The professor of anesthesiology at Washington University in St. Louis provided insight on his presentation at AHS 2023 discussing the need to engage underserved populations.
Patients with migraine typically take either pain-relieving medications or preventive therapies to treat their symptoms and prevent future attacks. While the treatment toolbox for migraine has certainly expanded in recent years, mainly through the introduction of calcitonin gene-related peptide antagonists, some patients still experience pain from their condition. Understanding the reasons for why some individuals remain drug-resistant remains a topic of conversation in the field, with some research suggesting social determinants of health playing a factor.
At the 2023 American Headache Society (AHS) Annual Meeting, held June 15-18, in Austin, Texas, Burel Goodin, PhD, presented a plenary talk on the need to engage underserved populations in pain research. Goodin, a professor of anesthesiology at Washington University in St. Louis, has an extensive research background on the topic, with previous work that has looked at the interaction between psychosocial and biobehavioral characteristics in relation to the experience of pain through key pathways of stress-related hormones and immune function.
As part of a new iteration of NeuroVoices, Goodin sat down to discuss his presentation, and why engaging with underserved populations remains an area of critical unmet need. In addition, he provided context on the increased efforts needed in clinical trial settings to better understand which patients are best candidates for certain treatments, along with why social determinants of health go beyond race and ethnicity.
Burel Goodin, PhD: Unfortunately, there's a lot of underserved populations. The lens through which I discussed as it relates to pain-focused clinical trials—whether that's just general pain, chronic pain, or headache, migraine—the whole point is to develop new and effective treatments. The issue is that one-size-fits-all type of medicine is not where it's at anymore. A lot of the stuff that I talked about when engaging underserved populations really speaks to historically marginalized groups. A lot of that is steeped in social determinants of health, whether that's issues pertaining to medical mistrust, and some of that's perpetrated, or manifests from issues around being stigmatized and healthcare system, or even discriminated against sometimes.
I think it's a precision medicine issue. Our treatments often need to be tailored to the person who presents in front of us. The challenge is that a lot of the clinical trials, and the guidelines that come from those clinical trials, are based upon averages. This is how the average person responds, but it's a pretty good bet that the patient sitting in front of you is not necessarily the average person. If it is a person who's coming from an underserved or marginalized group, they're not going to be the average person, at least from that clinical trial standpoint, because they've been excluded from those clinical trials. The treatment that you offer them may be the best guess of what would help them, but I don't think at this point we should be too surprised when the individual doesn't have the response we'd like to see them have to that treatment.
To bring it back around fully, the talk then is how do we create more diverse studies? No one study can do it all, so to speak. But if it's important to make sure that say treatment X is relevant and useful for say, a white woman as much as it is for a black man, then your study should include white women and black men. If you start to get into other sort of diverse groups, you need to be studying the populations that are reflected in your clinical catchment. Who shows up to your clinic?
In this day and age, things related to race and gender can be hyperpolarized. That’s not to say that previous work is worthless and should be discredited, I don't believe that. My argument is that I think we could be doing better. I think we always need to strive to do better. And even with that being said, previous trials that included maybe predominantly White men or women, those may be White men or women who live within a reasonable driving distance to the major medical centers, which tend to be located in urban areas. The White men and women may not even be reflective of, say, the rural men and women who lived several hours from those urban areas because they don't come into those medical centers. Again, White is not always White, as Black is not always Black. And to think that we can totally extrapolate from one group, between groups, or even from within groups, is a bit of a fallacy. We just need to be mindful of that to become more inclusive in our research that then informs our clinical practice.
Being a bit biased, considering this is where I spend a lot of my academic thought and time, I think it's wildly important; however, the social aspect is also sort of underappreciated. In my world, the sort of rubric or the heuristic that we think about with people's experiences of pain is related to say, the biopsychosocial model. A lot of times folks will pay homage to that model, and then focus in on the biology and or the psychology, although oftentimes the biology. But the third sort of pillar there, the social aspect, doesn't necessarily get the same attention because it can be very challenging. Oftentimes, the social aspects, or what has been considered the noise, or the stuff that we want to sort of exclude out of our study. We can get a clearer picture of what's going on. Inherently, in an effort to make the picture clearer, you just made it less clear, because while what one individual considers noise, I consider to be the contextual factors that may explain why this person responded to your treatment, but this person did not.
It's a weird sort of yin and yang, because the "cleaner" your study, the more homogenous it is that you included participants that look alike and talk like and think alike, you may have proved the internal validity of your findings. But the external validity takes a hit because your data and your findings aren't necessarily going to generalize beyond your sample. Again, the population that we're interested in is human, and we're exquisitely esoteric and nuanced. It’s also why a lot of the phase 1, phase 2 proof-of-concept trials fail, because you start with an animal model, where the biology looks good, but it's very arguable to say whatever animal—even if it's a more advanced mammal like a primate—the social aspects aren't nearly what they are in humans. Those are all things that can color your findings in finding an effect or not. That's where a lot of stuff falls apart, when making that sort of transitional leap from animals to people. Because we're social beings. There's a lot of social things going on there that without thinking about it diligently, will tear down your clinical trial and leave you standing there thinking what just happened.
Transcript edited for clarity. Click here for more coverage of AHS 2023.