PALO ALTO – Race can undoubtedly be a tricky subject, with any suggestion of genetic differences among racial groups – beyond superficial characteristics like skin color – potentially invoking memories of the nineteenth-century eugenics movement and its eventual role in Nazi ideology. Now, with drug companies increasingly seeking to develop medications that target particular racial groups, the long-taboo subject of racial genetics has reemerged.
Much of the current debate centers on whether race should be a criterion for inclusion in clinical trials – and, by extension, whether drug labeling should mention race specifically. Although the issues are complicated, the solution is simple: follow the data.
In fact, clinical trials are not intended to demonstrate the effectiveness of a treatment (drug, medical device, or other intervention) in a completely random sample from the general population. Rather, researchers “enrich” the study population by using a characteristic, such as age or laboratory-test results, to select a subset of patients in whom the intervention’s effects will likely be easier to detect than they would be in an unfiltered population. In recent years, “biomarkers,” such as certain DNA sequences or the presence of a particular drug receptor, have become increasingly important indicators for determining eligibility for clinical trials.
This approach is not new. For example, scientists have known for decades that certain drugs can cause severe and precipitous anemia in people with a genetic deficiency of the enzyme G6PD. More recently, researchers have learned that certain cancer drugs are ineffective in fighting tumors containing the mutated variant of the gene KRAS.
Such discoveries have enhanced researchers’ ability to enrich study populations with patients who are likely to benefit from the drug, while sparing from any possible side effects of exposure those patients who are unlikely to benefit. Enrichment thus enables researchers to strengthen clinical trials’ “statistical power,” that is, the probability of detecting differences, if any exist, between study groups.
Given that a larger number of subjects or iterations enhances an experiment’s ability to detect all of the relevant effects, which bolsters confidence in the result, outcomes of small studies tend to imply significant uncertainty – unless the intervention’s effects are potent. Enrichment allows researchers to perform smaller, more informative trials by helping them to design studies that will show a high “relative treatment difference” between the drug and whatever it is being compared to (often a placebo, but sometimes another treatment).
In the 1980’s, a biomarker contributed to the success of the small but seminal clinical trial of human growth hormone in children who were unable to produce it naturally. Some children lose the ability to make growth hormone due to injury or tumors; others lack normal growth-hormone activity from birth, owing to a genetic mutation; and others are missing the gene that codes for the hormone altogether.
Giving the latter group exogenous growth hormone is futile, because their immune systems react to the “foreign” protein by producing antibodies. Although the hormone may stimulate growth for a short period, the antibodies soon bind and neutralize it.
By limiting the study population to children in the other two groups, for whom exogenous growth hormone stimulates normal growth, researchers achieved a 100% relative treatment difference. In other words, every subject who received the active drug responded, and none of those who received the placebo did. Given this result, US regulators approved the treatment for marketing based on a trial of only 28 patients.
Clearly, genetic markers are useful in designing clinical trials. But are more subjective factors like race or ethnicity also relevant?
For the cardiac drug BiDil (a combination of the vasodilators hydralazine and isosorbide dinitrate), the answer is yes. In 1996, inconclusive clinical trials led US regulators to reject the drug. But when more detailed analysis of the data revealed potentially elevated benefits for black patients, a new trial was performed on 1,050 self-identified “black” patients with severe heart failure for whom available treatments had proved ineffective.
The results – a 43% reduction in mortality and a 39% decrease in hospital visits among patients who received BiDil – were so striking that the study was concluded early. Although BiDil has not been a great commercial success since its approval in 2009, it remains on the market.
Some regard race-based medical treatment as necessary to reduce health disparities, while others view it as downright discriminatory. When BiDil was approved, Francis Collins, who was Director of the US National Human Genome Research Institute at the time, warned that “we should move without delay from blurry and potentially misleading surrogates for drug response, such as race, to the more specific causes.”
Of course, Collins was correct; race is a crude and incomplete mechanism for understanding genetic differences. But we must fight illness with the data we have, not the data we wish we had. Political and ethical sensitivities notwithstanding, drug testing, approval, and labeling must go wherever the evidence leads.