Defining decision thresholds for judgments on health benefits and harms using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence to Decision (EtD) frameworks: a randomised methodological study (GRADE-THRESHOLD).
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INTRODUCTION: GRADE and other Evidence to Decision (EtD) frameworks are widely used by guideline development groups (GDG) and other decision-makers. When GDGs judge the magnitude of desirable and undesirable health outcomes on EtDs, they typically categorize them as trivial, small, moderate or large. However, generic judgment or decision thresholds (DTs) that could guide the user about such estimates of effect size or serve as references for interpretation of findings are not yet available. The objective of this study was to empirically derive DTs for EtD judgments about the magnitude of dichotomously assessed health benefits and harms. METHODS: We conducted a methodological randomised controlled trial to derive empirical DTs across conditions and health outcomes. We invited stakeholders including clinicians, epidemiologists, decision scientists, health research methodologists, experts in Health Technology Assessment (HTA), members of GDGs, patient representatives, and the public to participate in the trial. We employed randomly assigned case scenarios to elicit ranges of absolute risk differences (ARD) judged as small and moderate effects from study participants. We then used the collected data to derive empirical decision thresholds. We also investigated the validity of our DTs by measuring the agreement between judgments that were made by GDGs in the past and the judgments that our DTs approach would suggest if applied to the same guideline data. RESULTS: A total of 445 stakeholders accessed the survey of which 409 were randomised and 288 rated at least one case scenario. Based on these participants, the study findings support our a priori hypothesis of a difference in the DTs for trivial, small, moderate, and large effects and are suggestive of a relation between raters' judgments and the joint measure of absolute effects and outcome values. The results permit the use and calculation of DTs for a variety of scenarios and we present three ways of how to use the results practically. CONCLUSIONS: In this trial we confirmed that empirically derived DTs discriminate between judgments on the EtDs. These DTs can be used for judgments about desirable and undesirable health effects in systematic reviews or to initiate and inform a discussion with a GDG. This ensures consistency in judgments across different guideline questions and promotes transparency in judgments.
