1. Developing and externally validating multinomial prediction models for methotrexate treatment outcomes in patients with rheumatoid arthritis: results from an international collaboration.
- Author
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Gehringer CK, Martin GP, Hyrich KL, Verstappen SMM, Sexton J, Kristianslund EK, Provan SA, Kvien TK, and Sergeant JC
- Subjects
- Humans, Methotrexate therapeutic use, Treatment Outcome, Prognosis, Arthritis, Rheumatoid drug therapy, Antirheumatic Agents therapeutic use
- Abstract
Objectives: In rheumatology, there is a clinical need to identify patients at high risk (>50%) of not responding to the first-line therapy methotrexate (MTX) due to lack of disease control or discontinuation due to adverse events (AEs). Despite this need, previous prediction models in this context are at high risk of bias and ignore AEs. Our objectives were to (i) develop a multinomial model for outcomes of low disease activity and discontinuing due to AEs 6 months after starting MTX, (ii) update prognosis 3-month following treatment initiation, and (iii) externally validate these models., Study Design and Setting: A multinomial model for low disease activity (submodel 1) and discontinuing due to AEs (submodel 2) was developed using data from the UK Rheumatoid Arthritis Medication Study, updated using landmarking analysis, internally validated using bootstrapping, and externally validated in the Norwegian Disease-Modifying Antirheumatic Drug register. Performance was assessed using calibration (calibration-slope and calibration-in-the-large), and discrimination (concordance-statistic and polytomous discriminatory index)., Results: The internally validated model showed good calibration in the development setting with a calibration-slope of 1.01 (0.87, 1.14) (submodel 1) and 0.83 (0.30, 1.34) (submodel 2), and moderate discrimination with a c-statistic of 0.72 (0.69, 0.74) and 0.53 (0.48, 0.59), respectively. Predictive performance decreased after external validation (calibration-slope 0.78 (0.64, 0.93) (submodel 1) and 0.86 (0.34, 1.38) (submodel 2)), which may be due to differences in disease-specific characteristics and outcome prevalence., Conclusion: We addressed previously identified methodological limitations of prediction models for outcomes of MTX therapy. The multinomial approach predicted outcomes of disease activity more accurately than AEs, which should be addressed in future work to aid implementation into clinical practice., Competing Interests: Declaration of competing interest KLH has received speaker honoraria from AbbVie and grant income from BMS and Pfizer. TKK has received fees for speaking from Janssen, Sandoz, Grünenthal, and UCB; fees for consulting from AbbVie, Galapagos, Janssen, Pfizer, and Sandoz; research funding to Diakonhjemmet Hospital from AbbVie, BMS, Novartis, Pfizer, and UCB., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)
- Published
- 2024
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