Clinical studies that involve people typically report summary information about who their participants are in tables. However, as a group of Stanford researchers show in a recent American Journal of Epidemiology article, this ubiquitous reporting style has a major flaw: tables don’t unambiguously describe the people who were actually included in a study.

The authors demonstrate this point by showing that tables that appear to have equal enrollment across age, race, and sex categories could represent entirely different study samples. This ambiguity can have significant implications, including regulatory approval of new medicines as well as treatment decisions by physicians.

“Clinicians and policymakers often use sociodemographic reporting to understand who clinical research does and does not apply to, so it’s important to represent study participants as completely as possible” said Oana Enache, MS, a PhD candidate in the Department of Biomedical Data Science at Stanford Medicine and lead author of the study.

Enache was recently awarded a prestigious Stanford Interdisciplinary Graduate Fellowship, which supports doctoral students pursuing impactful interdisciplinary research. The co-authors of the study are Lisa Goldman Rosas, PhD, MPH, an assistant professor in the Department of Epidemiology and Population Health, and senior author Sherri Rose, PhD, a professor of health policy and director of the Health Policy Data Science Lab.

The limitation of tabular reporting is especially timely in light of a recent federal law that will require the reporting of age, sex, race and ethnicity in late-stage clinical trials. This law aims to improve on the long history of trials that have largely excluded people of color, older adults, LGBTQIA+ populations, pregnant and lactating individuals, and disabled persons. Clinical trial sponsors will need to provide diversity enrollment plans for late-stage clinical trials to the FDA, although the implementation details are still being finalized. The law reflects content presented in the Diverse and Equitable Participation in Clinical Trials (DEPICT) Act, which was first introduced by U.S. House Reps. Anna G. Eshoo (D-CA), Brian Fitzpatrick (R-PA), and Robin Kelly (D-IL).

A Transparent Solution

To address the limitations of tabular sociodemographic reporting, Enache and colleagues propose the inclusion of a straightforward graph displaying baseline characteristics alongside the standard tables, which they argue would more completely represent participants’ identities and health. The authors note that decades of health and intersectionality research have shown that a person’s health is jointly influenced by many sociodemographic factors.

“Tables represent each characteristic separately,” Enache said. “However, no one is a certain race and separately a certain age and separately additional characteristics. Each of our identities is an overlapping set of demographic characteristics.”

The authors also provide guidance on how to implement sociodemographic graphs, concluding that the addition of more rigorous graphical reporting of characteristics would better inform standards of care, treatment decisions, and health outcomes.