Medical Journal Policies on Requirements for Clinical Trial Registration, Reporting Guidelines, and Data Sharing: A Systematic Review
Notice bibliographique
Résumé
Kyobin Hwang,<sup>1</sup> Zexing Song,<sup>2,3</sup> Marsida Stafa,<sup>3</sup> Jodie Chiu<sup>,4</sup><sup> </sup>An-Wen Chan<sup>1,3,5</sup> <h4>Objective</h4> We aimed to determine how often medical journals have policies requiring clinical trial registration, adherence to reporting guidelines, and participant-level data sharing. We also evaluated associations between journal characteristics and the existence of such policies for clinical trial manuscripts. <h4>Design </h4>A PubMed search using the clinical trial filter was conducted to identify journals that published at least 20 trials in 2023. We extracted publicly available data from journal websites, including policies on trial registration, adherence to reporting guidelines, trial protocol submission requirements, and availability of participant-level data. A practice was classified as required if the policy used words such as must, need, or should. Policies using language such as encouraged and preferred were classified as recommended practices. For each journal, we recorded the 2023 Clarivate impact factor, journal scope (general vs specialty), and publishing model (purely open access vs other). We calculated descriptive statistics to summarize the prevalence of transparency policies and used multivariable logistic regression to assess the association between journal characteristics and policy requirements. <h4>Results</h4> Among 380 included journals, 320 (84%) required trial registration, 11 (3%) recommended it, and 49 (13%) did not mention it. Adherence to a reporting guideline for clinical trials was required by 251 journals (66%), recommended by 74 (19%), and not mentioned by 55 (14%). Trial protocol submission was required by 118 (31%), recommended by 110 (29%), and not mentioned in 152 (40%). Public availability of participant-level datasets was required by 104 (27%), recommended by 218 (57%), and not mentioned by 58 (15%). A description of the data sharing plan was required by 212 journals (55.8%), recommended by 110 (28.9%), and not mentioned by 58 (15.3%). Purely open access journals had a 4-fold higher odds of requiring trial registration (adjusted odds ratio [AOR], 4.02; 95% CI, 1.41-15.59) and protocol submission (AOR, 4.13; 95% CI, 2.17-8.37) and 2.5 times higher odds of requiring public sharing of participant-level data (AOR, 2.46; 95% CI, 1.03-7.04) compared with other journals (<b>Table 25-1183</b>). Each 5-point increase in journal impact factor was associated with a more than 2.5-fold increase in the odds of requiring trial registration (AOR, 2.65; 95% CI, 1.45-5.98) and over 50% increase in the odds of requiring protocol submission (AOR, 1.56; 95% CI, 1.26-2.03). Impact factor was not significantly associated with requiring data sharing. No significant associations were found for journal scope or volume of trials published. https://assets.underline.io/markdown_image/1/image/1f3e3ae7eedf2cd146453708cac3c6fc.png <h4>Conclusions</h4> Journal policy requirements vary substantially in supporting best practices for clinical trial transparency. Journals with a purely open access publishing model and higher impact factor were more likely to adopt transparency policies. These findings highlight the need for improved editorial standards across the publishing landscape to promote transparency and reduce research waste. <sup>1</sup>Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada, anwen.chan@utoronto.ca; <sup>2</sup>Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; <sup>3</sup>Women’s College Research Institute, Toronto, Ontario, Canada; <sup>4</sup>Faculty of Health Science, University of Western Ontario, London, Ontario, Canada; <sup>5</sup>Division of Dermatology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada. <h4>Conflict of Interest Disclosures</h4> An-Wen Chan is a member of the Peer Review Congress Advisory Board but was not involved in the review or decision for this abstract.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,261 | 0,703 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,005 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,013 | 0,005 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».