If you would use genetic studies to guide clinical trial representation for a drug to combat heart disease you would look at the genes associated with heart disease and see that mutations in those genes are evenly distributed in your clinical trial representation. You would not focus on the race with which people self-identify.
I asked Claude a few questions. I’ll just give snippets of the answers:
Are there scenarios where doctors recommend different doses of a medication, or other variations in a medical plan, based on a patient’s race?
Yes. “For instance, some Asian populations metabolize certain antidepressants and antipsychotics differently, requiring adjusted dosages”; “African American patients often respond differently to certain blood pressure medications. Guidelines recommend specific first-line treatments like calcium channel blockers for this population.”
In these scenarios, have people found out the relevant genes that make the difference?
Yes in some cases. “CYP2D6 gene: Affects metabolism of antidepressants, antipsychotics, and pain medications. Variations are more common in certain ethnic groups”; “HLA-B*1502 gene: Associated with severe skin reactions to carbamazepine in Asian populations, particularly those of Han Chinese descent.”
Are there cases where doctors adjust the treatment plan by race but don’t yet know which genes are relevant?
Yes. “Kidney Disease: African Americans show different progression and treatment responses compared to other racial groups, with ongoing research to identify genetic factors”; “Differences in heart disease risk and medication response across racial groups are recognized, with some genetic pathways identified but not fully mapped.”
So. If you do know what genes make the difference, then of course that’s the best type of information to work with. But, particularly for polygenic effects, it may be that you have information about the relevance of race without knowing the genes in question. In that scenario, either you use the race information or you use nothing, and the former seems the better choice (though, yes, to the extent that “self-identification” means that someone would say “I’m X” instead of “I’m half-X and half-Y”, that makes the information lower-quality).
For background, I’m coming from Germany, where our liberals protest when they ask asylum seekers for their ethnic identity to find out whether they are discriminated in their homeland for their ethnic identity, because we believe treating people different based on ethnic identity is wrong.
Obese people show different effects to all sorts of clinical interventions compared to people that are underweight. Yet, the FDA makes no attempt to have a representative sample of obese people and underweight people in their clinical trials. When Big Pharma companies recruit patients for clinical trials, they don’t try to a representative population when it comes to weight. In many cases they have a hypothesis that their drug will be more effective if the trial population is based to have less preconditions and then they recruit a clinical trial population that’s biased by design.
Clinical trials have trial populations that are sized to find clinically significant effects in the total trial population. If you have a clinical trial that sized to find an effect in the general population but only have that effect on Native Americans or on Black people, you are unlikely to find a statistical significant effect if you have Native Americans and Black people at their normal representation of the population.
The way doses for antidepressants and antipsychotics are chosen in clinical practice is often that you start with the lowest dose and change the dose for a single patient till the dose is good for the patient.
It’s also worth noting that genetic differences between different populations in Africa itself are higher than genetic differences between Whites and Asians. When people like Elizabeth Warren identify as Native Americans even when they are genetically mostly White, it’s not very safe that you have a good idea of someone genetics from their racial self-identification. There’s a reason why self-studies don’t ask whether someone is gay but asks for whether they belong to the group of men-who-have-sex-with-men.
If you wanted a new science of how to build racial categories about how to guide medical decisions, there’s research you could fund do gene sequencing and do a lot of work, nobody really wants that or at least I have seen nobody who advocates it.
The motivation for using the standard racial categories is equity. It was a policy to fight distrust of minorities in mainstream medicine. While the decision might be older then the term DEI but it still seems to be the principle of DEI.
I asked Claude a few questions. I’ll just give snippets of the answers:
Are there scenarios where doctors recommend different doses of a medication, or other variations in a medical plan, based on a patient’s race?
Yes. “For instance, some Asian populations metabolize certain antidepressants and antipsychotics differently, requiring adjusted dosages”; “African American patients often respond differently to certain blood pressure medications. Guidelines recommend specific first-line treatments like calcium channel blockers for this population.”
In these scenarios, have people found out the relevant genes that make the difference?
Yes in some cases. “CYP2D6 gene: Affects metabolism of antidepressants, antipsychotics, and pain medications. Variations are more common in certain ethnic groups”; “HLA-B*1502 gene: Associated with severe skin reactions to carbamazepine in Asian populations, particularly those of Han Chinese descent.”
Are there cases where doctors adjust the treatment plan by race but don’t yet know which genes are relevant?
Yes. “Kidney Disease: African Americans show different progression and treatment responses compared to other racial groups, with ongoing research to identify genetic factors”; “Differences in heart disease risk and medication response across racial groups are recognized, with some genetic pathways identified but not fully mapped.”
So. If you do know what genes make the difference, then of course that’s the best type of information to work with. But, particularly for polygenic effects, it may be that you have information about the relevance of race without knowing the genes in question. In that scenario, either you use the race information or you use nothing, and the former seems the better choice (though, yes, to the extent that “self-identification” means that someone would say “I’m X” instead of “I’m half-X and half-Y”, that makes the information lower-quality).
For background, I’m coming from Germany, where our liberals protest when they ask asylum seekers for their ethnic identity to find out whether they are discriminated in their homeland for their ethnic identity, because we believe treating people different based on ethnic identity is wrong.
Obese people show different effects to all sorts of clinical interventions compared to people that are underweight. Yet, the FDA makes no attempt to have a representative sample of obese people and underweight people in their clinical trials. When Big Pharma companies recruit patients for clinical trials, they don’t try to a representative population when it comes to weight. In many cases they have a hypothesis that their drug will be more effective if the trial population is based to have less preconditions and then they recruit a clinical trial population that’s biased by design.
Clinical trials have trial populations that are sized to find clinically significant effects in the total trial population. If you have a clinical trial that sized to find an effect in the general population but only have that effect on Native Americans or on Black people, you are unlikely to find a statistical significant effect if you have Native Americans and Black people at their normal representation of the population.
The way doses for antidepressants and antipsychotics are chosen in clinical practice is often that you start with the lowest dose and change the dose for a single patient till the dose is good for the patient.
It’s also worth noting that genetic differences between different populations in Africa itself are higher than genetic differences between Whites and Asians. When people like Elizabeth Warren identify as Native Americans even when they are genetically mostly White, it’s not very safe that you have a good idea of someone genetics from their racial self-identification. There’s a reason why self-studies don’t ask whether someone is gay but asks for whether they belong to the group of men-who-have-sex-with-men.
If you wanted a new science of how to build racial categories about how to guide medical decisions, there’s research you could fund do gene sequencing and do a lot of work, nobody really wants that or at least I have seen nobody who advocates it.
The motivation for using the standard racial categories is equity. It was a policy to fight distrust of minorities in mainstream medicine. While the decision might be older then the term DEI but it still seems to be the principle of DEI.