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DC Field | Value | Language |
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dc.contributor.author | Nicola Dalbeth | en_US |
dc.contributor.author | H. Ralph Schumacher | en_US |
dc.contributor.author | Jaap Fransen | en_US |
dc.contributor.author | Tuhina Neogi | en_US |
dc.contributor.author | Tim L. Jansen | en_US |
dc.contributor.author | Melanie Brown | en_US |
dc.contributor.author | Worawit Louthrenoo | en_US |
dc.contributor.author | Janitzia Vazquez-Mellado | en_US |
dc.contributor.author | Maxim Eliseev | en_US |
dc.contributor.author | Geraldine McCarthy | en_US |
dc.contributor.author | Lisa K. Stamp | en_US |
dc.contributor.author | Fernando Perez-Ruiz | en_US |
dc.contributor.author | Francisca Sivera | en_US |
dc.contributor.author | Hang Korng Ea | en_US |
dc.contributor.author | Martijn Gerritsen | en_US |
dc.contributor.author | Carlo A. Scire | en_US |
dc.contributor.author | Lorenzo Cavagna | en_US |
dc.contributor.author | Chingtsai Lin | en_US |
dc.contributor.author | Yin Yi Chou | en_US |
dc.contributor.author | Anne Kathrin Tausche | en_US |
dc.contributor.author | Geraldo da Rocha Castelar-Pinheiro | en_US |
dc.contributor.author | Matthijs Janssen | en_US |
dc.contributor.author | Jiunn Horng Chen | en_US |
dc.contributor.author | Marco A. Cimmino | en_US |
dc.contributor.author | Till Uhlig | en_US |
dc.contributor.author | William J. Taylor | en_US |
dc.date.accessioned | 2018-09-05T03:07:41Z | - |
dc.date.available | 2018-09-05T03:07:41Z | - |
dc.date.issued | 2016-12-01 | en_US |
dc.identifier.issn | 21514658 | en_US |
dc.identifier.issn | 2151464X | en_US |
dc.identifier.other | 2-s2.0-84997078109 | en_US |
dc.identifier.other | 10.1002/acr.22896 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84997078109&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/56008 | - |
dc.description.abstract | © 2016, American College of Rheumatology 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. | en_US |
dc.subject | Medicine | en_US |
dc.title | Survey Definitions of Gout for Epidemiologic Studies: Comparison With Crystal Identification as the Gold Standard | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | Arthritis Care and Research | en_US |
article.volume | 68 | en_US |
article.stream.affiliations | University of Auckland | en_US |
article.stream.affiliations | University of Pennsylvania | en_US |
article.stream.affiliations | Radboud University Nijmegen Medical Centre | en_US |
article.stream.affiliations | Boston University School of Medicine | en_US |
article.stream.affiliations | VieCuri Medisch Centrum voor Noord-Limburg | en_US |
article.stream.affiliations | University of Otago | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
article.stream.affiliations | Hospital General de Mexico | en_US |
article.stream.affiliations | V.A. Nasonova Research Institute of Rheumatology | en_US |
article.stream.affiliations | University College Dublin, School of Medicine | en_US |
article.stream.affiliations | Hospital Universitario Cruces and BioCruces Health Research Institute | en_US |
article.stream.affiliations | Hospital General Universitario de Alicante | en_US |
article.stream.affiliations | Universite Paris 7- Denis Diderot | en_US |
article.stream.affiliations | Westfriesgasthuis | en_US |
article.stream.affiliations | Italian Society for Rheumatology | en_US |
article.stream.affiliations | Fondazione IRCCS Policlinico San Matteo | en_US |
article.stream.affiliations | Veterans General Hospital-Taichung Taiwan | en_US |
article.stream.affiliations | Dresden University Faculty of Medicine and University Hospital Carl Gustav Carus | en_US |
article.stream.affiliations | Universidade de Estado do Rio de Janeiro | en_US |
article.stream.affiliations | Rijnstate Hospital | en_US |
article.stream.affiliations | China Medical University Taichung | en_US |
article.stream.affiliations | Universita degli Studi di Genova | en_US |
article.stream.affiliations | Diakonhjemmet Sykehus | en_US |
Appears in Collections: | CMUL: Journal Articles |
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