Predictors of treatment response in rheumatoid arthritis: a narrative review
- 1Division of Immunology, Otto Loewi Research Center, Medical University Graz, Graz, Austria
- 2Department of Rheumatology and Immunology, LKH Univ. Klinikum Graz, Medical University of Graz, Graz, Austria
Abstract
Rheumatoid arthritis (RA) is a common autoimmune disease having diverse responses to disease-modifying antirheumatic drugs. Although treat-to-target strategies have improved disease management, therapeutic selection remains largely empirical and a substantial proportion of patients fail to achieve adequate clinical response to their therapies. Therefore, reliable biomarkers capable of predicting treatment response before therapy initiation are urgently needed to guide personalised treatment decisions. Current evidence suggests that multiple categories of biomarkers may contribute to the prediction of treatment responses across different therapeutic agents in RA, including clinical characteristics, serological markers, cytokine profiles, genetic and transcriptomic signatures, immune-cell phenotypes, synovial pathotypes and microbiome features. This review summarises current biomarker strategies for predicting therapeutic response in RA and discusses their potential utility in improving precision medicine. However, most individual biomarkers show limited predictive power, partly due to the complex and dynamic nature of RA pathogenesis. Combining biomarkers from multiple biological dimensions, together with the continued exploration of novel predictive markers, may improve the robustness and accuracy of treatment response prediction in RA.
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BibTeX
@article{sun2026predictors,
title = {{Predictors of treatment response in rheumatoid arthritis: a narrative review}},
author = {Yi Sun and Martin Helmut Stradner and Johannes Fessler and Myriam Katja Reisch},
journal = {RMD Open},
year = {2026},
month = oct,
doi = {10.1136/rmdopen-2026-007225},
url = {https://doi.org/10.1136/rmdopen-2026-007225},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Predictors of treatment response in rheumatoid arthritis: a narrative review
AU - Yi Sun
AU - Martin Helmut Stradner
AU - Johannes Fessler
AU - Myriam Katja Reisch
PY - 2026
DA - 2026/10/26
JO - RMD Open
DO - 10.1136/rmdopen-2026-007225
UR - https://doi.org/10.1136/rmdopen-2026-007225
AB - Rheumatoid arthritis (RA) is a common autoimmune disease having diverse responses to disease-modifying antirheumatic drugs. Although treat-to-target strategies have improved disease management, therapeutic selection remains largely empirical and a substantial proportion of patients fail to achieve adequate clinical response to their therapies. Therefore, reliable biomarkers capable of predicting treatment response before therapy initiation are urgently needed to guide personalised treatment decisions. Current evidence suggests that multiple categories of biomarkers may contribute to the prediction of treatment responses across different therapeutic agents in RA, including clinical characteristics, serological markers, cytokine profiles, genetic and transcriptomic signatures, immune-cell phenotypes, synovial pathotypes and microbiome features. This review summarises current biomarker strategies for predicting therapeutic response in RA and discusses their potential utility in improving precision medicine. However, most individual biomarkers show limited predictive power, partly due to the complex and dynamic nature of RA pathogenesis. Combining biomarkers from multiple biological dimensions, together with the continued exploration of novel predictive markers, may improve the robustness and accuracy of treatment response prediction in RA.
SN - 2056-5933
ER -