Individual-Participant Data Meta-Analysis Methodological Guidance: A Systematic Review
Notice bibliographique
Résumé
Edith Otalike,<sup>1</sup> Mike Clarke,<sup>2</sup> Ngianga-Bakwin Kandala,<sup>1</sup> Joel J. Gagnier<sup>1,3</sup> <h4>Objective</h4> Individual-participant data meta-analysis (IPD-MA) is regarded as the criterion standard in evidence synthesis, but it is resource intensive. While there is consensus on reporting items, a consensus-based tool for the critical appraisal of the methodological quality of IPD-MA does not currently exist. We undertook a systematic methodology review as the initial phase in the development of a critical appraisal checklist. This review collated and summarized the available methodological guidance on IPD-MA of randomized and observational studies. <h4>Design</h4> We followed the guidelines for Cochrane Methodology Reviews and reported following the PRISMA 2020 guidance. We performed an electronic search of MEDLINE, Embase, CINAHL, Web of Science Scopus, Cochrane Methodology Registry, CONSORT Database of Methodological Papers, Health Technology Assessment Review Database, <i>Research Synthesis Methods</i>, and <i>Journal of the Royal Statistical Society</i> covering publications from 1946 to June 2024. We included studies published in English that addressed any methodological guidance and essential statistical and software requirements for IPD-MA. Data extraction focused on study characteristics, domain of the review process, and the specific recommendations. Risk of bias was assessed using resources relevant to the study design. A thematic synthesis was performed to group recurring themes into domains. For each domain, signalling questions were generated to develop a preliminary checklist for assessment and refinement in a 2-round e-Delphi survey involving international IPD-MA experts. <h4>Results</h4> The literature search yielded 13,589 citations. After screening 9436 unique abstracts and reviewing 286 full texts, we included 130 articles that met our inclusion criteria. These articles consisted of narrative reviews, handbooks, critical reviews, empirical studies, and statistical method articles. They were published between 1995 and 2024, with most originating from the UK (62 [48%]), the US (20 [15%]), and the Netherlands (16 [12%]) and 50 (38%) originating from 10 other countries. Most of these studies had a low risk of bias. We identified 14 domains of guidance for conducting and reporting of IPD-MA, and we categorized them into 5 sections (<b>Table 25-0999</b>). This finding informed the initial version of the checklist to be evaluated in the e-Delphi survey. https://assets.underline.io/markdown_image/1/image/ae40b29d7f5b93606f06cb13df104504.png <h4>Conclusions</h4> There are many recommendations in the literature on the general conduct of IPD-MA and on specific aspects of this research, which would benefit from consensus recommendations for all aspects of IPD-MA and critical appraisal of reports. This review provides many suggestions for these recommendations, and our e-Delphi survey will seek consensus on items to include in the critical appraisal tool, which we expect to be completed in 2025. <sup>1</sup>Department of Epidemiology & Biostatistics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada, eotalike@uwo.ca; <sup>2</sup>Northern Ireland Methodology Hub, Queen’s University Belfast, Northern Ireland, UK; <sup>3</sup>Department of Surgery, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada. <h4>Conflict of Interest Disclosures</h4> Edith Otalike receives internal funding from Western University and the Dean’s Research Scholarship award. No other disclosures were reported. <h4>Additional Information</h4> Joel J. Gagnier is a co–corresponding author (jgagnie4@uwo.ca).
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 | 0,178 | 0,111 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,029 | 0,005 |
| Bibliométrie | 0,008 | 0,053 |
| Études des sciences et des technologies | 0,002 | 0,009 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,036 | 0,017 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,056 | 0,017 |
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 ».