Racial, Ethnic, and Gender Diversity in United States Ophthalmology Clinical Trials
Fateme Montazeri, Michael C. Wang, Abhijith Atkuru, Marcela Maria Estrada, Yin Liu, Parisa Emami-Naeini
Abstract
ObjectiveTo investigate the representation of different gender, racial, and ethnic groups in ophthalmology clinical trials conducted in the United States (US) between 1997 and 2022.DesignRetrospective cross-sectional study.SubjectsDemographics of participants in completed phase 2/3, 3, and 4 ophthalmology clinical trials reported on the ClincialTrials.gov database.MethodsThe proportional enrollment of each racial/ethnic and gender group in the clinical trials was calculated compared to the overall US population. We also investigated the impact of various clinical trial features on the rate of reporting demographic information and enrollment of minorities.Main Outcome MeasuresProportional enrollment of each gender and race/ethnicity group compared to the US Census.ResultsOf the total clinical trials included in the study, less than half (43.6%) provided information about the racial or ethnic backgrounds of their participants. The majority of the enrollees in trials were female (median 57.5%, interquartile range (IQR) 47.2-65.8%). Among the trials that reported information about race and/or ethnicity, White populations were overrepresented (median 76.6%, IQR 69.0-84.0%, p=0.001), and minorities, including Asian, Hispanic, and ‘Other’ groups, were underrepresented compared to the 2010 US Census (p<0.001). However, enrollment of Black individuals was found to be comparable to the US population estimates (median 12.4%, IQR 6.2-20.8%, p=0.44). The trial phase, the number of study participants, the primary clinical condition, and the year the trial started all affected minority reporting and enrollment.ConclusionsOur findings highlight the need for increased efforts to promote diversity and inclusivity in ophthalmology clinical trials. Ensuring equitable inclusion of different gender, racial, and ethnic groups in these trials is essential for minimizing disparities and producing unbiased scientific findings generalizable to the entire population.