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.
| Original language | English |
|---|---|
| Pages (from-to) | 1894-1898 |
| Number of pages | 5 |
| Journal | Arthritis Care and Research |
| Volume | 68 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - Dec 1 2016 |
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ASJC Scopus subject areas
- Rheumatology
Cite this
Survey Definitions of Gout for Epidemiologic Studies : Comparison With Crystal Identification as the Gold Standard. / Dalbeth, Nicola; Schumacher, H. Ralph; Fransen, Jaap; Neogi, Tuhina; Jansen, Tim L.; Brown, Melanie; Louthrenoo, Worawit; Vazquez-Mellado, Janitzia; Eliseev, Maxim; McCarthy, Geraldine; Stamp, Lisa K.; Perez-Ruiz, Fernando; Sivera, Francisca; Ea, Hang Korng; Gerritsen, Martijn; Scire, Carlo A.; Cavagna, Lorenzo; Lin, Chingtsai; Chou, Yin Yi; Tausche, Anne Kathrin; da Rocha Castelar-Pinheiro, Geraldo; Janssen, Matthijs; Chen, Jiunn Horng; Cimmino, Marco A.; Uhlig, Till; Taylor, William J.
In: Arthritis Care and Research, Vol. 68, No. 12, 01.12.2016, p. 1894-1898.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Survey Definitions of Gout for Epidemiologic Studies
T2 - Comparison With Crystal Identification as the Gold Standard
AU - Dalbeth, Nicola
AU - Schumacher, H. Ralph
AU - Fransen, Jaap
AU - Neogi, Tuhina
AU - Jansen, Tim L.
AU - Brown, Melanie
AU - Louthrenoo, Worawit
AU - Vazquez-Mellado, Janitzia
AU - Eliseev, Maxim
AU - McCarthy, Geraldine
AU - Stamp, Lisa K.
AU - Perez-Ruiz, Fernando
AU - Sivera, Francisca
AU - Ea, Hang Korng
AU - Gerritsen, Martijn
AU - Scire, Carlo A.
AU - Cavagna, Lorenzo
AU - Lin, Chingtsai
AU - Chou, Yin Yi
AU - Tausche, Anne Kathrin
AU - da Rocha Castelar-Pinheiro, Geraldo
AU - Janssen, Matthijs
AU - Chen, Jiunn Horng
AU - Cimmino, Marco A.
AU - Uhlig, Till
AU - Taylor, William J.
PY - 2016/12/1
Y1 - 2016/12/1
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=84997078109&partnerID=8YFLogxK
U2 - 10.1002/acr.22896
DO - 10.1002/acr.22896
M3 - Article
VL - 68
SP - 1894
EP - 1898
JO - Arthritis care and research : the official journal of the Arthritis Health Professions Association
JF - Arthritis care and research : the official journal of the Arthritis Health Professions Association
SN - 0893-7524
IS - 12
ER -