Aim: To study the performance of a clinical pharmacogenetic model for the prediction of nonresponse in rheumatoid arthritis (RA) patients treated with methotrexate (MTX) in combination with other synthetic or biologic disease-modifying anti-rheumatic drugs . This prediction model includes gender, smoking status, rheumatoid factor positivity and four genetic variants in AMPD1 (rs17602729), ATIC (rs2372536), ITPA (rs1127354) and MTHFD1 (rs17850560).
Methods: A total of 314 RA patients from three Dutch studies were retrospectively included. Eligible patients were adults diagnosed with RA and had a treatment duration with MTX and follow-up for at least two study evaluation visits. Prediction model risk scores at the first and second evaluation were calculated and compared with the actual nonresponse (disease activity score >2.4). Regression and receiver operating characteristic curve analyses of the prediction model were performed. Also, the sensitivity, specificity and the positive and negative predictive values (PPV and NPV) were determined.
Results: The receiver operating characteristic area under the curve was 75% at first and 70% after second evaluation. At the second evaluation, prediction nonresponse had a sensitivity of 67% (CI: 54–78%), specificity of 69% (CI: 60–77%), PPV of 52% (CI: 45–60%) and NPV of 80% (CI: 73–85%).
Conclusions: This study demonstrates that the clinical pharmacogenetic model has an inadequate performance for the prediction of nonresponse to MTX in RA patients treated with combination therapies.

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Keywords effectiveness of therapy, methotrexate, pharmacogenetic models, prediction model, rheumatoid arthritis
Persistent URL dx.doi.org/10.2217/pgs-2018-0144, hdl.handle.net/1765/115209
Journal Pharmacogenomics
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Citation
F. Eektimmerman (Frank), Allaart, C.F, Hazes, J.M.W, den Broeder, A.A, J. Fransen (Jaap), Swen, J.J, & Guchelaar, H.J. (2019). Validation of a clinical pharmacogenetic model to predict methotrexate nonresponse in rheumatoid arthritis patients. Pharmacogenomics, 20(2), 85–93. doi:10.2217/pgs-2018-0144