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Enregistrement W4321163600 · doi:10.1097/js9.0000000000000114

Should the reporting certainty of evidence for meta-analysis of observational studies using GRADE be revisited?

2023· article· en· W4321163600 sur OpenAlexaboutno aff
Mahmoud Yousefifard, Arman Shafiee

Notice bibliographique

RevueInternational Journal of Surgery · 2023
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueMeta-analysis and systematic reviews
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésObservational studyGrading (engineering)Systematic reviewMedicineCertaintyGuidelineMeta-analysisEvidence-based medicineMEDLINEPsychological interventionCritical appraisalMedical physicsAlternative medicinePathologyPsychiatry

Résumé

récupéré en direct d'OpenAlex

Highlights Assessing the certainty of results is an inevitable part of systematic reviews. Grading of Recommendations Assessment, Development, and Evaluation is a widely used tool for assessing certainty of evidence. Using Grading of Recommendations Assessment, Development, and Evaluation for observational studies meta-analyses is accompanied by limitations. Dear Editor, It is evident in the literature that aside from reporting the synthesis from the predefined questions, one must be aware of the validity and reliability of their estimates. Reporting the level of evidence will guide policymakers and practitioners to apply evidence in routine practice. In 2004, The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) working group developed an approach for systematic reviews to provide transparent information on the certainty of evidence. The approach was initially designed to address the effectiveness of interventions in systematic reviews. However, it has been widely used by researchers as an evidence-ranking scheme to assess the certainty of the evidence of all types of systematic reviews, including prognostic, diagnostic, and prevalence studies. In our experience, the journal reviewers and editors suggested reporting the certainty of the evidence for prognostic/diagnostic systematic reviews using the GRADE guideline. However, applying the GRADE guideline for the rating of the prognostic/diagnostic systematic reviews have important limitations. Here, we will address some issues regarding using this approach in systematic reviews and meta-analyses of observational studies. The GRADE approach has four levels of evidence: very low, low, moderate, and high. Eight GRADE criteria must be evaluated to report the certainty of each synthesized outcome. Among them, five decreases the grade of evidence (risk of bias, imprecision, inconsistency, indirectness, and publication bias)1. In the case of methodologically robust observational research, GRADE advises raising the quality of the evidence (large magnitude of effect, dose-response gradient, and all plausible residual confounding). Most of the published systematic reviews have stated they reported their study in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline2. According to PRISMA guideline, authors must specify how they assess certainty (or confidence) in the body of evidence for an outcome. The GRADE approach suggests evidence from randomized clinical trials must begin with a high level, while evidence based on observational studies starts with a low level. Therefore, it seems that researchers of meta-analyses of observational studies might not be as eager to utilize this method to assess the certainty of evidence because the quality of a meta-analysis of an observational study will be mostly judged as low or very low. In addition, in the latest revision of GRADE guideline, the risk of bias assessment may cause rating down of evidence three levels3. For example, O’Keeffe et al.4 published a meta-analysis on the relation of smoking and risk of lung cancer in 2018. In this well-written systematic review, a high risk of bias was observed according to the Newcastle–Ottawa scale, and there was also considerable heterogeneity (89.4–98.8%). According to the GRADE guideline, the certainty of the evidence is rated down five levels: three points due to an extremely serious risk of bias and two points due to very serious heterogeneity. As well, we can rate up the level of evidence two to three levels since there was a large magnitude of effect and potential dose-response gradients (increasing the risk of cancer with increasing the number of cigarettes per day). As a conclusion, the overall certainty of evidence for the relationship between smoking and lung cancer derived from the O’Keeffe and colleagues study is ‘low to very low.’ Therefore, based on the definitions given by the GRADE, this relationship will probably be markedly different from the actual estimated effect. While there is a global consensus on the independent hazardous effect of smoking on the increasing risk of lung cancer. Although randomized clinical trials provide a higher level of evidence than observational studies to assess the safety and efficacy of intervention, in the assessment of the diagnostic/prognostic value of an indicator, observational studies can provide the optimum evidence available5. Furthermore, based on the Centre for Evidence-Based Medicine (CEBM) recommendation, systematic reviews of observational studies evaluated to address prognosis, diagnosis, and prevalence of a predefined question are among the studies with the highest levels of evidence. In conclusion, it seems that the prespecified low rating of the quality of evidence derived from observational studies proposed by the GRADE may lead to an excessive decrease in the quality of evidence, and most of the authors of meta-analyses of observational studies tend not to report the certainty of evidence throughout their manuscript. In addition, rating down of certainty three levels for application of new risk of bias tools such as ROBINS-I may not applicable for systematic review of observational studies. We propose to define a new approach for rating the level of evidence in such a way that the rating for systematic reviews of observational studies is designed based on the CEBM guideline. For example, the CEBM suggests the level of evidence provided by well-designed cohort studies and cross-sectional studies to investigate the prognostic and diagnostic value of an indicator is ‘high.’ Therefore, if a systematic review of well-designed cross-sectional studies is conducted to assess the diagnostic value of an indicator, it is better to start rating its certainty from high-quality evidence. Moreover, ‘extremely serious’ risk of bias due to using the new risk of bias tools should be apply only in systematic reviews of treatment effect. Ethical approval Not applicable. Sources of funding None. Author contribution M.Y. contributed to conception of the manuscript, drafted the manuscript, circulated for review, and revised the final manuscript. A.S. drafted the manuscript, circulated for review, and revised the final manuscript. Conflict of interest disclosure The authors declare that they have no financial conflict of interest with regard to the content of this report. Research registration unique identifying number (UIN) None. Guarantor Mahmoud Yousefifard and Arman Shafiee. Data statement None.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,236
score de la tête « metaresearch » (Gemma)0,351
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens large), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesMétarecherche
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Méta-analyse · Signal consensuel: Méta-analyse
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,140
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,2360,351
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0060,013
Bibliométrie0,0020,003
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,995
Tête enseignante GPT0,715
Écart entre enseignants0,280 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeMéta-analyse
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations21
Publié2023
Routes d'admission1
Résumé présentoui

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Même revueInternational Journal of SurgeryMême sujetMeta-analysis and systematic reviewsTravaux en français237 207