Renal Formulas, Equity Concerns Present Challenges in Oncology

In an interview with Pharmacy Times as part of the American Society of Clinical Oncology (ASCO) 2022 Annual Meeting, Jan Beumer, PharmD, PhD, DABT, discussed how renal formulas present challenges for clinicians advancing racial equity.

How are renal formulas related to equity issues?

Jan Beumer, PharmD, PhD, DABT: So, in general, these formulas are really important because they give an indication of how well the kidneys function. And so, they determine whether people get a drug at all, what the dose of certain drugs would be, and whether to continue treatment if there's toxicity. And so, it matters that you get these values right.

Now, years ago, people observed that in African Americans, serum creatinine levels were higher, and serum creatinine is one of these markers that is imputed into this formula. And so, it's something that's produced by the muscles, it's filtered by the kidneys. And if, in the formula, you have something that gives you an indication of body size—which is assumed to be muscle, right, but you know, not the case with everyone, right? Some people have more muscle than others at the same weight. But that's the input, the generation of this creatinine, and then the kidneys filter it out. And so, you can imagine more muscle, you get higher levels [of serum creatinine], lower muscle, lower levels. And if you have a poor kidney, then the filtration is not very good and your levels in the blood also go up. So anyway, creatine is part of what goes into that equation. And so, this observation that in African Americans, serum creatinine levels were higher, is an old observation. And so, at that point, people accounted for that. They put this racial factor in these equations starting in 1999, with the MDRD equation. And so, this was a factor of about 20%, and so at equal age, sex, weight, African Americans seem to have higher creatinine levels. And so, you need to accommodate for that. And so, what that meant is, at equal serum creatinine levels, African Americans actually have a higher kidney function and have better kidneys. So that was just an observation for these estimating formulas to work best.

They didn't set out to include race, but they just evaluated all these different demographics. And race just shook out as if you don't account for it, your formula is just not going to predict as well. Right. And so, it just ended up there. And so that's how this factor got in there. Now, obviously, with the recent societal movements to really rethink how we look at race and what we do with it, people, especially in the nephrology field, but really everywhere in medicine, are like, do we really need to consider race? Is race really important? Because race is a societal construct, right? It's not biology, it's skin color. Well, what does that have to do with anything else? And so, that's why people said, well, we should just not look at it. And so, the consequence of that for kidney function values is that no matter how you do it, whether you take the old formula and just ignore African American race, so you just assume everyone is white, or you re-derive these equations and you develop the equations from scratch, and you just ignore the information of race, the consequence is that African American patients, their kidney estimates, will drop. So, their estimator, their value of kidney function will look worse, their kidneys will look worse, going from the old formula to ignoring race, whichever way you slice or dice it.

And so, in the nephrology field—which has really been pushing this because these formula come from the nephrology field, they really know what they're doing—in their field, that's a good thing. Because if these African American patients’ kidney function numbers look a little worse, then that qualifies these patients earlier for diagnosis, treatments, those kinds of things, and so it would actually balance out to some extent for the medical disparities that exist in, say, kidney disease. Well, that's great for kidney function but what kind of impacts do these changes have in oncology? Because in oncology, like I said, it's used to determine drug dose. And so, there are these drugs that are either cleared by the kidneys, your kidneys get rid of them in your body, or they are also toxic to the kidney. And so, if some patients’ kidney function is not well enough, you don't want to give them the drug. And that reverses the situation. And so, if you now have an African American patient, and you use these new equations where their kidney function looks a little worse than it may really be, then they don't qualify for some of these drugs, or they'll get lower doses. And so, with potentially curative chemotherapy, that's a bad thing, you're actually reducing the number of African American patients that that would otherwise get the right therapy.

And so, equity is context dependent, I guess you could say. So in the nephrology field, that's great. But in oncology, these consequences of removing this this race equation are different. Now, it's a tricky thing, right? I mean, there's plenty of information and data to show that this may be the case with Black patients in America. But if you look at these equations, in Black patients in South America, Black patients in Africa, Black patients in Europe, this race factor doesn't really do all that well. So, Black patients in Africa, in America, are different in that creatinine level than Black patients elsewhere. And so, just that tells you that, you know, race is a bit of a, you know, I don't know what a better term is, but it's a bit of a black box, right? So, in America, this may function and may improve your prediction. But we sort of don't really understand how it works, because Black people elsewhere, this racial adjustment doesn't function the same way. And so, it's something else than skin color, clearly, right? There's something that associates with African Americans in America, right, Black people in America, something is going on with them, that associates with their skin color, but clearly, it's not the biology, there's some complexity. And so, just the fact that we don't really understand it makes you scratch your head, whether, you know, well, first of all, we should figure it out. And then, hopefully, get rid of having to use race for lack of something better, you know, something we'd actually understand.

And so, there are these markers, alternatives to creatinine. But they're not ready for primetime yet. And so, assays are not available in all the institutions, they're more expensive. These assays are not really validated across the country, so if I get my blood tested in 2 different hospitals, I'm going to get 2 different results. It's not harmonized, everyone has their own little assay going. And so, it's just not. So, on a research basis, you can say, yeah, we can get rid of race, and we can do just fine. But from an implementation point of view, it's just not ready. And so, we need to work toward that.

I guess the last thing I want to say about this is that all these estimates are still only that they're estimates. And we get these values in the clinical records, you know, with decimal values, with values behind the decimal point, but it's not that accurate. So, if you actually look at, if you get an estimated GFR value of 60, then then the range of actual GFR that's behind that estimate is huge. It's really a big, fuzzy reality behind that seemingly accurate number. And so, actually, that margin of error dwarfs the effect of race. And so, what are we really doing here?

I think, if you really want to make treatment decisions for a patient in front of you, should not treat the value, you should treat the patient, and even if their values may be just over the edge of an eligibility threshold or a dose decision, you know, physicians should look at like, what's the performance status of this patient? Is it a young patient? Do they still run marathons? And so, maybe they can tolerate this drug, and I don't need to exclude this drug from their treatment choices. And so, I think that is an important component.

But this will not help with trial eligibility. And so, this is also a big issue in the last couple of years. The [National Cancer Institute] has done a lot of work trying to increase the ability of patients to enroll to trials, to not be too limiting. But in clinical trial protocols, there's these eligibility criteria and it's a hard value. Physicians cannot say, “Oh, but this patient looks good otherwise, I'm just going to do it anyway.” No, the trial is the trial, the eligibility, that's the number, it's a hard stop, it will be an audit issue. If you do it anyway, you violate the protocol. And so, this would also, to some extent, would reduce the ability of Black patients to enroll onto clinical trials with novel therapies. It's exactly the opposite direction that we want to go in.

And so, I think what's missing, especially in America, is the ability to measure GFR. So, it's amazing, right? Where we've got the most amazing innovations in cancer therapy, but we actually don't have standard of care, the ability, not even at all the major academic institutions, the ability to just measure GFR. Brazil does it and it costs $25. One of my co-speakers in the session mentioned this. In England they do it, in all these European countries, you know, the practices differ. But most of the western world and even some countries in South America have figured this out. If there's any doubt if these estimating equations are sort of close to a decision point, they just say let's just measure it, because then we know, and North America still hasn't been able to just do that. And so, for all the talk of personalized therapy, right, measuring genetics and tumors and selecting patients for the right drug, something as elementary as just assessing someone's kidney function, which would have an impact across so many therapeutic areas, not just cancer, the ability to measure it. This country hasn't figured out. It's really a shame.