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Evaluation of a clinical pharmacogenetics model to predict methotrexate response in patients with rheumatoid arthritis

The Pharmacogenomics Journal volume 18, pages 539–545 (2018)Cite this article

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Abstract

Variability of response to treatment hinders successful management of rheumatoid arthritis (RA). Consequently, a clinical pharmacogenetics model for predicting response to methotrexate (CP-MTX) has been previously proposed that includes four clinical variables (disease activity, sex, the presence of rheumatoid factor and smoking status) and four SNPs (rs2236225, rs17602729, rs1127354, and rs2372536) in genes of the folate pathway. It showed good performance, but failed to attract attention, likely, in relation with lack of clear clinical benefit. Here, we have revised the value of the CP-MTX model directly addressing its clinical benefit by focusing on the expected benefit-cost of the predictions. In addition, our study included a much larger number of RA patients (n = 720) in MTX monotherapy than previous studies. Benefit of CP-MTX prediction was defined as the patients that would have received combination therapy as first treatment because they were correctly predicted as non-responders to MTX monotherapy. In contrast, cost of CP-MTX prediction was defined as the responder patients that were wrongly predicted as non-responders. Application of CP-MTX predictions to our patients showed a good benefit-cost relationship, with half of the 66.7% non-responders to MTX monotherapy rightly directed to alternative treatments (a benefit of 33.3%) at the cost of 8.5% wrongly predicted non-responders. These benefits-costs were consistent with reanalysis of the previously published studies. Therefore, predictions of CP-MTX showed a good benefit-cost relationship for informing MTX prescription.

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Acknowledgements

We are indebted to the patients that generously have contributed the samples and time to this work. We thank Carmen Pena for her excellent technical support. This work was supported by the Instituto de Salud Carlos III (Spain) through grants (PI14/01651 and RD16/0012/0014 to AG). These grants are partially financed by the European Regional Development Fund of the EU (FEDER). RL-R was supported by Instituto de Salud Carlos III (Spain) through a Postdoctoral Contract “Sara Borrell” (CD14/00186).

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Authors and Affiliations

  1. Experimental and Observational Rheumatology and Rheumatology Unit. Instituto de Investigación Sanitaria, Hospital Clínico Universitario de Santiago, Santiago de Compostela, Spain

    Rosario López-Rodríguez, Aida Ferreiro-Iglesias, Eva Pérez-Pampín, Antonio Mera-Varela, Laura Vidal-Bralo, José Gorgonio Acuña-Ochoa, Carmen Conde & Antonio Gonzalez

  2. CESPU, Institute of Research & Advanced Training in Health Sciences & Technologies, Drug Discovery, Delivery & Toxicology Group, Gandra PRD, Portugal

    Aurea Lima

  3. Molecular Oncology & Viral Pathology Group - Research Center, Portuguese Institute of Oncology of Porto, Porto, Portugal

    Aurea Lima

  4. Faculty of Medicine, University of Porto, Porto, Portugal

    Miguel Bernardes

  5. Rheumatology Department, São João Hospital Center, Porto, Portugal

    Miguel Bernardes

  6. Department of Physiology, Pomeranian Medical University Szczecin, Szczecin, Poland

    Andrzej Pawlik

  7. Department of Biochemistry and Molecular Biology, National Institute of Geriatrics, Rheumatology and Rehabilitation, Warsaw, Poland

    Agnieszka Paradowska‑Gorycka

  8. Department of Rheumatology, Wroclaw Medical University, Wrocław, Poland

    Jerzy Świerkot

  9. Department of Genetics, Medical University of Wroclaw, Wrocław, Poland

    Ryszard Slezak

  10. Rheumatology Department, Instituto de Investigacion del Hospital de La Princesa (IIS-IP), Madrid, Spain

    Isidoro Gonzalez-Alvaro

  11. Department of Rheumatology, Hospital Universitario de Bellvitge-IDIBELL, Barcelona, Spain

    Javier Narvaez

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  1. Rosario López-Rodríguez
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Correspondence to Antonio Gonzalez.

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López-Rodríguez, R., Ferreiro-Iglesias, A., Lima, A. et al. Evaluation of a clinical pharmacogenetics model to predict methotrexate response in patients with rheumatoid arthritis. Pharmacogenomics J 18, 539–545 (2018). https://doi.org/10.1038/s41397-018-0017-5

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