Practical guidance for using multiple data sources in systematic reviews and meta‐analyses (with examples from the MUDS study). (15th December 2017)

• Record Type: Journal Article
• Authors: Mayo‐Wilson, Evan; Li, Tianjing; Fusco, Nicole; Dickersin, Kay
• Is Part Of: Research synthesis methods. Volume 9:Number 1(2018)
• Page Start: 2
• Page End: 12
• Publication Date: 2017-12-15
• Subjects: meta‐analysis -- multiple data sources -- reporting bias -- risk of bias assessment -- selective outcome reporting; Research -- Methodology -- Periodicals; Research -- Statistical methods -- Periodicals; 507.2
• DOI: 10.1002/jrsm.1277
• Languages: English
• ISSNs: 1759-2879

Abstract

Abstract : Data for individual trials included in systematic reviews may be available in multiple sources. For example, a single trial might be reported in 2 journal articles and 3 conference abstracts. Because of differences across sources, source selection can influence the results of systematic reviews. We used our experience in the Multiple Data Sources in Systematic Reviews (MUDS) study, and evidence from previous studies, to develop practical guidance for using multiple data sources in systematic reviews. We recommend the following: (1) Specify which sources you will use. Before beginning a systematic review, consider which sources are likely to contain the most useful data. Try to identify all relevant reports and to extract information from the most reliable sources. (2) Link individual trials with multiple sources. Write to authors to determine which sources are likely related to the same trials. Use a modified Preferred Reporting Items for Systematic Reviews and Meta‐analyses (PRISMA) flowchart to document both the selection of trials and the selection of sources. (3) Follow a prespecified protocol for extracting trial characteristics from multiple sources. Identify differences among sources, and contact study authors to resolve differences if possible. (4) Prespecify outcomes and results to examine in the review and meta‐analysis. In your protocol, describe how you will handle multiple outcomes within each domain of interest. Look for outcomes using all eligible sources. (5) Identify which data sources were included in the review. Consider whether the results might have been influenced by data sources used. (6) To reduce bias, and to reduce research waste, share the data used in your review.