Predicting response to tocilizumab monotherapy in rheumatoid arthritis: A real-world data analysis using machine learning
Journal article, 2021

Objective. Tocilizumab (TCZ) has shown similar efficacy when used as monotherapy as in combination with other treatments for rheumatoid arthritis (RA) in randomized controlled trials (RCTs). We derived a remission prediction score for TCZ monotherapy (TCZm) using RCT data and performed an external validation of the prediction score using real-world data (RWD). Methods. We identified patients in the Corrona RA registry who used TCZm (n = 452), and matched the design and patients from 4 RCTs used in previous work (n = 853). Patients were followed to determine remission status at 24 weeks. We compared the performance of remission prediction models in RWD, first based on variables determined in our prior work in RCTs, and then using an extended variable set, comparing logistic regression and random forest models. We included patients on other biologic disease-modifying antirheumatic drug monotherapies (bDMARDm) to improve prediction. Results. The fraction of patients observed reaching remission on TCZm by their follow-up visit was 12% (n = 53) in RWD vs 15% (n = 127) in RCTs. Discrimination was good in RWD for the risk score developed in RCTs, with area under the receiver-operating characteristic curve (AUROC) of 0.69 (95% CI 0.62-0.75). Fitting the same logistic regression model to all bDMARDm patients in the RWD improved the AUROC on held-out TCZm patients to 0.72 (95% CI 0.63-0.81). Extending the variable set and adding regularization further increased it to 0.76 (95% CI 0.67-0.84). Conclusion. The remission prediction scores, derived in RCTs, discriminated patients in RWD about as well as in RCTs. Discrimination was further improved by retraining models on RWD.

Disease-modifying antirheumatic drug

Machine learning

Prediction model

Rheumatoid arthritis



Fredrik Johansson

Data Science and AI

Jamie Collins

Brigham and Women's Hospital

Vincent Yau


Hongshu Guan

Brigham and Women's Hospital

Seoyoung C. Kim

Brigham and Women's Hospital

Elena Losina

Brigham and Women's Hospital

D. Sontag

Massachusetts Institute of Technology (MIT)

Jacklyn Stratton

Brigham and Women's Hospital

Huong Trinh


Jeffrey Greenberg

New York University

Daniel H. Solomon

Brigham and Women's Hospital

Journal of Rheumatology

0315-162X (ISSN) 1499-2752 (eISSN)

Vol. 48 9 1364-1370

Subject Categories


Rheumatology and Autoimmunity

Cardiac and Cardiovascular Systems





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