Journal of clinical epidemiology · 2025
A semi-automated approach facilitated the assessment of the certainty of evidence in a network meta-analysis: Part 1 - Direct comparisons.
СтатьяСравнительное исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Kamso Mohammed Mujaab, Whittle Samuel L, Pardo Jordi Pardo, Buchbinder Rachelle, Wells George, Deardon Rob, Sajobi Tolulope, Tomlinson George, Elliott Jesse, Thomas Jocelyn, Kelly Shannon E, Brignardello-Petersen Romina, Hazlewood Glen S
Аннотация
OBJECTIVES: To implement and evaluate a semi-automated approach to facilitate rating the Grading, Recommendation, Assessment, Development and Evaluation (GRADE) certainty of evidence (CoE) for direct comparisons within two living network meta-analysis.
METHODS: For each of three GRADE domains (study limitations, indirectness, and inconsistency), decision rules were developed and used to generate automated judgments for each domain and the overall certainty. Inputs included risk of bias and indirectness ratings for each study and measures of heterogeneity. Indirectness ratings were made by two independent reviewers and resolved through consensus. With the help of an online tool (customized to our project), two independent raters viewed forest plots and additional data and could confirm or modify the suggested rating. Disagreements were resolved by consensus. We evaluated inter-rater reliability and accuracy.
RESULTS: Across 374 direct comparisons, there was perfect agreement (100%) between the automated judgment and reviewer consensus, when only a single study was available (n = 292), and near-perfect agreement when more than one study was available (99%-100% for the three GRADE domains and 96% for overall rating). Inter-rater reliability was near perfect (Gwet's AC1 kappa score ranging from 96% to 100%).
CONCLUSION: Automated judgments using established decision rules agreed with expert judgment for the vast majority of GRADE CoE ratings.
METHODS: For each of three GRADE domains (study limitations, indirectness, and inconsistency), decision rules were developed and used to generate automated judgments for each domain and the overall certainty. Inputs included risk of bias and indirectness ratings for each study and measures of heterogeneity. Indirectness ratings were made by two independent reviewers and resolved through consensus. With the help of an online tool (customized to our project), two independent raters viewed forest plots and additional data and could confirm or modify the suggested rating. Disagreements were resolved by consensus. We evaluated inter-rater reliability and accuracy.
RESULTS: Across 374 direct comparisons, there was perfect agreement (100%) between the automated judgment and reviewer consensus, when only a single study was available (n = 292), and near-perfect agreement when more than one study was available (99%-100% for the three GRADE domains and 96% for overall rating). Inter-rater reliability was near perfect (Gwet's AC1 kappa score ranging from 96% to 100%).
CONCLUSION: Automated judgments using established decision rules agreed with expert judgment for the vast majority of GRADE CoE ratings.