Methodological Characteristics of Clinical Trials: Impact of Mandatory Trial Registration
Bibliographic record
Abstract
PURPOSE: Numerous studies across multiple specialties have evaluated the impact of trial registration on quality of study reports and found significant improvements over several domains. However, the impact of mandatory trial registration on the quality of clinical trial protocols remains hitherto unexplored. METHODS: We carried out a retrospective cohort study of clinical trial applications submitted to drug regulatory authority of India for initial review with the objective of comparing methodological characteristics of their protocols. Since trial registration was made mandatory in the country in June 2009, we selected two study periods as between January 2007 to May 2009 (Period I) and July 2009 to December 2011 (Period II). Seventy-five protocols were randomly selected using a computer-generated list for each study period, making a total of 150 protocols. Data on twelve key methodological characteristics were collected including clearly defined primary outcomes, randomization, blinding, use of control group, statistical methods, handling of withdrawals amongst others. RESULTS: More than 3/4th of the trial applications in the two study periods were for new chemical entities and nearly 90% were pharmaceutical industry sponsored studies. Comparing the period before and after implementation of mandatory trial registration, description of clearly defined trial outcomes improved from nearly 42% to 80% (p<0.001), sample size justifications increased from 38% to 70% (p<0.001) and use of allocation concealment improved from 24% to 49% (p=0.001). Marked improvement was also noted for blinding, description of statistical methods and handling of withdrawals and dropouts. Remaining characteristics did not change significantly between the two study periods. The mean cumulative scores for the study protocols improved significantly from 7± 0.296 in the first period to 8.93± 0.346 (p<0.001) in the second period. CONCLUSIONS: Our study found a significant improvement in the methodological quality characteristics of the protocols particularly in elements related to minimization of bias and statistical methods, which could be attributed to mandatory trial registration. Overall, the significant improvement was limited to global clinical trials, and room for improvement was noted for two quality characteristics - proportion of randomized studies and trials adequately describing the generation of allocation sequence.
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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 | 0.717 | 0.850 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".