Nonregistration, Discontinuation, and Nonpublication of Randomized Trials in Switzerland, the UK, Germany, and Canada: An Updated Meta-Research Study
Bibliographic record
Abstract
Benjamin Speich,<sup>1</sup> Ala Taji Heravi,<sup>1</sup> Johannes M. Schwenke,<sup>1</sup> Christof M. Schönenberger,<sup>1</sup> Lena Hausheer,<sup>1</sup> Dmitry Gryaznov,<sup>1</sup> Jason W. Busse,<sup>2,3</sup> Manuela Covino,<sup>1</sup> Szimonetta Lohner,<sup>4</sup> Malena Chiaborelli,<sup>1</sup> Ruben<sup> </sup>Ramirez,<sup>1</sup> Ramon Saccilotto,<sup>5</sup> Erik von Elm,<sup>6</sup> Arnav Agarwal,<sup>3</sup> Julian Hirt,<sup>7</sup> David Mall,<sup>1</sup> Alain Amstutz,<sup>1</sup> Selina Epp,<sup>1</sup> Dominik Mertz,<sup>3</sup> Anette Blümle,<sup>8</sup> Belinda von Niederhäusern,<sup>9</sup> Ayodele Odutayo,<sup>10</sup> Alexandra N. Griessbach,<sup>1</sup> Sally Hopewell,<sup>11</sup> Matthias Briel,<sup>1,3</sup> for the ASPIRE Study Group <h4>Objective</h4> Previous studies found that approximately one-third of randomized clinical trials (RCTs) were discontinued prematurely and that the most common reason for stopping early was poor recruitment of participants. To minimize research waste, it is crucial that all RCTs are registered and make their results available. Hence, we aimed to (1) assess the fate of RCTs approved by ethics committees in 2016 in terms of nonregistration, discontinuation, and nonpublication and (2) examine RCT characteristics associated with discontinuation due to poor recruitment and nonpublication of RCT results. <h4>Design</h4> We had access to 347 RCT protocols that were approved in 2016 by research ethics committees in the UK, Switzerland, Germany, and Canada. Key trial characteristics were extracted from approved trial protocols. <span lang="de-DE">Trial registration was verified using registration numbers from the protocol and by searching the </span>World Health Organization<span lang="de-DE"> International Clinical Trials Registry Platform, ClinicalTrials.gov, </span>European Union Clinical Trials Register<span lang="de-DE">, ISRCTN, and Google; trials were deemed nonregistered if not found. We searched for full-text publications in PubMed, Google Scholar, and Scopus. Searches for both registration and publication used (</span>1<span lang="de-DE">) full titles</span>,<span lang="de-DE"> (</span>2<span lang="de-DE">) short titles</span>,<span lang="de-DE"> (</span>3<span lang="de-DE">) study acronyms</span>,<span lang="de-DE"> and (</span>4<span lang="de-DE">) the study population and intervention. </span>All searches were conducted in duplicate (last search, July 2024). In case the status of an RCT was unclear, we contacted the corresponding ethics committee or the principal investigator. We reported the proportion of nonregistered RCTs, discontinued RCTs (including reason for early discontinuation), and nonpublished RCTs (considering peer-reviewed publications and results in trial registries). <h4>Results</h4> Of the 347 included RCTs from 2016, 20 (5.8%) were nonregistered (industry-sponsored RCTs, 5 of 181 [2.8%]; nonindustry RCTs, 15 of 166 [9.0%]). Approximately one-third of RCTs (108 of 347 [31.1%]) were discontinued, most often due to poor recruitment (49 of 108 [45.4%]). A total of 276 of 347 RCTs (79.5%) made their results available at any source, 249 (71.8%) as a peer-reviewed publication, and 170 (49.0%) in the trial registry. Discontinued RCTs had lower result availability than completed RCTs (discontinued, 74 of 108 [68.5%]; completed, 202 of 226 [89.4%]). Results from industry-sponsored trials were more often available compared with nonindustry trials (92% vs 66%). This difference was driven by the fact that only 17 of 166 nonindustry RCTs (10.2%) reported results in trial registries compared with 153 of 181 industry trials (84.5%). The status of 4% of RCTs remained unclear despite our efforts to contact investigators. <h4>Conclusions</h4> Nonregistration, premature discontinuation due to poor recruitment, and nonpublication of RCT results remain major challenges, especially for nonindustry trials. <sup>1</sup>Division of Clinical Epidemiology, Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland, johannesmanteo.schwenke@usb.ch; <sup>2</sup>Department of Anesthesia, McMaster University, Hamilton, Ontario, Canada; <sup>3</sup>Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada; <sup>4</sup>MTA–PTE Lendület Momentum Evidence in Medicine Research Group, Medical School, University of Pécs, Pécs, Hungary; <sup>5</sup>Clinical Trial Unit, Department of Clinical Research, University of Basel and University Hospital Basel, Basel, Switzerland; <sup>6</sup>Cochrane Switzerland, Centre for Primary Care and Public Health (Unisante), University of Lausanne, Lausanne, Switzerland; <sup>7</sup>Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland; <sup>8</sup>Clinical Trials Unit, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany; <sup>9</sup>Roche Pharma AG, Grenzach-Wyhlen, Germany; <sup>10</sup>University Health Network, Division of Nephrology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada; <sup>11</sup>Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK. <h4>Conflict of Interest Disclosures</h4> Benjamin Speich and Matthias Briel received unrestricted grants from Moderna for the conduct of the COVERALL-2 and COVERALL-3 study. Benjamin Speich has received honoraria from Moderna and Roche for presenting study results not related to this work. Johannes M. Schwenke is paid by the Swiss National Science Foundation for work unrelated to this project. No other disclosures were reported. <h4>Funding/Support</h4> The study is supported by the Swiss Federal Office of Public Health (Matthias Briel). <h4>Role of the Funder/Sponsor</h4> The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the abstract; and decision to submit the abstract for presentation. <h4>Group Information</h4> The ASPIRE Study Group included Dmitry Gryaznov, Belinda von Niederhäusern, Benjamin Speich, Benjamin Kasenda, Elena Ojeda-Ruiz, Anette Blümle, Stefan Schandelmaier, Dominik Mertz, Ayodele Odutayo, Yuki Tomonaga, Alain Amstutz, Christiane Pauli-Magnus, Viktoria Gloy, Szimonetta Lohner, Karin Bischoff, Katharina Wollmann, Laura Rehner, Joerg J. Meerpohl, Alain Nordmann, Katharina Klatte, Nilabh Ghosh, Ala Taji Heravi, Jacqueline Wong, Ngai Chow, Patrick Jiho Hong, Kimberly McCord, Sirintip Sricharoenchai, Jason W. Busse, Lukas Kübler, Pooja Gandhi, Zsuzsanna Kontar, Julia Hüllstrung, Mona Elafy, Arnav Agarwal, Ramon Saccilotto, Alexandra N. Griessbach, Christof Schönenberger, Matthias Schwenkglenks, Giusi Moffa, Lars G. Hemkens, Sally Hopewell, Erik von Elm, and Matthias Briel. <h4>Additional Information</h4> Matthias Briel is a co–corresponding author (matthias.briel@usb.ch).
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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 | 0.209 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".