Using GRADE evidence to decision frameworks to choose from multiple interventions

Area of Science:

• Health Economics and Outcomes Research
• Clinical Guideline Development
• Evidence-Based Medicine

Background:

• Health care decision makers often need to compare multiple interventions simultaneously.
• Existing methods may lead to recommendations based on limited pairwise comparisons, missing broader insights.

Purpose of the Study:

• To develop and test a flexible approach for multiple-intervention comparisons (MC) within the Grading of Recommendations Assessment, Development and Evaluation (GRADE) evidence to decision (EtD) frameworks.
• To integrate this MC approach into a software module for practical application in guideline development.

Main Methods:

• Developed a flexible MC approach using GRADE EtD frameworks, drawing on examples from international organizations.
• Refined the approach through user testing and integrated it into the GRADEpro software.
• Tested the approach in real-world and theoretical guideline development scenarios.

Main Results:

• The MC approach was found to be feasible, considering all EtD criteria.
• Network meta-analyses (NMA) support decision-making but are not essential for the proposed MC approach.
• Challenges such as intransitivity and relative intervention rankings were identified when using similar comparators.

Conclusions:

• The developed MC approach and software module successfully support recommendation generation across various scenarios.
• This approach enables transparent and critical assessment of multiple health intervention options.
• Further application and refinement by guideline developers are expected to enhance understanding and impact.