Nicola Dalbeth1, H Ralph Schumacher2, Jaap Fransen3, Tuhina Neogi4, Tim L Jansen5, Melanie Brown6, Worawit Louthrenoo7, Janitzia Vazquez-Mellado8, Maxim Eliseev9, Geraldine McCarthy10, Lisa K Stamp11, Fernando Perez-Ruiz12, Francisca Sivera13, Hang-Korng Ea14, Martijn Gerritsen15, Carlo A Scire16, Lorenzo Cavagna17, Chingtsai Lin18, Yin-Yi Chou18, Anne-Kathrin Tausche19, Geraldo da Rocha Castelar-Pinheiro20, Matthijs Janssen21, Jiunn-Horng Chen22, Marco A Cimmino23, Till Uhlig24, William J Taylor6. 1. University of Auckland, Auckland, New Zealand. 2. University of Pennsylvania, Philadelphia. 3. Radboud University Medical Centre, Nijmegen, The Netherlands. 4. Boston University School of Medicine, Boston, Massachusetts. 5. Viecuri Medical Center, Venlo, The Netherlands. 6. University of Otago, Wellington, New Zealand. 7. Chiang Mai University, Chiang Mai, Thailand. 8. Hospital General de Mexico, Mexico City, Mexico. 9. Nasonova Research Institute of Rheumatology of Russia, Moscow, Russia. 10. Geraldine McCarthy, MD, FRCPI, University College Dublin School of Medicine and Medical Science, Dublin, Ireland. 11. University of Otago, Christchurch, New Zealand. 12. Hospital Universitario Cruces & BioCruces Health Research Institute, Vizcaya, Spain. 13. Hospital General Universitario de Elda, Alicante, Spain. 14. Université Paris Diderot, Sorbonne Paris Cité, UFR de Médecine, INSERM, UMR 1132, Hôpital Lariboisière, Assistance Publique-Hôpitaux de Paris, and Hôpital Lariboisière, Paris, France. 15. Westfries Gasthuis, Hoorn, The Netherlands. 16. Carlo A. Scire, MD, PhD, Italian Society for Rheumatology, Milan, Italy. 17. University and IRCCS Policlinico S. Matteo Foundation, Pavia, Italy. 18. Taichung Veterans General Hospital, Taichung, Taiwan. 19. University Hospital Carl Gustav Carus, Dresden, Germany. 20. Universidade de Estado do Rio de Janeiro, Rio de Janeiro, Brazil. 21. Rijnstate Hospital, Arnhem, The Netherlands. 22. China Medical University School of Medicine, Taichung, Taiwan. 23. University of Genoa, Genoa, Italy. 24. Diakonhjemmet Hospital, Oslo, Norway.
Abstract
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.
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.
Authors: Ruth K Topless; Amanda Phipps-Green; Megan Leask; Nicola Dalbeth; Lisa K Stamp; Philip C Robinson; Tony R Merriman Journal: ACR Open Rheumatol Date: 2021-04-15
Authors: Ruth K G Topless; Tanya J Major; Joanne B Cole; Tony R Merriman; Jose C Florez; Joel N Hirschhorn; Murray Cadzow; Nicola Dalbeth; Lisa K Stamp; Philip L Wilcox; Richard J Reynolds Journal: Arthritis Res Ther Date: 2021-03-04 Impact factor: 5.156
Authors: Natalie McCormick; Na Lu; Chio Yokose; Amit D Joshi; Shanshan Sheehy; Lynn Rosenberg; Erica T Warner; Nicola Dalbeth; Tony R Merriman; Kenneth G Saag; Yuqing Zhang; Hyon K Choi Journal: JAMA Netw Open Date: 2022-08-01
Authors: Sarah Stewart; Amanda Phipps-Green; Greg D Gamble; Lisa K Stamp; William J Taylor; Tuhina Neogi; Tony R Merriman; Nicola Dalbeth Journal: PLoS One Date: 2022-02-01 Impact factor: 3.240