Choudhary D, Thomas M, Pacheco-Barrios K, Zhang Y, Alonso-Coello P, Schünemann H, Hazlewood G. Methods to Summarize Discrete-Choice Experiments in a Systematic Review: A Scoping Review.
THE PATIENT 2022;
15:629-639. [PMID:
35829927 DOI:
10.1007/s40271-022-00587-7]
[Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/16/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND AND OBJECTIVE
Systematic reviews of discrete-choice experiments (DCEs) are being increasingly conducted. The objective of this scoping review was to identify and describe the methodologies that have been used to summarize results across DCEs.
METHODS
We searched the electronic databases MEDLINE and EMBASE from inception to March 18, 2021, to identify English-language systematic reviews of patient preferences that included at least two DCEs and extracted data on attribute importance. The methods used to summarize results across DCEs were classified into narrative, semi-quantitative, and quantitative (meta-analytic) approaches and compared. Approaches to characterize the extent of preference heterogeneity were also described.
RESULTS
From 7362 unique records, we identified 54 eligible reviews from 2010 to Mar 2021, across a broad range of health conditions. Most (83%) used a narrative approach to summarize findings of DCEs, often citing differences in studies as the reason for not formally pooling findings. Semi-quantitative approaches included summarizing the frequency of the most important attributes, the frequency of attribute statistical significance, or tabulated comparisons of attribute importance for each pair of attributes. One review conducted a meta-analysis using the maximum acceptable risk. While reviews often commented on the heterogeneity of patient preferences, few (6%) addressed this systematically across studies.
CONCLUSION
While not commonly used, several semi-quantitative and one quantitative approach for synthesizing results of DCEs were identified, which may be useful for generating summary estimates across DCEs when appropriate. Further work is needed to assess the validity and usefulness of these approaches.
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