Differences in when and how patients are treated for breast cancer account for an estimated 50 percent of the racial disparities in breast cancer mortality. If not for this gap, we might drastically improve survival for people of color after a breast cancer diagnosis.
Which leads, of course, to the key question: How do we close that gap?
It’s a question that Dr. Lola Fayanju is working hard to address and resolve, including through a new study that seeks to develop tools to preemptively identify women at risk for treatment delay and non-adherence (not finishing treatment) after a breast cancer diagnosis.
Dr. Fayanju is an associate professor in the Perelman School of Medicine at the University of Pennsylvania and chief of the division of breast surgery for the University of Pennsylvania Health System. She is also the surgical director of the Rena Rowan Breast Center in the Abramson Cancer Center, director of health equity innovation at the Penn Center for Cancer Care Innovation, and a senior fellow at the Leonard Davis Institute of Health Economics at PENN. In 2019, Dr. Fayanju was recognized by the National Academy of Medicine as an Emerging Leader in Health and Medicine Scholar, and she has been a BCRF Investigator since 2023.
Below is an edited transcript of their conversation.
Dr. Lola Fayanju: When I meet patients, I’m often struck by the extent to which you need to know so much more about them than the biomarkers of their disease, the stage, what their other medical conditions are, to really be able to get them through treatments, even to get them to treatments. And I think as the COVID-19 pandemic really provided a magnifying glass for the ways in which patients can engage with or are unable to fully take advantage of the best aspects of their various social determinants of health, really impacts their ability to receive care. And we know that certain groups are disproportionately affected by unmet social need as a result of the interaction between their demography and the social determinants of health that define their lives. And yet we do a terrible job of collecting this kind of information. We spend so much time again focusing on biomarkers and stage and hypertension and diabetes that we aren’t asking about, do you have any other person you care for at home whose well-being you will prioritize over your own even as you’re going through chemotherapy?
One of the main parts of my work is how can we do a better job at centering patients at this moment where honestly, our predisposition is the center of the disease to focus on the cancer, not focus on the person who has the cancer. And so the trial that I’m conducting with the support of the Breast Cancer Research Foundation, is looking how to optimize collecting data on social and behavioral determinants of health for people with breast cancer.
We know that delayed treatment is significantly associated with worse survival with regards to breast cancer. So the structure of our trial is that as soon as someone is diagnosed with breast cancer in our health system, or is referred to our health system for scheduling if they’re diagnosed elsewhere, they are immediately connected to our study team who then make sure that they’re enrolled in our electronic patient portal. And they will be sent a survey to complete, a screen, one of three screens that we’re testing that are previously validated, but we want to see which ones are amenable to completion amongst the diverse group of patients and they’re sent that to the portal. If they don’t complete it to the portal within a specified time before their first visit, we actually then randomize them to either receiving it via a text message or receiving it via a phone call. Recognizing that a lot of our most marginalized patients also may have challenges with technology, or even an aversion towards technology that may not allow them to or encourage them to use the computer. Our hope is that it’ll give us more information on how to do this equitably across all people who present with new diagnoses. That we can then also have an opportunity to intervene upon the things that might prevent them from getting to evaluation and getting a treatment in a timely fashion.
Dr. Lola Fayanju: So, one we know that certain groups are at increased risk for delays in time to treatment and that is associated with their survival decrement. We know that there is underdosing of certain groups of people with regards to systemic therapy; that is often ascribed to they’re having higher rates of certain kind of comorbidities. That is: other diseases that may make it hard for them to receive the full doses of prescribed breast cancer treatment. And that relates in part to the fact that, for example, if you already have diabetes and a predisposition to neuropathy and then you receive a chemotherapy agent that also provides neuropathy as a side effect. Well, then you’re probably even less likely to go through with the whole treatment.
At the same time, we know that in many ways you can get ahead of intolerability with early and proactive addressing of patient symptoms. We see that in the geriatric population. We see it in the population of anyone who’s frail, that you have to just check often and address iteratively versus waiting for people to fall off the cliff and then declare that they’re not going to take anything else. So the extent to which we can partner with our patients who may have greater challenges complying or adhering to treatment because of the other medical and social and physical circumstances in their lives, means we could probably do a better job of getting patients through treatment, getting patients to treatment, and then getting them the outcomes that they deserve. Now, that being said, we also know that even amongst patients who do everything, that is the ones who you compare a patient from one group to another group and they’ve had the exact same treatments for what superficially looks like the exact same cancer, there will still often be disparities between for instance Black patients and white patients.
And that points to our need to better understand, again, not only the biological but also social milieu in which cancer happens and in which health frankly happens. And there are many people looking at the extent to which the stressors of being a person living in a marginalized circumstance, one in which you experience discrimination. One in which even if you are well-resourced, you experience people not listening to you, people not taking your symptoms or your concerns seriously, people not prioritizing the same types of health optimization for you that they would for someone else. That is we settle for lower hemoglobin A1C, the marker of diabetic treatment efficacy for people of color relative to white people. There’s evidence that people think that Black people have less pain than white people so they get less medication. All of these are ways in which, even if someone is supposed to get the same treatment, how are they going to get it if they’re suffering? And why should they trust you if you haven’t listened to anything they’ve said in the interim, running up to this point of now having a lot of sequelae from their treatment?
So we may not be able to close all the gaps because it’s still at baseline. Some different proportions or some different prevalence rates with regards to certain more aggressive subtypes of breast cancer between groups. But really much of the disparity that we see can be ascribed to the cancers we treat the best. That is our hormone receptor–positive, HER2-negative breast cancers, the ones for which patients technically should do really well. And also amongst the cancers that are very aggressive, we know that a lot of the disparity we see is due to unequal receipt of treatment. That is: people not getting the same treatments across all groups, in part because of intolerance of certain types of sequelae that might be better managed.
Dr. Lola Fayanju: I would say patients need to be prioritized as recipients of their own data. One thing that’s really important with regards to collecting data on social determinants of health is making sure patients know why you’re collecting it and that you’re asking of everyone. No one wants to feel that you’re asking them because you perceive them to be weak or poor or needing your help. If they feel like it’s something that you’re screening everyone for, it means not only are you less likely to alienate the individuals who really need your help, but have good reason not to trust the healthcare system. But you may also engage people who don’t realize they need help and that you might not realize they need help. But because of a, again, equitably distributed screening process, you actually are able to tap into their needs and help them as well.
Freeing the data is something I think a lot of us in research are really committed to. The idea that data should go back to analysis and results of analysis, and research should go back to the individuals who contribute to it. I am very proud of and grateful for the relationships I’ve developed with patient advocates who have been critical to the development of our trial. And who we feel are central to understanding, for instance, the instruments that we implemented into this trial, was the translation of these instruments into text messaging and phone formats, did it make sense? Did it work for them? Do they think it was too onerous? Do they think it would be too hard for patients to go through it? With regards to clinicians, obviously there’s a hope that their finding out this information will allow them to practice better.
But I think what’s exciting about research, especially research that looks at improving receipt of guideline concordant care, which has really been central to a lot of my funded research, is how to optimize receipt of Guideline-Concordant Care, is that if we can predict who’s at risk for not getting it. And we’re not always right about who’s not going to get it, but if we can predict we can use that information to identify groups of people at risk for not getting it. But also identify institutions that are good at delivering Guideline-Concordant Care and institutions that are less good, that could stand to do better. And we can then learn something about this process versus thinking of disparities as something where often there is this, woe is me, what can we do? Helpless approach where you can’t change where someone lives, you can’t change their racial background, you can’t change their income easily.
But actually, we can look at institutions that work maybe in areas that have more underserved patients and yet people get more Guideline-Concordant Care. As opposed to places where there’s a lot of large S, but certain groups still fall behind what’s happening there. So, I think that when you think about prioritizing prediction of Guideline-Concordant Care receipt and optimizing how people can get it, you can then use that information not only for improving individual care, looking at populations, looking at institutional improvement. And it can even be a way to guide value-based payment in terms of thinking about how to encourage or incentivize institutions to do a better job at lifting all those.
Dr. Lola Fayanju: Well, I’m excited to say that we officially launched in March. We’ve already approached almost 100 women about this and we’ve already had, I think nearly 50 in just two months complete the instruments. The question is what can we learn from this fairly idealized state where we have personnel and resources dedicated to doing this, to translate this into everyday life. The goal is that once we have a year’s worth of data, we’re going to be doing qualitative inquiry where we talk not only to the people who participated but those who chose not to.
And then finally, we can figure out how best to respond to these in personalized ways because I think that right now, unfortunately, many of the social services that help patients who have the most difficulty receiving care are not reimbursed. Patient navigation is just being explored for that as of the end of 2023. And the CMS has also released what are called Z codes, which are basically diagnosis codes that we can use in order to begin to document the ways in which assessing for and managing unmet social need and other kind of issues related to patients, obtaining care, can be documented in the medical record.
But the truth of the matter is there isn’t yet much accountability for what we do with that. So my hope is that, again, we can learn a lot from what we get right as well from what we get wrong. And the information we get, at least provide some durable impact on the care trajectory of the patients who participated. And that this is something that can ultimately be scaled up and translated into other arenas beyond breast cancer and even beyond oncology, which I think would be a real boom to our health system nationally.
Dr. Lola Fayanju: One of the best things about being a BCRF investigator is obviously the community of individuals who are also BCRF investigators. And I think also that the generosity of BCRF gives you the courage to ask questions that might be a little bit hard to secure even federal funding or other kind additional sources of funding for. It allows us to be a little bit creative, a little bit daring, but also to address things that while they may not be the shiniest question, asking people what their lives are like may not sound like a classic kind of research question. BCRF allows us, again, to center the patient in terms of thinking about how to get to the heart of actually delivering care through research and doing it in an evidence-based way, not just kind of following our gut. So I’m very grateful to the BCRF community.
I’m grateful to the people I’ve met to the BCRF community who have given me ideas, who connected me with other people. As we think about this trial, as we think about what we’re getting right, getting wrong, I think our collective wisdom is enhanced as the investigators by the context I’ve had through BCRF, in addition to the financial support they’re providing for our team.
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