Discontinuation and non-publication of randomised clinical trials supported by the main public funding body in Switzerland: a retrospective cohort study
Bibliographic record
Abstract
OBJECTIVE: The Swiss National Science Foundation (SNSF) promotes academic excellence through competitive selection of study proposals and rigorous evaluation of feasibility, but completion status and publication history of SNSF-supported randomised clinical trials (RCTs) remain unclear. The main objectives were to review all healthcare RCTs supported by the SNSF for trial discontinuation and non-publication, to investigate potential risk factors for trial discontinuation due to poor recruitment and non-publication, and to compare findings to other Swiss RCTs not supported by the SNSF. DESIGN: We established a retrospective cohort of all SNSF-supported RCTs for which recruitment and funding had ended in 2015 or earlier. For each RCT, two investigators independently searched corresponding publications in electronic databases. In addition, we approached all principal investigators to ask for additional publications and information about trial discontinuation. Teams of two investigators independently extracted details about study design, recruitment of participants, outcomes, analysis and sample size from the original proposal and, if available, from trial registries and publications. We used multivariable regression analysis to explore potential risk factors associated with discontinuation due to poor recruitment and with non-publication, and to compare our results with data from a previous cohort of Swiss RCTs not supported by the SNSF. RESULTS: We included 101 RCTs supported by the SNSF between 1986 and 2015. Eighty-seven (86%) principal investigators responded to our survey. Overall, 69 (68%) RCTs were completed, 26 (26%) RCTs were prematurely discontinued (all due to slow recruitment) and the completion status remained unclear for 6 (6%) RCTs. For analysing publication status, we excluded 4 RCTs for which follow-up was still ongoing and 9 for which manuscripts were still in preparation. Of the remaining 88 RCTs, 53 (60%) were published as full articles in peer-reviewed journals. Multivariable regression models suggested that discontinued trials were at higher risk for non-publication than completed trials (adjusted OR 7.61; 95% CI 2.44 to 27.09). Compared with other Swiss RCTs, the risk of discontinuation for SNSF-supported RCTs was higher than in industry-initiated RCTs (adjusted OR 3.84; 95% CI 1.68 to 8.74), but not significantly different from investigator-initiated RCTs not supported by the SNSF (adjusted OR 1.05; 95% CI 0.51 to 2.11). We found no evidence that the proportion of discontinued or unpublished RCTs decreased over the last 20 years. CONCLUSIONS: One out of four SNSF-supported RCTs were prematurely discontinued due to slow recruitment, 40% of all included RCTs and 70% of all discontinued RCTs were not published in peer-reviewed journals. There is a case to reconsider how public funding bodies such as the SNSF could improve their feasibility assessment and promote publication of RCTs irrespective of completion status.
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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 | 0.218 | 0.387 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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; both teacher heads 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".