ChatGPT for assessing risk of bias of randomized trials using the RoB 2.0 tool: A methods study

Author:

Pitre TylerORCID,Jassal Tanvir,Talukdar Jhalok Ronjan,Shahab Mahnoor,Ling Michael,Zeraatkar Dena

Abstract

AbstractBackgroundInternationally accepted standards for systematic reviews necessitate assessment of the risk of bias of primary studies. Assessing risk of bias, however, can be time- and resource-intensive. AI-based solutions may increase efficiency and reduce burden.ObjectiveTo evaluate the reliability of ChatGPT for performing risk of bias assessments of randomized trials using the revised risk of bias tool for randomized trials (RoB 2.0).MethodsWe sampled recently published Cochrane systematic reviews of medical interventions (up to October 2023) that included randomized controlled trials and assessed risk of bias using the Cochrane-endorsed revised risk of bias tool for randomized trials (RoB 2.0). From each eligible review, we collected data on the risk of bias assessments for the first three reported outcomes. Using ChatGPT-4, we assessed the risk of bias for the same outcomes using three different prompts: a minimal prompt including limited instructions, a maximal prompt with extensive instructions, and an optimized prompt that was designed to yield the best risk of bias judgements. The agreement between ChatGPT’s assessments and those of Cochrane systematic reviewers was quantified using weighted kappa statistics.ResultsWe included 34 systematic reviews with 157 unique trials. We found the agreement between ChatGPT and systematic review authors for assessment of overall risk of bias to be 0.16 (95% CI: 0.01 to 0.3) for the maximal ChatGPT prompt, 0.17 (95% CI: 0.02 to 0.32) for the optimized prompt, and 0.11 (95% CI: -0.04 to 0.27) for the minimal prompt. For the optimized prompt, agreement ranged between 0.11 (95% CI: -0.11 to 0.33) to 0.29 (95% CI: 0.14 to 0.44) across risk of bias domains, with the lowest agreement for the deviations from the intended intervention domain and the highest agreement for the missing outcome data domain.ConclusionOur results suggest that ChatGPT and systematic reviewers only have “slight” to “fair” agreement in risk of bias judgements for randomized trials. ChatGPT is currently unable to reliably assess risk of bias of randomized trials. We advise against using ChatGPT to perform risk of bias assessments. There may be opportunities to use ChatGPT to streamline other aspects of systematic reviews, such as screening of search records or collection of data.

Publisher

Cold Spring Harbor Laboratory

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