Department of Inflammation Biology, School of Immunology & Microbial Sciences.
Primary Care & Public Health Sciences, Health & Social Care Research, Kings College London, London.
Rheumatology (Oxford). 2019 Oct 1;58(10):1767-1776. doi: 10.1093/rheumatology/kez037.
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.
利用英国风湿病学会生物制剂登记处(BSRBR-RA)的数据,评估在类风湿关节炎(RA)患者中,药物使用情况与治疗反应和严重不良事件(SAEs)之间的关系。
BSRBR-RA 是一项针对生物制剂起始治疗患者和 DMARD 对照组的前瞻性观察性队列研究。采用逻辑回归模型,按药物数量计算生物治疗 12 个月后 EULAR 反应良好的可能性。采用 Cox 比例风险模型确定 SAE 风险。通过受试者工作特征曲线和 Harrell 的 C 统计比较模型的预测效果。
分析纳入 22005 例患者,其中 83%起始使用生物制剂。每增加一种药物,EULAR 反应良好的可能性降低 8%[比值比(OR)0.92(95%置信区间(CI)0.91,0.93),P<0.001],在调整模型中降低 3%[调整 OR 0.97(95% CI 0.95,0.98),P<0.001]。受试者工作特征曲线显示,药物使用情况模型的曲线下面积明显大于风湿病发病指数。7286 例患者中报告了 12547 例 SAE。每增加一种药物,发生 SAE 的风险增加 13%[风险比(HR)1.13(95% CI 1.12,1.13),P<0.001],在调整模型中增加 6%[调整 HR 1.06(95% CI 1.05,1.07),P<0.001]。药物使用情况模型和风湿病发病指数模型对 SAE 的预测值相当。
药物使用情况是评估 RA 患者临床结局的简单但有价值的指标。本研究支持将药物计数作为流行病学分析中有效测量指标的应用。