Reporting of conflicts of interest from drug trials in Cochrane reviews: cross sectional study
Bibliographic record
Abstract
OBJECTIVES: To investigate the degree to which Cochrane reviews of drug interventions published in 2010 reported conflicts of interest from included trials and, among reviews that reported this information, where it was located in the review documents. DESIGN: Cross sectional study. DATA SOURCES: Cochrane Database of Systematic Reviews. SELECTION CRITERIA: Systematic reviews of drug interventions published in 2010 in the Cochrane Database of Systematic Reviews, with review content classified as up to date in 2008 or later and with results from one or more randomised controlled trials. RESULTS: Of 151 included Cochrane reviews, 46 (30%, 95% confidence interval 24% to 38%) reported information on the funding sources of included trials, including 30 (20%, 14% to 27%) that reported information on trial funding for all included trials and 16 (11%, 7% to 17%) that reported for some, but not all, trials. Only 16 of the 151 Cochrane reviews (11%, 7% to 17%) provided any information on trial author-industry financial ties or trial author-industry employment. Information on trial funding and trial author-industry ties was reported in one to seven locations within each review, with no consistent reporting location observed. CONCLUSIONS: Most Cochrane reviews of drug trials published in 2010 did not provide information on trial funding sources or trial author-industry financial ties or employment. When this information was reported, location of reporting was inconsistent across reviews.
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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 | 0.414 | 0.826 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.021 | 0.027 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".