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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References
Smolen JS, Aletaha D, Bijlsma JW, Breedveld FC, Boumpas D, Burmester G, et al. Treating rheumatoid arthritis to target: recommendations of an international task force. Ann Rheum Dis. 2010;69:631–7.
Smolen JS, Landewe R, Bijlsma J, Burmester G, Chatzidionysiou K, Dougados M, et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2016 update. Ann Rheum Dis. 2017;76:960–77.
Brown PM, Pratt AG, Isaacs JD. Mechanism of action of methotrexate in rheumatoid arthritis, and the search for biomarkers. Nat Rev Rheumatol. 2016;12:731–42.
Romao VC, Canhao H, Fonseca JE. Old drugs, old problems: where do we stand in prediction of rheumatoid arthritis responsiveness to methotrexate and other synthetic DMARDs? BMC Med. 2013;11:17.
Wessels JA, van der Kooij SM, le Cessie S, Kievit W, Barerra P, Allaart CF, et al. A clinical pharmacogenetic model to predict the efficacy of methotrexate monotherapy in recent-onset rheumatoid arthritis. Arthritis Rheum. 2007;56:1765–75.
Fransen J, Kooloos WM, Wessels JA, Huizinga TW, Guchelaar HJ, van Riel PL, et al. Clinical pharmacogenetic model to predict response of MTX monotherapy in patients with established rheumatoid arthritis after DMARD failure. Pharmacogenomics. 2012;13:1087–94.
Owen SA, Lunt M, Hider SL, Bruce IN, Barton A, Thomson W. Testing pharmacogenetic indices to predict efficacy and toxicity of methotrexate monotherapy in a rheumatoid arthritis patient cohort. Arthritis Rheum. 2010;62:3827–9.
Chen Y, Zou K, Sun J, Yang Y, Liu G. Are gene polymorphisms related to treatment outcomes of methotrexate in patients with rheumatoid arthritis? A systematic review and meta-analysis. Pharmacogenomics. 2017;18:175–95.
Qiu Q, Huang J, Shu X, Fan H, Zhou Y, Xiao C. Polymorphisms and pharmacogenomics for the clinical efficacy of methotrexate in patients with rheumatoid arthritis: a systematic review and meta-analysis. Sci Rep. 2017;7:44015.
IGSR: The International Genome Sample Resource. 2017 http://www.internationalgenome.org/home
van Gestel AM, Haagsma CJ, van Riel PL. Validation of rheumatoid arthritis improvement criteria that include simplified joint counts. Arthritis Rheum. 1998;41:1845–50.
Braun J, Kastner P, Flaxenberg P, Wahrisch J, Hanke P, Demary W, et al. Comparison of the clinical efficacy and safety of subcutaneous versus oral administration of methotrexate in patients with active rheumatoid arthritis: results of a six-month, multicenter, randomized, double-blind, controlled, phase IV trial. Arthritis Rheum. 2008;58:73–81.
Barrera P, van der Maas A, van Ede AE, Kiemeney BA, Laan RF, van de Putte LB, et al. Drug survival, efficacy and toxicity of monotherapy with a fully human anti-tumour necrosis factor-alpha antibody compared with methotrexate in long-standing rheumatoid arthritis. Rheumatology. 2002;41:430–9.
van Ede AE, Laan RF, Rood MJ, Huizinga TW, van de Laar MA, van Denderen CJ, et al. Effect of folic or folinic acid supplementation on the toxicity and efficacy of methotrexate in rheumatoid arthritis: a forty-eight week, multicenter, randomized, double-blind, placebo-controlled study. Arthritis Rheum. 2001;44:1515–24.
Detert J, Bastian H, Listing J, Weiss A, Wassenberg S, Liebhaber A, et al. Induction therapy with adalimumab plus methotrexate for 24 weeks followed by methotrexate monotherapy up to week 48 versus methotrexate therapy alone for DMARD-naive patients with early rheumatoid arthritis: HIT HARD, an investigator-initiated study. Ann Rheum Dis. 2013;72:844–50.
O’Dell JR, Curtis JR, Mikuls TR, Cofield SS, Bridges SL Jr., Ranganath VK, et al. Validation of the methotrexate-first strategy in patients with early, poor-prognosis rheumatoid arthritis: results from a two-year randomized, double-blind trial. Arthritis Rheum. 2013;65:1985–94.
Bijlsma JWJ, Welsing PMJ, Woodworth TG, Middelink LM, Petho-Schramm A, Bernasconi C, et al. Early rheumatoid arthritis treated with tocilizumab, methotrexate, or their combination (U-Act-Early): a multicentre, randomised, double-blind, double-dummy, strategy trial. Lancet. 2016;388:343–55.
Singh JA, Furst DE, Bharat A, Curtis JR, Kavanaugh AF, Kremer JM, et al. 2012 update of the 2008 American College of Rheumatology recommendations for the use of disease-modifying antirheumatic drugs and biologic agents in the treatment of rheumatoid arthritis. Arthritis Care Res. 2012;64:625–39.
Albrecht K, Zink A. Poor prognostic factors guiding treatment decisions in rheumatoid arthritis patients: a review of data from randomized clinical trials and cohort studies. Arthritis Res Ther. 2017;19:68.
Bykerk VP, Akhavan P, Hazlewood GS, Schieir O, Dooley A, Haraoui B, et al. Canadian Rheumatology Association recommendations for pharmacological management of rheumatoid arthritis with traditional and biologic disease-modifying antirheumatic drugs. J Rheumatol. 2012;39:1559–82.
Singh JA, Saag KG, Bridges SL Jr., Akl EA, Bannuru RR, Sullivan MC, et al. 2015 American College of Rheumatology guideline for the treatment of rheumatoid arthritis. Arthritis Rheumatol. 2016;68:1–26.
National Institute for Health and Clinical Excellence. The management of rheumatoid arthritis in adults (Clinical guideline 79). London: NICE; 2009. www.nice.org.uk/CG79.
Guidelines and Protocols Advisory Committee of British Columbia. Rheumatoid Arthritis - Diagnosis, Management and Monitoring, 2012. https://www2.gov.bc.ca/gov/content/health/practitioner-professional-resources/bc-guidelines/rheumatoid-arthritis?keyword=rheumatoid&keyword=arthritis&keyword=medical&keyword=treatment.
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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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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DOI: https://doi.org/10.1038/s41397-018-0017-5
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