Objective: To identify the best-performing survey definition of gout from items commonly available in epidemiologic studies. Methods: Survey definitions of gout were identified from 34 epidemiologic studies contributing to the Global Urate Genetics Consortium (GUGC) genome-wide association study. Data from the Study for Updated Gout Classification Criteria (SUGAR) were randomly divided into development and test data sets. A data-driven case definition was formed using logistic regression in the development data set. This definition, along with definitions used in GUGC studies and the 2015 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) gout classification criteria were applied to the test data set, using monosodium urate crystal identification as the gold standard. Results: For all tested GUGC definitions, the simple definition of “self-report of gout or urate-lowering therapy use” had the best test performance characteristics (sensitivity 82%, specificity 72%). The simple definition had similar performance to a SUGAR data-driven case definition with 5 weighted items: self-report, self-report of doctor diagnosis, colchicine use, urate-lowering therapy use, and hyperuricemia (sensitivity 87%, specificity 70%). Both of these definitions performed better than the 1977 American Rheumatism Association survey criteria (sensitivity 82%, specificity 67%). Of all tested definitions, the 2015 ACR/EULAR criteria had the best performance (sensitivity 92%, specificity 89%). Conclusion: A simple definition of “self-report of gout or urate-lowering therapy use” has the best test performance characteristics of existing definitions that use routinely available data. A more complex combination of features is more sensitive, but still lacks good specificity. If a more accurate case definition is required for a particular study, the 2015 ACR/EULAR gout classification criteria should be considered.
ASJC Scopus subject areas