Reporting of noninferiority and equivalence randomized trials for major prostaglandins: A systematic survey of the ophthalmology literature
Bibliographic record
Abstract
BACKGROUND: Standards for reporting clinical trials have improved the transparency of patient-important research. The Consolidated Standards of Reporting Trials (CONSORT) published an extension to address noninferiority and equivalence trials. We aimed to determine the reporting quality of prostaglandin noninferiority and equivalence trials in the treatment of glaucoma. METHODS: We searched, independently and in duplicate, 6 electronic databases for eligible trials evaluating prostaglandins. We abstracted data on reporting of methodological criteria, including reporting of per-protocol [PP] and intention-to-treat [ITT] analysis, sample size estimation with margins, type of statistical analysis conducted, efficacy summaries, and use of hyperemia measures. RESULTS: Trials involving the four major prostaglandin groups (latanoprost, travoprost, bimatoprost, unoprostone) were analyzed. We included 36 noninferiority and 11 equivalence trials. Seventeen out of the included 47 trials (36%, 95% Confidence Intervals [CI]: 24-51) were crossover designs. Only 3 studies (6%, 95% CI: 2-17) reported a presented results of both ITT and PP populations. Twelve studies (26%, 95% CI: 15-39) presented only ITT results but mentioned that PP population had similar results. Thirteen trials (28%, 95% CI: 17-42) presented only PP results with no mention of ITT population results while 17 studies (36%, 95% CI: 24-51) presented only ITT results with no mention of PP population results. Thirty-four (72%, 95% CI: 58-83) of studies adequately described their margin of noninferiority/equivalence. Sequence generation was reported in 22/47 trials (47%, 95% CI: 33-61). Allocation concealment was reported in only 10/47 (21%, 95% CI: 12-35) of the trials. Thirty-five studies (74%, 95% CI: 60-85) employed masking of at least two groups, 4/47 (9%, 95% CI: 3-20) masked only patients and 8/47 (17%, 95% CI: 9-30) were open label studies. Eight (17%, 95% CI: 9-30) of the 47 trials employed a combined test of noninferiority and superiority. We also found 6 differing methods of evaluating hyperemia. CONCLUSION: The quality of reporting noninferiority/equivalency trials in the field of glaucoma is markedly heterogeneous. The adoption of the extended CONSORT statement by journals will potentially improve the transparency of this field.
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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 | 0.338 | 0.705 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.024 | 0.023 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".