October 17, 2019
Polypharmacy can predict clinical outcomes among persons with rheumatoid arthritis, according to results of a new study.
The researchers evaluated data of 22,005 patients with RA enrolled in the British Society for Rheumatology Biologics Register for Rheumatoid Arthritis (BSRBR-RA), an ongoing treatment register that assesses exposures to biologic disease-modifying antirheumatic drugs, treatment response, and adverse effects among persons in the United Kingdom.
A logistic regression model was used to measure the likelihood of a good response, based on European League Against Rheumatism (EULAR) response criteria, after 12 months of biologic therapy by medication count. The Cox proportional hazards model was used to identify the risk of serious adverse events (SAEs).
The researchers compared the utility of both models with the Rheumatic Disease Comorbidity Index via the receiver operating characteristic (ROC) curve and Harrell C statistic.
Results indicated that each additional medication reduced the likelihood of a good response by 8% and by 3% in the adjusted model. The ROC showed significantly greater areas under the curve with the polypharmacy model compared with the Rheumatic Disease Comorbidity Index.
A total of 12,547 SAEs were reported among 7286 patients. Each additional medication was equated to a 13% increased risk of an SAE, and a 6% increased risk in the adjusted model.
The predictive values of SAEs were comparable between the polypharmacy and Rheumatic Disease Comorbidity Index models.
“Polypharmacy is a simple but valuable predictor of clinical outcomes in patients with RA. This study supports medication count as a valid measure for use in epidemiologic analyses,” the authors concluded.
Bechman K, Clarke BD, Rutherford AI, et al. Polypharmacy is associated with treatment response and serious adverse events: results from the British Society for Rheumatology Biologics Register for Rheumatoid Arthritis. Rheumatology. 2019;58(10):1767-1776. doi:10.1093/rheumatology/kez037.