Race and ethnicity reporting in uterine fibroid clinical trials: a systematic review and meta-analysis

Purpose Underreporting of race and ethnicity in clinical trials limits assessment of equity, generalisability and treatment relevance. This is particularly important in uterine fibroids, where disease burden, symptom severity and treatment pathways vary across population groups, especially among Black women. We evaluated the frequency, granularity and distribution of race- or ethnicity-related reporting in randomised controlled trials (RCTs) of uterine fibroid management. Methods We searched the Cochrane Library, Embase, MEDLINE/PubMed and Scopus from database inception to 24 March 2024 for English-language human RCTs evaluating uterine fibroid management. We extracted demographic terminology as reported by the original trial publications, recorded whether race or ethnicity data were reported, and harmonised categories to National Institutes of Health (NIH) racial and ethnic categories only where source reporting permitted. Descriptive analyses were undertaken, and random-effects meta-analyses were used to summarise reported group proportions. Results Of 1,673 records identified, 285 RCTs involving 33,360 participants met the inclusion criteria. Race or ethnicity data were reported in 68 (23.9%) RCTs. Trials reporting these data tended to have larger sample sizes and were more commonly conducted in high-income countries. Among RCTs reporting specific race or ethnicity categories (13,843 participants), 48.6% of participants were White, 37.7% Black and 8.2% Asian. Reporting increased over time but remained limited, with only 30.1% of RCTs published between 2019 and 2024 reporting these data. Conclusion Race and ethnicity reporting in uterine fibroid RCTs remains inadequate and inconsistent. The absence of standardised, granular demographic reporting leaves the applicability of trial findings across ethnic groups, and particularly those disproportionately affected by fibroids—uncertain. Future fibroid trials should use context-sensitive and transparent reporting frameworks for race, ethnicity and related population descriptors to strengthen equity, generalisability and personalised care.