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Polypharmacy is associated with treatment response and serious adverse events: results from the British Society for Rheumatology Biologics Register for Rheumatoid Arthritis


Bechman K1, Clarke BD1, Rutherford AI1, Yates M1, Nikiphorou E1, Molokhia M2, Norton S1, Cope AP1, Hyrich KL3,4, Galloway JB1.

Author informationRheumatology (Oxford). 2019 Apr 14. pii: kez037. doi: 10.1093/rheumatology/kez037. [Epub ahead of print]

Author Information

1 Department of Inflammation Biology, School of Immunology & Microbial Sciences.

2 Primary Care & Public Health Sciences, Health & Social Care Research, Kings College London, London.

3 Arthritis Research UK Centre for Epidemiology, Centre for Musculoskeletal Research, University of Manchester.

4 NIHR Manchester Biomedical Research Centre, Manchester Foundation Trust, Manchester, UK.



To evaluate whether polypharmacy is associated with treatment response and serious adverse events (SAEs) in patients with RA using data from the British Society for Rheumatology Biologics Register (BSRBR-RA).


The BSRBR-RA is a prospective observational cohort study of biologic therapy starters and a DMARD comparator arm. A logistic regression model was used to calculate the odds of a EULAR 'good response' after 12 months of biologic therapy by medication count. Cox proportional hazards models were used to identify risk of SAEs. The utility of the models were compared with the Rheumatic Disease Comorbidity Index using Receiver Operator Characteristic and Harrell's C statistic.


The analysis included 22 005 patients, of which 83% were initiated on biologics. Each additional medication reduced the odds of a EULAR good response by 8% [odds ratios 0.92 (95% CI 0.91, 0.93) P < 0.001] and 3% in the adjusted model [adjusted odds ratios 0.97 (95% CI 0.95, 0.98) P < 0.001]. The Receiver Operator Characteristic demonstrated significantly greater areas under the curve with the polypharmacy model than the Rheumatic Disease Comorbidity Index. There were 12 547 SAEs reported in 7286 patients. Each additional medication equated to a 13% increased risk of an SAE [hazard ratio 1.13 (95% CI 1.12, 1.13) P < 0.001] and 6% in the adjusted model [adjusted hazard ratio 1.06 (95% CI 1.05, 1.07) P < 0.001]. Predictive values for SAEs were comparable between the polypharmacy and Rheumatic Disease Comorbidity Index model.


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.