Centre for Musculoskeletal Research, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Centre for Musculoskeletal Research, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK; NIHR Manchester Musculoskeletal Biomedical Research Unit, Manchester Academy of Health Sciences, Manchester, UK.
Lancet. 2015 Feb 26;385 Suppl 1:S48. doi: 10.1016/S0140-6736(15)60363-4.
Up to 40% of patients with rheumatoid arthritis treated with anti-tumour necrosis factor (TNF) drugs do not respond because of primary inefficacy or loss of response. Although one explanation is that immunogenicity leads to the development of anti-drug antibodies and low drug concentrations, the clinical usefulness of pharmacological monitoring is debated. Our aim was to assess whether the presence of anti-drug antibodies and non-trough drug concentrations could predict treatment response in patients with rheumatoid arthritis treated with anti-TNF drugs.
331 patients were selected from a multicentre prospective cohort (160 treated with adalimumab, 171 etanercept). Serum samples were collected at 3, 6, and 12 months after treatment initiation. Anti-drug antibodies were measured with RIA, drug concentrations with ELISAs, and Disease Activity Score in 28 joints (DAS28) at each timepoint. Linear and logistic regression, generalised estimating equation (GEE), and receiver operating characteristic curves were used to test the association and predictive value of anti-drug antibodies and non-trough drug concentrations on treatment response (ΔDAS28).
835 serial samples were tested (414 adalimumab, 421 etanercept). Anti-adalimumab antibodies were detected in 31 (24·8%) of 125 patients who had completed 12 month follow-up and none of the etanercept patients. The presence of anti-drug antibodies was associated with lower adalimumab concentrations (Spearman r=-0·66, p=0·0041). At 3 months, anti-drug antibody formation and low adalimumab concentrations were significant predictors of poor treatment response at 12 months (area under curve [AUC] 0·68, 95% CI 0·54-0·81, and 0·66, 0·55-0·77, respectively; and both combined 0·71, 0·57-0·85). Adalimumab concentration was the most significant independent predictor of ΔDAS28 after adjustment for confounders (regression coefficient 0·12, 95% CI 0·06-0·18; p=0·003). High etanercept concentrations were associated with better treatment response (p=0·01), but low concentrations at 3 months were not a significant predictor of poor treatment response at 12 months (AUC 0·58, 95% CI 0·46-0·70). In the combined GEE model including adalimumab and etanercept, a body-mass index of 30 kg/m(2) or more was associated with low drug concentrations (regression coefficient 0·78, 95% CI 0·37-1·18; p<0·0001).
Pharmacological testing in anti-TNF initiated patients is clinically useful even in the absence of trough levels. At 3 months, presence of anti-drug antibodies and low adalimumab concentrations are a significant predictor for poor treatment response at 12 months. Strengths of this study include a large, prospective cohort and use of RIA to measure antibodies (less prone to drug interference). Although non-trough concentrations might have underestimated the frequency of antibodies, their presence still predicted response.
MJ is a MRC Clinical Training Fellow supported by the North West England Medical Research Council Fellowship Scheme in Clinical Pharmacology and Therapeutics, which is funded by the UK Medical Research Council (grant number G1000417/94909), ICON, GlaxoSmithKline, AstraZeneca, and the Medical Evaluation Unit. Arthritis Research UK (grant ref 20385).
高达 40%的接受抗肿瘤坏死因子（TNF）药物治疗的类风湿关节炎患者由于原发性疗效不佳或疗效丧失而没有反应。尽管有一种解释是免疫原性导致了抗药物抗体的产生和药物浓度降低，但药物监测的临床实用性仍存在争议。我们的目的是评估类风湿关节炎患者接受抗 TNF 药物治疗时，是否存在抗药物抗体和非谷浓度可以预测治疗反应。
从一个多中心前瞻性队列中选择了 331 名患者（阿达木单抗治疗 160 例，依那西普治疗 171 例）。在治疗开始后 3、6 和 12 个月采集血清样本。用 RIA 测量抗药物抗体，用 ELISA 测量药物浓度，用 28 个关节疾病活动评分（DAS28）在每个时间点进行测量。线性和逻辑回归、广义估计方程（GEE）和接收者操作特征曲线用于测试抗药物抗体和非谷浓度与治疗反应（ΔDAS28）的关联和预测价值。
共检测了 835 份连续样本（阿达木单抗 414 份，依那西普 421 份）。在完成 12 个月随访的 125 名患者中有 31 名（24.8%）检测到抗阿达木单抗抗体，而依那西普患者中没有检测到。抗药物抗体的存在与较低的阿达木单抗浓度相关（Spearman r=-0.66，p=0.0041）。在 3 个月时，抗药物抗体的形成和低阿达木单抗浓度是 12 个月时治疗反应不良的显著预测因素（曲线下面积[AUC]0.68，95%CI 0.54-0.81 和 0.66，0.55-0.77；两者联合 AUC 0.71，0.57-0.85）。在调整混杂因素后，阿达木单抗浓度是 ΔDAS28 的最显著独立预测因子（回归系数 0.12，95%CI 0.06-0.18；p=0.003）。高依那西普浓度与更好的治疗反应相关（p=0.01），但 3 个月时的低浓度并不是 12 个月时治疗反应不良的显著预测因素（AUC 0.58，95%CI 0.46-0.70）。在包括阿达木单抗和依那西普的联合 GEE 模型中，体重指数为 30 kg/m2 或更高与低药物浓度相关（回归系数 0.78，95%CI 0.37-1.18；p<0.0001）。
即使没有谷浓度，在开始接受 TNF 抑制剂治疗的患者中进行药物检测在临床上也是有用的。在 3 个月时，存在抗药物抗体和低阿达木单抗浓度是 12 个月时治疗反应不良的显著预测因素。本研究的优势包括一个大型的前瞻性队列和使用 RIA 来测量抗体（较少受到药物干扰）。尽管非谷浓度可能低估了抗体的频率，但它们的存在仍然可以预测反应。
MJ 是英国医学研究理事会临床药理学和治疗学北英格兰医学研究理事会奖学金计划的 MRC 临床培训研究员，该计划由英国医学研究理事会（资助号 G1000417/94909）、ICON、葛兰素史克、阿斯利康和医学评估单位资助。关节炎研究英国（资助号 20385）。
