Sex or Gender Reporting in Ophthalmology Clinical Trials Among US Food and Drug Administration Approvals, 1995 to 2022
Bibliographic record
Abstract
Importance: As critical determinants of scientific rigor, reproducibility, and equity, sex and gender should be considered in clinical trial design and reporting. Objective: To evaluate the accuracy of sex and gender reporting and extent of sex- and gender-based analysis in clinical trials associated with US Food and Drug Administration (FDA) drug approvals between January 1, 1995, and December 31, 2022. Design, Setting, and Participants: In this cross-sectional study of participants enrolled in FDA ophthalmology trials, the following trial documents were reviewed by pairs of independent reviewers in decreasing order of priority: peer-reviewed publication, ClinicalTrials.gov report, and FDA medical and statistical reviews. Trial protocols and supplementary materials were also reviewed. Main Outcome and Measures: The proportion of trials that correctly applied sex and gender terminology, reported the method of assessing sex or gender, and conducted sex- or gender-based data analysis; incorrect application of sex and gender terminology was defined as interchangeable use of sex- and gender-related terms without a clear justification. Results: Between 1995 and 2022, 34 ophthalmic drugs corresponding to 85 trials (34 740 participants) received FDA approval, of which 16 drugs (47.1%) corresponding to 32 trials (18 535 participants [37.6%]) were associated with peer-reviewed publications. Sixteen trials used sex and gender terminology correctly (19.5%). No trial reported how sex and gender were collected nor enrolled participants from sexual and gender identity minority populations. Most trials reported sex- and gender-disaggregated demographic data (96.5%), but few conducted sex- or gender-based analysis for data on dropout (1.2%), primary outcomes (28.2%), secondary outcomes (2.4%), and adverse events (9.4%). Erroneous sex and gender reporting was associated with later publication year (2008.5 vs 2001.0; median difference, 7.5; 95% CI, -6.0 to 11.0; P < .001) and higher journal influence metrics, including 2022 journal impact factor (13.7 vs 5.9; median difference, 7.8; 95% CI, -1.4 to 152.4, P < .001) and 2022 journal citation indicator (4.9 vs 2.1; median difference, 2.9; 95% CI, 0-20.0, P < .001). Conclusions and Relevance: In this observational study, over three-quarters of ophthalmology trials associated with FDA drug approvals conflated sex and gender and over two-thirds lacked sex- and gender-based analyses. More rigorous integration of sex and gender appears warranted for FDA, and presumably other trials, to improve their validity, reproducibility, and equity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.618 | 0.834 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".