Outcome Reporting bias in Exercise Oncology trials (OREO): a cross-sectional study
Bibliographic record
Abstract
Abstract Background Despite evidence of selective outcome reporting across multiple disciplines, this has not yet been assessed in trials studying the effects of exercise in people with cancer. Therefore, the purpose of our study was to explore prospectively registered randomised controlled trials (RCTs) in exercise oncology for evidence of selective outcome reporting. Methods Eligible trials were RCTs that 1) investigated the effects of at least partially supervised exercise interventions in people with cancer; 2) were preregistered (i.e. registered before the first patient was recruited) on a clinical trials registry; and 3) reported results in a peer-reviewed published manuscript. We searched the PubMed database from the year of inception to September 2020 to identify eligible exercise oncology RCTs clinical trial registries. Eligible trial registrations and linked published manuscripts were compared to identify the proportion of sufficiently preregistered outcomes reported correctly in the manuscripts, and cases of outcome omission, switching, and silently introduction of non-novel outcomes. Results We identified 31 eligible RCTs and 46 that were ineligible due to retrospective registration. Of the 405 total prespecified outcomes across the 31 eligible trials, only 6.2% were preregistered complete methodological detail. Only 16% (n=148/929) of outcomes reported in published results manuscripts were linked with sufficiently preregistered outcomes without outcome switching. We found 85 total cases of outcome switching. A high proportion (41%) of preregistered outcomes were omitted from the published results manuscripts, and many published outcomes (n=394; 42.4%) were novel outcomes that had been silently introduced (median, min-max=10, 0-50 per trial). We found no examples of preregistered efficacy outcomes that were measured, assessed, and analysed as planned. Conclusions We found evidence suggestive of widespread selective outcome reporting and non-reporting bias (outcome switching, omitted preregistered outcomes, and silently introduced novel outcomes). The existence of such reporting discrepancies has implications for the integrity and credibility of RCTs in exercise oncology. Preregistered protocol https://osf.io/dtkar/ (posted: November 19, 2019)
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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 | 0.404 | 0.577 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".