Outcome Reporting bias in Exercise Oncology trials (OREO): a cross-sectional study
Notice bibliographique
Résumé
Abstract Background Despite evidence of selective outcome reporting across multiple disciplines, this has not yet been assessed in trials studying the effects of exercise in people with cancer. Therefore, the purpose of our study was to explore prospectively registered randomised controlled trials (RCTs) in exercise oncology for evidence of selective outcome reporting. Methods Eligible trials were RCTs that 1) investigated the effects of at least partially supervised exercise interventions in people with cancer; 2) were preregistered (i.e. registered before the first patient was recruited) on a clinical trials registry; and 3) reported results in a peer-reviewed published manuscript. We searched the PubMed database from the year of inception to September 2020 to identify eligible exercise oncology RCTs clinical trial registries. Eligible trial registrations and linked published manuscripts were compared to identify the proportion of sufficiently preregistered outcomes reported correctly in the manuscripts, and cases of outcome omission, switching, and silently introduction of non-novel outcomes. Results We identified 31 eligible RCTs and 46 that were ineligible due to retrospective registration. Of the 405 total prespecified outcomes across the 31 eligible trials, only 6.2% were preregistered complete methodological detail. Only 16% (n=148/929) of outcomes reported in published results manuscripts were linked with sufficiently preregistered outcomes without outcome switching. We found 85 total cases of outcome switching. A high proportion (41%) of preregistered outcomes were omitted from the published results manuscripts, and many published outcomes (n=394; 42.4%) were novel outcomes that had been silently introduced (median, min-max=10, 0-50 per trial). We found no examples of preregistered efficacy outcomes that were measured, assessed, and analysed as planned. Conclusions We found evidence suggestive of widespread selective outcome reporting and non-reporting bias (outcome switching, omitted preregistered outcomes, and silently introduced novel outcomes). The existence of such reporting discrepancies has implications for the integrity and credibility of RCTs in exercise oncology. Preregistered protocol https://osf.io/dtkar/ (posted: November 19, 2019)
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 | 0,737 | 0,650 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,020 | 0,007 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,004 | 0,000 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,018 | 0,001 |
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 ».