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https://hdl.handle.net/2183/49125 Improved prediction of knee osteoarthritis progression by genetic polymorphisms: the Arthrotest Study
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Möller, Ingrid
Romera, Montserrat
Rozadilla, Antoni
Sánchez-Lázaro, Jaime A.
Rodríguez, Arturo
Gálvez, José
Forés, Joaquim
Monfort, Jordi
Ojeda, Soledad
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Blanco FJ, Möller I, Romera M, Rozadilla A, Sánchez-Lázaro JA, Rodríguez A, Gálvez J, Forés J, Monfort J, Ojeda S, Moragues C, Caracuel MÁ, Clavaguera T, Valdés C, Soler JM, Orellana C, Belmonte MÁ, Martín F, Giménez S, Úcar E, Pous J, Bartolomé N, Artieda M, Szczypiorska M, Tejedor D, Martínez A, Montell E, Martínez H, Herrero M, Vergés J; Arthrotest Study Group. Improved prediction of knee osteoarthritis progression by genetic polymorphisms: the Arthrotest Study. Rheumatology (Oxford). 2015 Jul;54(7):1236-43.
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Abstract
[Abstract] Objective: The aim of this study was to develop a genetic prognostic tool to predict radiographic progression towards severe disease in primary knee OA (KOA) patients.
Methods: This investigation was a cross-sectional, retrospective, multicentric association study in 595 Spanish KOA patients. Caucasian patients aged ≥40 years at the time of diagnosis of primary KOA of Kellgren-Lawrence grade 2 or 3 were included. Patients who progressed to Kellgren-Lawrence score 4 or who were referred for total knee replacement within 8 years after diagnosis were classified as progressors to severe disease. Clinical variables of the initial stages of the disease (gender, BMI, age at diagnosis, OA in the contralateral knee, and OA in other joints) were registered as potential predictors. Single nucleotide polymorphisms and clinical variables with an association of P < 0.05 were included in the multivariate analysis using forward logistic regression.
Results: A total of 23 single nucleotide polymorphisms and the time of primary KOA diagnosis were significantly associated with KOA severe progression in the exploratory cohort (n = 220; P < 0.05). The predictive accuracy of the clinical variables was limited: area under the curve (AUC) = 0.66. When genetic variables were added to the clinical model (full model), the prediction of KOA progression was significantly improved (AUC = 0.82). Combining only genetic variables (rs2073508, rs10845493, rs2206593, rs10519263, rs874692, rs7342880, rs780094 and rs12009), a predictive model with good accuracy was also obtained (AUC = 0.78). The predictive ability for KOA progression of the full model was confirmed on the replication cohort (two-sample Z-test; n = 62; P = 0.190).
Conclusion: An accurate prognostic tool to predict primary KOA progression has been developed based on genetic and clinical information from OA patients.
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Multicenter study
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This is a pre-copyedited, author-produced version of an article accepted for publication in Rheumatology (United Kingdom)following peer review. The version of record is available online on the OUP website.






