Frank Eektimmerman1,2, Cornelia F Allaart3, Johanna M Hazes4, Moenira B Madhar1, Alfons A den Broeder5, Jaap Fransen5, Jesse J Swen1,2, Henk-Jan Guchelaar1,2. 1. Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands. 2. Leiden Network for Personalised Therapeutics (LNPT), Leiden, The Netherlands. 3. Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands. 4. Department of Rheumatology, Erasmus Medical Center, Rotterdam, The Netherlands. 5. Department of Rheumatology, Radboud University Medical Center, Nijmegen, The Netherlands.
Abstract
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.
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 RApatients 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 RApatients treated with combination therapies.
Authors: Helen R Gosselt; Ittai B Muller; Gerrit Jansen; Michel van Weeghel; Frédéric M Vaz; Johanna M W Hazes; Sandra G Heil; Robert de Jonge Journal: J Pers Med Date: 2020-12-10
Authors: Jose U Scher; Renuka R Nayak; Carles Ubeda; Peter J Turnbaugh; Steven B Abramson Journal: Nat Rev Rheumatol Date: 2020-03-10 Impact factor: 32.286
Authors: Helen R Gosselt; Maxime M A Verhoeven; Maurits C F J de Rotte; Saskia M F Pluijm; Ittai B Muller; Gerrit Jansen; Janneke Tekstra; Maja Bulatović-Ćalasan; Sandra G Heil; Floris P J G Lafeber; Johanna M W Hazes; Robert de Jonge Journal: Rheumatol Ther Date: 2020-09-14