Characteristics and methodological standards across systematic reviews with Meta-analysis of efficacy and/or effectiveness of influenza vaccines: an overview of reviews
Notice bibliographique
Résumé
While systematic reviews (SR) generally suggest that vaccination is an effective way to prevent influenza infection, it is not clear if these conclusions are based on high quality SR methods. As such, we systematically identified, critically appraised, and summarised the characteristics and adherence to methodological standards in SRs with meta-analysis of efficacy/effectiveness of influenza vaccines. We searched MEDLINE, Embase, Scopus, CINAHL, Global Health, and CDSR for English-language SR publications up to July 11, 2022. We summarised the characteristics, adherence to methodological standards and SR quality (AMSTAR 2). From 11,193 retrieved citations, we included 48 publications (47 SRs). Seventy-five percent were of a critically low quality, 19% of a low quality, 2% of a moderate quality, and 4% of a high quality. Thirteen percent were industry-funded, about 13% co-authored by industry employee(s), and 4% commissioned by an organisation or authority. Only 45% percent reported protocol registration, 6% reported collaboration with a knowledge synthesis librarian/information specialist, and 60% utilised a reporting checklist (e.g. PRISMA). SRs with meta-analysis of efficacy/effectiveness of influenza vaccines are mostly of critically low quality and even the more recent reviews did not follow current best SR practices. These findings are significant in view of the controversies that surround influenza vaccines, and the use of SRs in informed decision-making. However, the findings do not justify curtailment or cessation of influenza vaccine use as vaccines continue to offer substantial net public health benefit.HighlightsWe systematically identified, critically appraised, and summarised the characteristics and adherence to methodological standards in 47 systematic reviews with meta-analysis of efficacy/effectiveness of influenza vaccines.13% of the reviews were industry-funded.About 13% of the reviews were co-authored by industry employee(s).4% of the reviews were commissioned by an organisation/authority.45% of the reviews reported protocol registration.6% of the reviews reported collaborating with a knowledge synthesis librarian/information specialist to prepare the search strategy.60% of the reviews reported using the PRISMA (or similar) checklist.75% of the reviews were judged to be of critically low quality; 19% of low quality; 2% of moderate quality; 4% of high quality. We systematically identified, critically appraised, and summarised the characteristics and adherence to methodological standards in 47 systematic reviews with meta-analysis of efficacy/effectiveness of influenza vaccines. 13% of the reviews were industry-funded. About 13% of the reviews were co-authored by industry employee(s). 4% of the reviews were commissioned by an organisation/authority. 45% of the reviews reported protocol registration. 6% of the reviews reported collaborating with a knowledge synthesis librarian/information specialist to prepare the search strategy. 60% of the reviews reported using the PRISMA (or similar) checklist. 75% of the reviews were judged to be of critically low quality; 19% of low quality; 2% of moderate quality; 4% of high quality.
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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 | 0,432 | 0,750 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,004 |
| Méta-épidémiologie (sens large) | 0,014 | 0,021 |
| Bibliométrie | 0,042 | 0,052 |
| Études des sciences et des technologies | 0,003 | 0,005 |
| Communication savante | 0,012 | 0,009 |
| Science ouverte | 0,006 | 0,009 |
| Intégrité de la recherche | 0,006 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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; 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 ».