Prospective registration and reporting of trial number in randomised clinical trials: global cross sectional study of the adoption of ICMJE and Declaration of Helsinki recommendations
Bibliographic record
Abstract
OBJECTIVES: To evaluate the compliance with prospective registration and inclusion of the trial registration number (TRN) in published randomised controlled trials (RCTs), and to analyse the rationale behind, and detect selective registration bias in, retrospective trial registration. DESIGN: Cross sectional analysis. DATA SOURCES: PubMed, the 17 World Health Organization's trial registries, University of Toronto library, International Committee of Medical Journal Editors (ICMJE) list of member journals, and the InCites Journal Citation Reports. STUDY SELECTION CRITERIA: RCTs registered in any WHO trial registry and published in any PubMed indexed journal in 2018. RESULTS: This study included 10 500 manuscripts published in 2105 journals. Overall, 71.2% (7473/10500) reported the TRN and 41.7% (3013/7218) complied with prospective trial registration. The univariable and multivariable analyses reported significant relations (P<0.05) between reporting the TRN and the impact factor and ICMJE membership of the publishing journal. A significant relation (P<0.05) was also observed between prospective trial registration and the registry, region, condition, funding, trial size, interval between paper registration and submission dates, impact factor, and ICMJE membership of the publishing journal. A manuscript published in an ICMJE member journal was 5.8 times more likely to include the TRN (odds ratio 5.8, 95% confidence interval 4.0 to 8.2), and a published trial was 1.8 times more likely to be registered prospectively (1.8, 1.5 to 2.2) when published in an ICMJE member journal compared with other journals. This study detected a new form of bias, selective registration bias, with a higher proportion (85.2% (616/723)) of trials registered retrospectively within a year of submission for publication. Higher rates of retrospective registrations were observed within the first three to eight weeks after enrolment of study participants. Within the 286 RCTs registered retrospectively and published in an ICMJE member journal, only 2.8% (8/286) of the authors included a statement justifying the delayed registration. Reasons included lack of awareness, error of omission, and the registration process taking longer than anticipated. CONCLUSIONS: This study found a high compliance in reporting of the TRN for trial papers published in ICMJE member journals, but prospective trial registration was low.
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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 | 0.843 | 0.891 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.015 | 0.024 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.008 | 0.010 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".