Development of a reporting guideline for umbrella reviews on epidemiological associations using cross-sectional, case-control, and cohort studies: the Preferred Reporting Items for Umbrella Reviews of Cross-sectional, Case-control, and Cohort studies (PRIUR-CCC)
Notice bibliographique
Résumé
Abstract Introduction Observational studies are fraught with several biases including reverse causation and residual confounding, which may limit the credibility of reported associations. Overview of reviews of observational studies (i.e., umbrella reviews) synthesize systematic reviews with or without meta-analyses of cross-sectional, case-control, and cohort studies, and may also aid in the grading of the credibility of reported associations. The number of published umbrella reviews has been increasing at a rapid pace. Recently, a reporting guideline for overviews of reviews of healthcare interventions (PRIOR, Preferred Reporting Items for Overviews of Reviews) was published, but the field lacks reporting guidelines for umbrella reviews of observational studies. Thus, our aim is to develop a reporting guideline for umbrella reviews on cross-sectional, case-control, and cohort studies assessing epidemiological associations. Methods and Analyses We will adhere to established guidance on how to develop reporting guidelines in health research and follow four steps to prepare a PRIOR extension for systematic reviews of cross-sectional, case-control, and cohort studies testing epidemiological associations between an exposure and an outcome, namely Preferred Reporting Items for Umbrella Reviews of Cross-sectional, Case-control, and Cohort studies (PRIUR-CCC). Step 1 will be the project launch to identify stakeholders. Step 2 will be a literature review of available guidance to conduct umbrella reviews. Step 3 will be a Delphi study sampling authors and editors of umbrella reviews, Delphi surveys and checklists of epidemiological studies, as well as funders, practitioners, and policy makers, which will be conducted in three rounds. Step 4 will encompass the finalization of PRIUR-CCC statement, including a checklist, a flow diagram, explanation, and elaboration document. Deliverables of each step will be as follows. First, identifying stakeholders to involve according to relevant expertise and end-user groups, with an equity, diversity, and inclusion lens. Second, completing a narrative review of methodological guidance on how to conduct umbrella reviews, a narrative review of methodology and reporting in published umbrella reviews, and preparing an initial PRIUR-CCC checklist for Delphi study Round 1. Third, preparing a PRIUR-CCC checklist with guidance after Delphi study. Fourth, publishing and disseminating PRIUR-CCC statement. Ethics and Dissemination PRIUR-CCC will guide reporting of umbrella reviews on epidemiological associations, with the aim to improve quantitative, credible, and transparent reporting, in a field of evidence synthesis where there is important methodological heterogeneity of reviews, and where sources of bias in original observational studies can lead to misleading conclusions. Strengths This is the first protocol for reporting guidance of umbrella reviews of epidemiological associations This protocol follows the guidance for reporting checklist, which are standard in the field. This protocol is urgently needed given the large number of umbrella reviews on epidemiological associations emerging across different branches of science
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 | 0,187 | 0,336 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».