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We sit down with surgeon Charles Dinerstein to explore the complex role of race in medical research and practice. We dive into the historical use of race as a variable in health care, its limitations, and potential alternatives like genetic ancestry and social determinants of health. Together, we examine the evolving understanding of race, ethnicity, and their impact on diagnostic tools and treatment, questioning whether race still holds relevance in modern medicine.

Charles Dinerstein is a surgeon.

He discusses the KevinMD article, “Medicine’s struggle with genetic and social realities.”

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Transcript

Kevin Pho: Hi, and welcome to the show. Subscribe at KevinMD.com/podcast. Today we welcome Charles Dinerstein. He’s a surgeon. Today’s KevinMD article is “Medicine’s struggle with genetic and social realities.” Charles, welcome to the show.

Charles Dinerstein: Thank you very much for having me.

Kevin Pho: So thank you so much for writing. You are a surgeon. Tell us a little about your story and journey briefly.

Charles Dinerstein: Very briefly, I grew up in Los Angeles, came to the east coast for my medical training, which was in New Jersey and New York, wound up practicing for 25 plus years in New Jersey, and have at this point gone into at least clinical retirement. I spend most of my time working for a nonprofit writing on science and health, and I find that that’s one of my ways to be able to give back for a great career in medicine.

Kevin Pho: All right, so your KevinMD article is “Medicine’s struggle with genetic and social realities.” Tell us what led you to write this article, and then talk about the article itself for those who didn’t get a chance to read it.

Charles Dinerstein: OK, well, there seems to be an ongoing drumbeat over the last several years to self-flagellate ourselves for what is described as racism in medicine. And in a lot of cases we’re looking at historical figures and we’re positing intent where there may or may not be the case. But in some other cases there is some real concern.

And the concern of late has been over the race-based clinical algorithms. There’s a whole series now going on in STAT talking about it, but this particular drum has been beating for the last five or six years, and it began with a concern over creatinine clearance as a measure, and it’s gone on to some other areas.

And what’s bothered me a lot about it is that in many cases the algorithm or the predictors that they’re talking about are not necessarily race-based, because race is just one of many factors that go into the regression equations that these guys use to come up with the guidelines or with some outcome measures. So that was a little bit bothersome to me to begin with. So that’s why I’ve been following it for a long time and writing about it.

And what I tried to say I think in the article is that race is something that’s easily measured but is poorly defined. And we’ve asked race to do an awful lot of things over the last several years. We’ve asked race to stand in for biology, and the human genome studies have shown that since we’re 99.5 percent identical, race is not a stand-in for our biological behavior. That we can pretty much throw to the side.

But race has also been asked to stand in for what we may call our lived experiences, what other people will call social determinants of health. And that too, while it works in some cases, doesn’t work in others.

And I think that a lot of the problems that we have when we talk about these algorithms is in just finding the context. The two they always mention are the ones having to do with pulmonary function and with renal function. And in fact in those cases both of those calculations are based on flawed data coming from small data sets, predominantly Caucasian patients, and they’ve made assumptions and they were clearly wrong and they clearly need to be replaced. Now there’s not a question there.

On the other hand, there are other guidelines and algorithms we have where race is the stand-in for social determinants, and in that case I think that we need to think twice before we cast them aside, because in some instances they can be particularly helpful.

I think one of the examples would be in prostate cancer, where there’s been data suggesting that Black men, who have a higher incidence of prostate cancer than white men, have poorer outcomes. And what they found ultimately was that when you look on a grade for grade, level for level basis, outcomes are essentially the same, but Black men suffer from more problems with lack of access and early diagnosis. So an algorithm that would give a Black individual a greater advantage in getting access to prostate care would actually be net beneficial. And it’s those kind of instances where I think we can make a difference.

I talk a little bit about other ways of considering race. If we’re looking from a biological perspective, then we can talk about genetics, which itself is still flawed, or ancestry, which would be another way to do it.

The latest discussion is around using ZIP codes to talk about some of the determinants of health, because if you look at the U.S. Census data you can look down at a very small level and it will break out for you the demographics and the socioeconomics of that particular six block area. Of course the problem with that is going to be that as we become a less segregated, more integrated society, the value of looking at one particular neighborhood or another is going to decline.

So I kind of was left with the thoughts that put forward by John Ioannidis, and I’ll just quote it: “The call to entirely abandon race from medical research and danger scores began several decades ago, but is a simplistic solution to a complex set of concerns.” And I think that that captures it very well.

Kevin Pho: So I want to talk about the first part of using race specifically in clinical diagnostic tools, like in renal function and pulmonary tests. Now for those who aren’t familiar, who aren’t clinicians, just tell us a little bit about that context in terms of how race currently influences the outcomes of these diagnostic tools. Give us a little context.

Charles Dinerstein: The context here in particular, when they’re talking about glomerular filtration, is that they use the creatinine clearance as a way to determine the placement of individuals in line for transplantation. And the original studies, where they looked at creatinine clearance and they used body mass and they used race to do things, they made a simplification and they said that Black patients had more muscle mass and therefore had more creatinine, and that led to them developing a formula that overestimated the function of these individuals.

So as a result, when we use that information to now decide who is in line for transplant, Black patients were kind of pushed to the back of the line by a chemical test. When we eliminate race, and they found several other ways to take that into account, all of a sudden any number of individuals that had previously been lowered down on the list were moved up on the list. So that’s one of the stronger arguments to be made for why using that generic term of race for some biological test is problematic.

Kevin Pho: And then how about in the case of pulmonary tests? How is race currently factored in diagnostic pulmonary testing?

Charles Dinerstein: That’s been a little bit more of a problem. Again it’s in looking at the FEV1 of individuals. They determined that, for reasons that are unclear to me, I’m a vascular surgeon so I’ll claim ignorance in that particular area, that the Black individuals had a greater FEV1, so that their pulmonary function tests again were compromised by that. So they were not necessarily slated to get the appropriate medications or treatments because of it.

Kevin Pho: So what is the current state in terms of the movement to remove race from these diagnostic tests? Has that gained resonance among the medical community?

Charles Dinerstein: It certainly gained a lot of resonance. And the difficulty again, I think as STAT has pointed out, and anybody that works in a hospital health system will know, is that getting new guidelines in place is a heavy lift.

There’s a lot of layers to first of all get some kind of clinical consensus. It’s always tough herding the cats together to come to an agreement about that. But even then, in the face of a consensus, now that you have electronic health records and any other numbers of systems, you have a governance system where it has to be approved by all the departments, all the departments then have to turn it over to IT, and IT governance has to approve it too, then somebody has to go into the system and build it.

So they found several medical centers have been able to do it, kind of a one-off thing, but there’s not been any great move to standardize some of these changes across the nation. And again, when you start talking about other clinical algorithms that look at outcomes or other forms of risk assessment, some of the specialty organizations have been very resistant to changing them, because point of fact they work for them.

And I think, if we jump ahead for a second just to talk about some kind of clinical take-home here, guidelines and these type of clinical algorithms are meant to guide our behavior, not dictate our behavior. And that’s an important thing to remember, especially when you look at some kind of a number like an FEV1 or a creatinine clearance. That number gives it a concrete quality that it doesn’t necessarily deserve. There’s some uncertainty in there.

Kevin Pho: So tell us more about what you mean by these professional organizations who want to keep the status quo.

Charles Dinerstein: I think that in those cases race is serving as that social determinant. It’s not the best social determinant, I would never argue that that’s the case, but it’s built into their equation, looking at questions of access if nothing else, or insurance, or any of those other things that would go along what we might say along stereotypical or true racial lines. Compliance with care, coming in to see the doctor, having insurance, having well-established family to provide backup for clinical care.

So I think that there’s been resistance there because it represents more of those social determinants than any kind of a biological basis. On the other hand, there are cases where there is a true racial biologic basis for some of these things. For instance Ashkenazi Jews, which is not a race, it’s more of an ethnicity, but again that fits into that great concept of some kind of a genetic biological basis, have a higher incidence of breast cancer, have a higher incidence of BRCA mutations. So taking that into account continues to be a clinical good rather than not.

So I think that that’s kind of the places you see this resistance to changing things that seem to be beneficial for patients. And that’s why I say, at the point at which you’re the doctor talking to the patient, that’s when you bring back that understanding that the guidelines and the numbers all come with a certain measure of uncertainty, and they all come with a certain context, so you can guide the care for your patient.

Kevin Pho: Earlier on you talk about a more nuanced approach where we have to question some of the biological implications of using race in these diagnostic tests, but when it comes to social determinants of health, race still has a useful influence. Is that essentially what you’re saying, in terms of having a more nuanced approach when we look at the complexities of race and practice?

Charles Dinerstein: I think that it speaks more directly to social determinants than certainly to biologic. There are other measures of socioeconomic determinants that are even better than race, and we should really start to talk about applying them, but there has to be some kind of new regressions, new testing, to prove that the altered algorithms are changed.

And here’s something that you would consider. Even if you were to say, does the patient have insurance, which is another common question that we’re starting to see more often in terms of the data that’s being collected that will form the basis for the algorithms, any clinician will tell you that simply having insurance does not guarantee access. Anytime that we have to deal with getting pre-approvals, or the drug is not on the formulary, or that the care that’s required is not within network, any of those things are not assured by having access. So that even something as definitive as, do you have insurance or not, doesn’t really get to the heart of what we’re trying to do clinically.

Kevin Pho: So what are some of the other factors that you said may be more powerful than race when it comes to influencing social determinants of health?

Charles Dinerstein: OK, so clearly economics makes a difference. Can you afford the care, do you get access to care, do you have some type of insurance? Your educational level, to the degree that you understand what’s being offered. And then of course having a family structure that you can rely on to help out.

I mean, I was a vascular surgeon, and so as a result my basic age group started at 65 and went up from there. And there was no way to really get an informed consent unless you had both the patient and spouse in the room, because you really needed four ears listening to the conversation to make sure that everybody got that. So family structure is very important in terms of doing that.

I’ve switched to the other side, unfortunately, of the desk, and I’m now spending more time as a patient than as a physician. And I can certainly attest to the fact that having a family member that comes by in the hospital and can speak on your behalf, those kind of things make a difference. And I think that those are the kind of determinants that we need to get a little better handle on to use in looking at outcomes.

Kevin Pho: And do you see a day in the future where we can use some of the socioeconomic traits of patients and potentially extrapolate those as potential risk factors for disease sometime in the future?

Charles Dinerstein: Certainly for risk factors for outcomes. I don’t know how well it plays back to our underlying biology though. Though if you look at any of the diseases that we associate with environmental risks, we certainly can use geography as a way of looking at that.

For instance, most of the urban pollution today comes from the cars, not so much from the fuels, the exhaust they emit, but from the brakes and the rubber. So people that live closer to highways are going to have a higher incidence of these kind of environmental effects than people living in other areas. And we should be able to start to see those kind of things if we begin to look granularly.

Kevin Pho: Well, tell us what the next steps are. What do you see in the coming months when we further examine that association between race and medicine?

Charles Dinerstein: Well, I think that the lines have been drawn to some extent. I’m hoping that we will begin to see a little bit more of a nuanced conversation around which things race is able to speak to and which things it clearly no longer has a role in. I think that still spending the time to go back over our history and wring our hands over what was done in the past, other than serving as a way to make us humble before our current knowledge, serves no additional purpose.

Kevin Pho: We’re talking to Charles Dinerstein. He’s a surgeon. Today’s KevinMD article is “Medicine’s struggle with genetic and social realities.” Charles, we’ll end with some of your take-home messages that you’d like to leave with the KevinMD audience.

Charles Dinerstein: OK, well, as I said, I’m at the point in my life where I’m sitting on the other side of the desk, so I don’t offer as much political wisdom to the next generation, because I think to a large degree it’s a whole different business than it has been.

But I think that it is fair to say that the guidelines are just that, they’re guidelines. And the great strength of being a physician is having those one-to-one relationships with your patients, and making use of those moments to take the one-size-fits-all guidelines and apply them to personalize the care. That’s where personalized medicine has always been, and from my point of view will always be, in that moment, interaction between the physician and patient.

Kevin Pho: Charles, thank you so much for sharing your perspective and insight, and thanks again for coming on the show.

Charles Dinerstein: Thank you very much for having me on.