PRISMA-DTA: An Extension of PRISMA for Reporting of Diagnostic Test Accuracy Systematic Reviews
Notice bibliographique
Résumé
Systematic reviews of diagnostic test accuracy (DTA)4 studies can help to clarify the clinical performance of laboratory tests. Such reviews hold a high position within the hierarchy of evidence, are published more frequently, and are often highly cited. Yet, poorly reported systematic reviews may prevent readers from assessing the quality of included primary studies, the extent of literature searched, and the applicability of results to clinical questions. Reporting guidelines have been developed to support transparent and complete descriptions of research, facilitating reproducible research and minimizing waste. Dissemination of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist, a guide for reporting systematic reviews, has been associated with improvements in reporting completeness and higher review quality. DTA systematic reviews, the most frequent review type in Clinical Chemistry, differ with respect to optimal methods and reporting practices from reviews of interventions. To better reflect the unique aspects required for reporting of DTA systematic reviews, the PRISMA-DTA group recently published an extension of PRISMA: PRISMA-DTA (1). PRISMA-DTA is a reporting guideline consisting of a 27-item checklist and flow diagram. Of the original PRISMA checklist's 27 items, 8 were unchanged, 17 were modified, 2 were added, and 2 were removed. In addition, PRISMA for abstracts was modified to create a 12-item PRISMA-DTA for abstracts; of the original PRISMA for abstracts, 5 items were unchanged, 1 was removed, and 1 was added. User-friendly versions of the checklists to facilitate reporting for authors, editors, and reviewers can be found on the EQUATOR network and PRISMA websites. A major change from PRISMA is the removal of the requirement to evaluate and report publication bias within studies (PRISMA items 15 and 22). This was related to the limited evidence for such bias in diagnostic accuracy research, as well as the lack of a test with sufficient statistical power to detect it. The structure of the review question was altered from an intervention-centric focus (e.g., patient and intervention) to one that is DTA-specific (e.g., patient, index test, and target condition). Reporting of the statistical methods used in metaanalysis is a new requirement for PRISMA-DTA, as these reviews require specific hierarchical methods that differ from those for interventions. Many additional changes were made to reflect DTA-specific and/or optimal contemporary systematic review methods. Potential challenges surrounding adherence to the PRISMA-DTA continue to exist. For example, logistical constraints on word counts and figures may pose barriers to complete reporting. The use of supplementary materials or appendices can often help overcome these challenges. The PRISMA-DTA group hopes that PRISMA-DTA (and PRISMA-DTA for abstracts) serves as a valuable resource to guide reporting for Clinical Chemistry authors, and can also help reviewers and editors determine completeness of reporting. Those looking for further guidance on the topic can refer to the complete PRISMA-DTA publication and/or the forthcoming explanation and elaboration document. diagnostic test accuracy Preferred Reporting Items for Systematic Reviews and Meta-Analyses.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,316 | 0,564 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,007 |
| Méta-épidémiologie (sens large) | 0,012 | 0,027 |
| Bibliométrie | 0,024 | 0,030 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,008 | 0,007 |
| Science ouverte | 0,008 | 0,011 |
| Intégrité de la recherche | 0,005 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,070 | 0,013 |
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; l’étiquette directe de Gemma et le classifieur distillé Codex 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 ».