested in seeing if there is really cancer at that point, and so we can increase the sensitivity and go down on specificity, but still looking at the overall outcome that we want to have for that specific patient. 

One thing that I was wondering is, do you also see a future where we personalize a little bit more also including additional information that comes from risk factors, environmental or behavioral patterns, type of diet, or these types of risk factors that we already know from epidemiology are associated with a higher risk? So could we potentially customize this test even more, saying, this patient has a higher risk of developing colorectal cancer, so could we look more specifically to that specific cancer type and that specific risk compared to tobacco associated cancers, that for that specific patient, they are not so relevant? 

Dr. Sana Raoof: What you're saying is actually a fascinating and really compelling idea, and it reminds me of the way that noninvasive prenatal testing works. So, again, back to the world of obstetrics and gynecology, you have a woman at the end of her first trimester having fetal DNA testing to look for chromosomal abnormalities. And when you order that test, you actually do put in various features about the woman to help you understand her baseline risk for carrying a fetus that has chromosomal abnormalities, including her age, the status of her other children, and other things in order to help you calculate a pretest probability. And so after that, the non invasive prenatal test takes that into consideration and returns a probability of carrying a fetus that might have those aberrations, and it's not a binary risk. It's, as I said, a continuous variable.

So I think what you're proposing actually goes beyond what I wrote about in the article. I think it's a fabulous idea. And I think that in the near future, I can imagine that as natural language processing is exploding, and in general, large language models and the ability to extract features about a patient from the EMR are exploding, we might have a better stratification in general of patients into average risk, low risk, high risk, and really high risk, using EMR data, using real world data that could help us feed a really accurate picture of a patient's pre-test probability into this test, so that these tests could be further refined and further trained and validated on patients, taking into consideration more factors and help us improve the predictive power of the tests as they're returned in a report to the physician. So I think maybe you should even write an article about the idea just proposed. It's a great idea.

Dr. Davide Soldato: So another aspect that I was really interested in is I've looked at one of the papers that you cited, and I wanted to discuss this with you as you are an expert on the topic. In one of the articles that you cited that used this type of test, they identified some of the cancers that we also normally identified with standard screening procedures, like breast or lung or colorectal. So for those cancers, we add a certain proportion, or like, for example, for breast cancer, a higher proportion identified with conventional screening. But still we had some other cancer that eluded those types of screening and were identified using liquid biopsy tools. So do you envision a strategy where we would use the screening methods that we already add as a complement to those liquid biopsies, or do you think that someday liquid biopsy could potentially completely substitute standard screening procedures? 

Dr. Sana Raoof: I think we're too far from a day where liquid biopsies are going to replace standard of care screens. The scope scans and smears that the United States Preventive Services Task Force has recommended are gold standard screening interventions because, number one, for all of them, except for cervical cancer screening, we have randomized data with definitive endpoints that tell us that there are mortality benefits from doing those screens. We don't have that type of data yet from the world of multi-cancer early detection. And as we talked about earlier in this podcast, those tests are kind of designed with a different approach where they have higher sensitivity and much lower specificity than multi-cancer early detection tests. 

So I think that the molecular cancer screening companies have done a very careful job of creating tests that are really more optimized to be complementary tests rather than a standalone catch all test, to have higher specificity at the cost of lower sensitivity. So I don't imagine a near future, at least not in my career, where we're going to stop doing colonoscopies and mammograms and pap smears. I don't think that that's going to happen. But I do think that whereas right now 75% of cancers that Americans die from, we lack cancer screening mechanisms for them, I think that that number has the potential to really drop. If in the next few years, one of these multi-cancer early detection tests is ultimately approved and covered, then I think that a lot more cancers could be detected by screening rather than by symptoms, and we might ultimately see a big stage shift. 

Dr. Davide Soldato: Yeah, I think you're absolutely right. In the same article that I was mentioning before, there were several of those cancers which can be lethal if diagnosed at an advanced stage, that were diagnosed at an early stage, for example, ovarian cancer, bladder cancer. So I really think that we really have potentially the way to screen, or at least have a signal for cancer that currently we just diagnosed when symptoms associated with higher stage appear. 

But moving on to turning the knobs on this type of test, and so going to the higher risk population, for example, cancer survivors, which is something that you speak a lot about in the manuscript. So you also discuss a little bit the question of whether we should use multi-cancer testing versus single cancer testing. So are we looking at a specific recurrence from that specific tumor, or are we looking at a general risk of cancer in a population that has a common risk factor, like tobacco? And so I was wondering if you think, and this is probably just your perception or just your opinion, that that is another way that the physician should turn the knob. Should we evaluate the risk of those cancer survivors and say, in this specific patient right now, the risk of recurrence is higher so I should use or I should be more in favor of a test that is more centered on the risk of recurrence versus I have a general risk of several cancers that could appear, and so should I use something that is more multi-cancer? This, of course, is merely speculative because we still don't have definitive data regarding the efficacy of this test. But it is just your perspective on this type of approach in the near future or not so near future. 

Dr. Sana Raoof: Well, I think if we're speculating, then I think that the fantasy situation for any oncologist is that you have two types of liquid biopsies. One is a multi-cancer early detection liquid biopsy. And it would be great if you could select whether you want it to be optimized for highest NPV, negative predictive value, or highest PPV, positive predictive value. And then you also have a host of single cancer screening liquid biopsies that can help you specifically figure out if there's a recurrence of a single cancer type that you're suspicious about.  

So, for example, in the article, I talk about how there will be clinical gray areas, and it's not always going to be obvious which test you should reach for. But one example that I think we can all relate to in the oncology community is you have some indeterminate imaging finding, and you don't know what to do about it. So, for example, you have a woman that has a history of breast cancer, has had no evidence of disease for a few years, now, has back pain. You do a spine MRI, you see a lesion. Maybe it's an atypical hemangioma that's causing pain, maybe it's a breast cancer metastasis. You're not sure. What should you do? Should you do a biopsy of that lesion in the spine? Should you wait and see if it grows and do another MRI in two or three months? What are your options? And so in this situation, I think we can all agree that if you had a liquid biopsy that was optimized for really high sensitivity, specifically for breast cancer, and had a very high negative predictive value, and if it came back negative, then in that setting, it might help you avoid an invasive test, like a biopsy in the spine, and give you a little bit more comfort as a physician to say, “You know what? I'm going to come back in two or three months and do another spine MRI. I'm going to see how this woman is feeling, and I don't need to biopsy this right now. Maybe it really is just hemangioma.” 

Dr. Davide Soldato: And in this specific setting, let's take the same patient. So it's a female patient, she had a previous diagnosis of breast cancer. Do you think that there is a difference between tumor-informed tests, really based on the molecular aberration that the primary tumor had for these women, versus just a standard test that gives us information regarding the presence of breast cancer cells or not? And if you think that there is a difference, what would you think would be the advantage of one? And the disadvantages, for example, is a tumor informed essay more complex to obtain? Do we need more time? Is it more expensive versus a commercial test that is already available or something like this? This is my understanding as someone who's not so much in the topic, but I think that this is a point that many oncologists probably wonder about, and probably we should speak a little bit more about with someone who is an expert on the topic. 

Dr. Sana Raoof: Absolutely. And I think that you've actually hit all of the major points on the head. So comparing a tumor informed versus a tumor agnostic test is like really comparing apples and oranges. A tumor informed test where you're starting with a patient's pathology and you are looking specifically for mutations and other molecular features that you know the patient has in their tumor, is going to, of course, result in a test that is, number one, more expensive and harder to make, but also, number two, more sensitive, more specific, more predictive, and in every way probably just more powerful than a test that is, in general, optimized for a single cancer type, but is almost certainly going to be trained and validated on people with a mix of histologies, a mix of molecular features, and will not be as sensitive or specific as a test that is actually informed by that single individual's tumor. One of the things that matters a lot to me is health equity in oncology. There are just huge disparities in outcomes in patients that are advantaged and disadvantaged. And it stems from lots of different things. In no small part, it stems from later stages of diagnosis in disadvantaged patients, and then even once you have a diagnosis, delays to confirmatory workup, delays to starting treatment, disparities in the treatments offered. 

I don't imagine a world where everyone on earth is going to have access to tumor-informed liquid biopsies. I do imagine a future where tumor agnostic liquid biopsies, both for single and multi-cancer screening, should be a lot more economical than they are now, and should be more available for multiple cancer types, and should be more available to patients that aren't at just the Memorial Sloan Ketterings and the Dana-Farbers of the world. And so I do think that those types of off the shelf tests have the potential to really revolutionize the way that we work up suspicion of cancer, not just in advantaged patients, but also in patients that are diverse, in patients that are not at academic cancer centers, but at other cancer centers around the world. And I think it's a really exciting prospect.  

Thinking about the chance of recurrence in the breast cancer patient is a perfect example of when you want to test that is optimized just for breast cancer, because you see something in the spine, you know her history, and you're less worried about a new primary and a new MET from that primary. But there are other situations that are also interesting to consider. For example, patients that have had lung cancer and have a history of smoking, because they've had a history of smoking, they're actually at risk for a dozen different cancers, not just lung cancer. And when you think about what we do to follow lung cancer survivors, we're just doing CTs of their chest and of course, physical exams. But the vast majority of cancers that people with lung cancer history will get may not be present in the field of view of a CT of the chest. They may also get renal cancer, bladder cancer, they might get leukemias, they might get pancreatic cancer. So there are a lot of things that you're not going to catch in a CT of the chest. And so in that situation, you care not only about recurrences, which in thoracic oncology, it's kind of a gaussian probability distribution, where the tail is almost close to 0 after five years, but also a uniform distribution of roughly 3% per year of a second cancer, a new primary cancer that goes on for the rest of their life. And so in that clinical setting, you can imagine that having an off the shelf multi-cancer early detection test may be dialed up for higher negative predictive value, would be extremely useful.

Dr. Davide Soldato: Yeah, I totally agree, but thank you for clarifying these points, because I think that there is a little bit of confusion also in the oncology community, as this type of tests, they're also based on very complicated molecular biology, sometimes could be potentially integrated, and we could potentially integrate them in the clinic. 

And so I wanted to close up with kind of a personal question. I was wondering how you came to be so interested in this field of molecular screening or early diagnosis and prevention associated with molecular data. 

Dr. Sana Raoof: Well, it's an interesting story. I did my MD PhD at Harvard Medical School, and my PhD was in the opposite world from molecular cancer screening. I was designing drug combinations that could be used in advanced oncogene mutant lung cancers. And I thought I would become a medical oncologist and spend my life designing new systemic therapies for advanced malignancies. And what I saw every day in the lab during my PhD is drug resistance emerges and it's a process of evolution by natural selection happening on a cellular level. And although we have some really great slam dunk drugs that come to mind, for example EGFR inhibitors in certain lung cancers, immunotherapy in melanoma, on average, the median overall survival gain from all of the FDA approved drugs in the last 10 years is roughly two months.  

By the end of my PhD, I really started feeling like, is the best use of my life to continue fighting a battle against natural selection in cancer cells, or is it a better strategy, to me, it seemed like a more sensical strategy to just try and find cancers in these patients earlier, when you don't have to engage with the complex signaling mechanisms of a cancer cells biology, and instead can just provide a definitive local intervention, like surgery or radiation, which already is curing many patients with non metastatic cancers. And as I looked around the world, I just didn't see that many people investing heavily in early detection research at the time. It was the very early days of multi-cancer early detection. And so I became involved with all of the groups, the companies, the organizations that were developing these tests, and really fell in love with, number one, just the concept of the tests, the concept of multi-cancer early detection, rather than single cancer screening alone, because no one knows what cancer they're ultimately going to get. But I also really fell in love with methylation biology, fragmentomics. I fell in love with the types of clinical trials that were being designed and the new types of endpoints that we have to think about when we're designing clinical trials for a multiverse of single cancer screening. And it's just such an exciting time in that community, it's the early days. So that's how I came to this space, and it's just the perfect time to be in this space, because everything is exploding. 

Dr. Davide Soldato: Thank you very much. And thank you also for sharing the personal side of the story.

Dr. Sana Raoof: Thank you so much. I'd like to thank Razelle Kurzrock, who's an amazing medical oncologist who's worked with me on two really fun papers so far, one on real world data, and this one on turning the knobs on liquid biopsies. It's always great to bounce ideas around about multi-cancer early detection with friends and collaborators, and Razelle did an absolutely amazing job helping write this piece. 

Dr. Davide Soldato: So this brings us to the end of the episode. Thank you Dr. Raoof, for joining us and sharing more on your JCO article titled, ”Turning the Knobs on Screening Liquid Biopsies for High-Risk Populations: Potential for Dialing Down Invasive Procedures.”  

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