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Nonregistration, Discontinuation, and Nonpublication of Randomized Trials

2025· article· en· W4413943352 on OpenAlexaffabout
Benjamin Speich, Ala Taji Heravi, Christof Schönenberger, L. Hausheer, Dmitry Gryaznov, Jason W. Busse, Manuela Covino, Szimonetta Lohner, Malena Chiaborelli, Johannes M. Schwenke, Ruben Ramirez Zegarra, Ramon Saccilotto, Julia Hüllstrung, Erik von Elm, Arnav Agarwal, Julian Hirt, David Mall, Alain Amstutz, Selina Epp, Dominik Mertz, Anette Blümle, Belinda von Niederhäusern, Ayodele Odutayo, Alexandra Griessbach, Sally Hopewell, Matthias Briel, Benjamin Kasenda, Elena Ojeda–Ruiz, Stefan Schandelmaier, Yuki Tomonaga, Christiane Pauli‐Magnus, Viktoria Gloy, Karin Bischoff, Katharina Wollmann, Laura Rehner, Joerg J Meerpohl, Alain Nordmann, Katharina Klatte, Nilabh Ghosh, Jacqueline Wong, Ngai Chow, Patrick Jiho Hong, Kimberly Mc Cord, Sirintip Sricharoenchai, Lukas Kübler, Pooja Gandhi, Zsuzsanna Némethné Kontár, Mona Elafy, Matthias Schwenkglenks, Giusi Moffa, Lars G. Hemkens

Bibliographic record

VenueJAMA Network Open · 2025
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of AlbertaCochraneMcMaster UniversityUniversity of TorontoUniversity Health NetworkImpact
Fundersnot available
KeywordsDiscontinuationRandomized controlled trialMedicineClinical trialFamily medicinePsychological interventionResearch ethicsEthics committeeProtocol (science)Alternative medicinePhysical therapyNursingSurgeryInternal medicinePsychiatryPathologyPolitical science

Abstract

fetched live from OpenAlex

Importance: Previous work found that 25% to 30% of randomized clinical trials (RCTs) with protocols approved in 2012 or between 2000 and 2003 were discontinued prematurely, most commonly due to inadequate participant recruitment. To minimize research waste, RCTs should be registered and their results made available. Objectives: To assess the fate of RCTs approved by ethics committees in 2016 in terms of nonregistration, discontinuation, and nonpublication, and to examine RCT characteristics associated with discontinuation due to poor recruitment and nonpublication of RCT results. Evidence Review: As a prespecified project of the Adherence to SPIRIT Recommendations (ASPIRE) study, this systematic review had access to 347 RCT protocols approved in 2016 by research ethics committees in the UK, Switzerland, Germany, and Canada. Eligible RCTs were defined as prospective studies randomly assigning participants to interventions to study effects on health outcomes. RCTs were excluded that never started, were ongoing at time of follow-up, were duplicates, or were labeled as pilot, feasibility, or phase 1 trials. Key trial characteristics were extracted from the approved trial protocols. In July 2024, pairs of reviewers systematically searched for trial registrations and results publications. When the status of either was unclear, the corresponding ethics committee or the principal investigator was contacted for clarification. Findings: Of 347 included RCTs, 20 (5.8%) were unregistered, 108 (31.1%) were discontinued, most often due to poor recruitment (49 [45.4%]), and 276 (79.5%) made their results publicly available. Results from industry-sponsored trials were more often available than non-industry-sponsored trials (166 of 181 [92.3%] vs 110 of 166 [66.3%]). This difference was attributable to a higher prevalence of industry-sponsored trials that reported results in trial registries (153 of 181 [84.5%]) vs nonindustry RCTs (17 of 166 [10.2%]). Multivariable logistic regression indicated that industry-sponsored trials were less frequently discontinued due to poor recruitment than non-industry-sponsored RCTs (adjusted odds ratio, 0.32 [95% CI, 0.15-0.71]). Conclusions and Relevance: Findings from this systematic review indicated that nonregistration, premature discontinuation due to poor recruitment, and nonpublication of RCT results remained major challenges, especially for non-industry-sponsored trials. To mitigate these challenges, requirements enforced by funders and ethics committees also taking into account legal obligations should be considered and empirically evaluated.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.064
metaresearch head score (Gemma)0.146
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.869
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0640.146
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.434
GPT teacher head0.598
Teacher spread0.165 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2025
Admission routes2
Has abstractyes

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