TY - JOUR
T1 - Study for Updated Gout Classification Criteria
T2 - Identification of Features to Classify Gout
AU - Taylor, William J
AU - Fransen, Jaap
AU - Jansen, Tim L
AU - Dalbeth, Nicola
AU - Schumacher, H Ralph
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
AU - Cavagna, Lorenzo
AU - Lin, Chingtsai
AU - Chou, Yin-Yi
AU - Tausche, Anne Kathrin
AU - Vargas-Santos, Ana Beatriz
AU - Janssen, Matthijs
AU - Chen, Jiunn-Horng
AU - Slot, Ole
AU - Cimmino, Marco A
AU - Uhlig, Till
AU - Neogi, Tuhina
N1 - COPECARE
PY - 2015/9
Y1 - 2015/9
N2 - OBJECTIVE: To determine which clinical, laboratory, and imaging features most accurately distinguished gout from non-gout.METHODS: We performed a cross-sectional study of consecutive rheumatology clinic patients with ≥1 swollen joint or subcutaneous tophus. Gout was defined by synovial fluid or tophus aspirate microscopy by certified examiners in all patients. The sample was randomly divided into a model development (two-thirds) and test sample (one-third). Univariate and multivariate association between clinical features and monosodium urate-defined gout was determined using logistic regression modeling. Shrinkage of regression weights was performed to prevent overfitting of the final model. Latent class analysis was conducted to identify patterns of joint involvement.RESULTS: In total, 983 patients were included. Gout was present in 509 (52%). In the development sample (n = 653), the following features were selected for the final model: joint erythema (multivariate odds ratio [OR] 2.13), difficulty walking (multivariate OR 7.34), time to maximal pain <24 hours (multivariate OR 1.32), resolution by 2 weeks (multivariate OR 3.58), tophus (multivariate OR 7.29), first metatarsophalangeal (MTP1) joint ever involved (multivariate OR 2.30), location of currently tender joints in other foot/ankle (multivariate OR 2.28) or MTP1 joint (multivariate OR 2.82), serum urate level >6 mg/dl (0.36 mmoles/liter; multivariate OR 3.35), ultrasound double contour sign (multivariate OR 7.23), and radiograph erosion or cyst (multivariate OR 2.49). The final model performed adequately in the test set, with no evidence of misfit, high discrimination, and predictive ability. MTP1 joint involvement was the most common joint pattern (39.4%) in gout cases.CONCLUSION: Ten key discriminating features have been identified for further evaluation for new gout classification criteria. Ultrasound findings and degree of uricemia add discriminating value, and will significantly contribute to more accurate classification criteria.
AB - OBJECTIVE: To determine which clinical, laboratory, and imaging features most accurately distinguished gout from non-gout.METHODS: We performed a cross-sectional study of consecutive rheumatology clinic patients with ≥1 swollen joint or subcutaneous tophus. Gout was defined by synovial fluid or tophus aspirate microscopy by certified examiners in all patients. The sample was randomly divided into a model development (two-thirds) and test sample (one-third). Univariate and multivariate association between clinical features and monosodium urate-defined gout was determined using logistic regression modeling. Shrinkage of regression weights was performed to prevent overfitting of the final model. Latent class analysis was conducted to identify patterns of joint involvement.RESULTS: In total, 983 patients were included. Gout was present in 509 (52%). In the development sample (n = 653), the following features were selected for the final model: joint erythema (multivariate odds ratio [OR] 2.13), difficulty walking (multivariate OR 7.34), time to maximal pain <24 hours (multivariate OR 1.32), resolution by 2 weeks (multivariate OR 3.58), tophus (multivariate OR 7.29), first metatarsophalangeal (MTP1) joint ever involved (multivariate OR 2.30), location of currently tender joints in other foot/ankle (multivariate OR 2.28) or MTP1 joint (multivariate OR 2.82), serum urate level >6 mg/dl (0.36 mmoles/liter; multivariate OR 3.35), ultrasound double contour sign (multivariate OR 7.23), and radiograph erosion or cyst (multivariate OR 2.49). The final model performed adequately in the test set, with no evidence of misfit, high discrimination, and predictive ability. MTP1 joint involvement was the most common joint pattern (39.4%) in gout cases.CONCLUSION: Ten key discriminating features have been identified for further evaluation for new gout classification criteria. Ultrasound findings and degree of uricemia add discriminating value, and will significantly contribute to more accurate classification criteria.
U2 - 10.1002/acr.22585
DO - 10.1002/acr.22585
M3 - Journal article
C2 - 25777045
SN - 2151-464X
VL - 67
SP - 1304
EP - 1315
JO - Arthritis Care & Research
JF - Arthritis Care & Research
IS - 9
ER -