Examining Bias in Published Surgical Glaucoma Clinical Trials
Bibliographic record
Abstract
PRÉCIS: Our results demonstrate that, among randomized clinical trials examining the use of surgical treatments for glaucoma, the majority were not registered. Publication bias (PB) was less likely. More than a third of registered trials presented outcome reporting bias (ORB). PURPOSE: Despite the optimum of quality evidence provided by randomized controlled trials (RCTs), biases may be introduced and hinder their application. The primary objective of this study was to investigate ORB and PB in RCTs assessing surgical treatments of glaucoma, as well as their registration status. MATERIALS AND METHODS: A literature review was conducted in MEDLINE, EMBASE, and CENTRAL databases. Inclusion criteria were RCTs published in English between 2007 and 2021 that focused on surgical treatments of patients of all ages with glaucoma or elevated intraocular pressure. Exclusion criteria included cadaveric and animal studies. Registration status was correlated with entries from clinical trial registries. PB was determined by the proportion of trials presenting statistically significant results. ORB was evaluated by comparing the study's primary outcome with that listed in the trial registry. Trials quality was assessed using the Jadad score. RESULTS: After deleting duplicates, 7561 citations were screened. One hundred sixty-one RCTs were eligible and included between 13 and 556 participants. Of the total, 91% studied an adult population and 71% included patients suffering from primary open angle glaucoma. Among included studies, 63% were not registered and 47% had statistically significant results. An upward trend in registration was observed with time. However, 37% of the studies showed discrepancies between objectives in cited clinical trial registries and the published results. CONCLUSION: PB in surgical glaucoma trials was not obvious. Among the minority of trials that were registered, more than a third presented ORB. Unregistered trials had lower quality. RCT registration is crucial for the transparent interpretation of studies, improved patient care in surgery, and informed decision-making.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, not a consensus.
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".