Survey revealed a lack of clarity about recommended methods for meta-analysis of diagnostic accuracy data

Abstract

ObjectivesTo collect reasons for selecting the methods for meta-analysis of diagnostic accuracy from authors of systematic reviews and improve guidance on recommended methods. Study Design and SettingOnline survey in authors of recently published meta-analyses of diagnostic accuracy. ResultsWe identified 100 eligible reviews, of which 40 had used more advanced methods of meta-analysis (hierarchical random-effects approach), 52 more traditional methods (summary receiver operating characteristic curve based on linear regression or a univariate approach), and 8 combined both. Fifty-nine authors responded to the survey; 29 (49%) authors had used advanced methods, 25 (42%) authors traditional methods, and 5 (9%) authors combined traditional and advanced methods. Most authors who had used advanced methods reported to do so because they believed that these methods are currently recommended (n = 27; 93%). Most authors who had used traditional methods also reported to do so because they believed that these methods are currently recommended (n = 18; 75%) or easy to understand (n = 18; 75%). ConclusionAlthough more advanced methods for meta-analysis are recommended by The Cochrane Collaboration, both authors using these methods and those using more traditional methods responded that the methods they used were currently recommended. Clearer and more widespread dissemination of guidelines on recommended methods for meta-analysis of test accuracy data is needed.