Genetic and clinical prediction models for the efficacy and hepatotoxicity of methotrexate in patients with rheumatoid arthritis: a multicenter cohort study

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Abstract

The objective of the study is to develop genetic and clinical prediction models for the efficacy and hepatotoxicity of methotrexate (MTX) in patients with rheumatoid arthritis (RA). Among RA patients treated with MTX, 1966 polymorphisms of 246 enzymes/transporters relevant to pharmacokinetics and pharmacodynamics were measured by the Drug Metabolism Enzymes and Transporters (DMET) microarray and direct sequencing, and clinical variables at baseline were collected. For efficacy, response criteria of the European League Against Rheumatism were used to classify patients as responders or non-responders. Hepatotoxicity was defined as elevations of aspartate aminotransferase or alanine aminotransferase ≥1.5 times the reference range upper limit. Among 166 patients, a genetic prediction model for efficacy using seven polymorphisms showed the area under the receiver operating characteristic curve (AUC) was 0.822, with 74.3% sensitivity and 76.8% specificity. A combined genetic and clinical model indicated the AUC was 0.844, with 81.5% sensitivity and 76.9% specificity. By incorporating clinical variables into the genetic model, the overall category-free net reclassification improvement (NRI) was 0.663 (P < 0.0001) and the overall integrated discrimination improvement (IDI) was 0.083 (P = 0.0009). For hepatotoxicity, a genetic prediction model using seven polymorphisms showed the AUC was 0.783 with 70.0% sensitivity and 80.0% specificity, while the combined model indicated the AUC was 0.906 with 85.1% sensitivity and 87.8% specificity (overall category-free NRI: 1.002, P < 0.0001; overall IDI: 0.254, P < 0.0001). Our genetic and clinical models demonstrated moderate diagnostic accuracy for MTX efficacy and high accuracy for hepatotoxicity. These findings should, however, be validated and interpreted with a caution until external validation.

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Fig. 1: Flowchart illustrating the development of the prediction models for methotrexate efficacy and hepatotoxicity.
Fig. 2: Receiver operation curves for the prediction models.
Fig. 3: Decision curves for the prediction models.

Data availablility

Allele frequencies are available in https://humandbs.biosciencedbc.jp/.

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Acknowledgements

The DMET plus microarray measurement, direct sequencing, and statistical analyses were partly supported by Sysmex Corporation under the Collaborative Research Agreement.

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Correspondence to Akira Onishi.

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Onishi, A., Kamitsuji, S., Nishida, M. et al. Genetic and clinical prediction models for the efficacy and hepatotoxicity of methotrexate in patients with rheumatoid arthritis: a multicenter cohort study. Pharmacogenomics J (2019) doi:10.1038/s41397-019-0134-9

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