Real-World Sarilumab Use and Rule Testing to Predict Treatment Response in Patients with Rheumatoid Arthritis: Findings from the RISE Registry.
Real-World Sarilumab Use and Rule Testing to Predict Treatment Response in Patients with Rheumatoid Arthritis: Findings from the RISE Registry.
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DOI：
10.1007/s40744-023-00568-8
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发表时间：
2023-08
影响因子：
3.8
通讯作者：
Choy, Ernest
中科院分区：
文献类型：
--
作者：
Curtis, Jeffrey R.;Yun, Huifeng;Chen, Lang;Ford, Stephanie S.;van Hoogstraten, Hubert;Fiore, Stefano;Ford, Kerri;Praestgaard, Amy;Rehberg, Markus;Choy, Ernest
关键词：
临床试验结果可能无法推广到常规实践。本研究评估了sar在类风湿性关节炎（RA）患者中的有效性，并测试了使用机器学习（基于C反应蛋白[CRP] > 12.3 mg/l和血清阳性[抗环瓜氨酸肽抗体，ACPA +]）从试验数据中得出的反应预测规则的现实适用性。来自ACR-RISE登记研究的Sar启动者，FDA批准时/批准后有≥ 1个处方（2017-2020年），根据逐步限制的标准分为三个队列：队列A（患有活动性疾病），队列B（符合在对肿瘤坏死因子抑制剂[TNFi]应答不足/不耐受的RA患者中进行的III期试验的合格性标准），和队列C（与III期试验基线匹配的特征）。在6个月和12个月时评价了临床疾病活动指数（CDAI）和患者指数数据常规评估3（RAPID 3）的平均变化。在一个单独的队列中，基于CRP水平和血清阳性状态（ACPA和/或类风湿因子）测试预测规则;将患者分类为规则阳性（血清阳性，CRP > 12.3 mg/l）和规则阴性组，以比较在24周内实现CDAI低疾病活动度（LDA）/缓解和最小临床重要差异（MCID）的几率。在sar启动者（N = 2949）中，观察到各队列的治疗有效性，在6个月和12个月时观察到队列C的改善更大。在预测规则队列（N = 205）中，规则阳性（与规则阴性）患者更有可能达到LDA（比值比：1.5 [0.7，3.2]）和MCID（1.1 [0.5，2.4]）。敏感性分析（CRP > 5 mg/l）显示，规则阳性患者对sar的反应更好。在现实世界中，sar表现出治疗有效性，在最具选择性的人群中有更大的改善，反映了3期TNFi难治性和规则阳性的RA患者。血清阳性似乎是比CRP更强的治疗应答驱动因素，尽管在常规实践中优化该规则需要进一步的数据。在线版本包含补充材料，可通过10.1007/s40744-023-00568-8获取。风湿性关节炎（RA）是一种如果不治疗可能导致关节损伤的疾病。Sar是一种先进的药物，被批准用于治疗对初始标准药物无反应的中度至重度RA患者。临床试验表明，sar改善RA症状;然而，有些人没有反应。这是RA治疗中的常见问题。医生测量人们血液中的蛋白质（称为生物标志物;例如，抗环瓜氨酸肽抗体[ACPA]、C反应蛋白[CRP]和类风湿因子[RF]）来预测药物的反应。之前的一项研究表明，ACPA和CRP（> 12.3 mg/l）血液检测阳性的人对sar反应良好;这项研究基于机器学习（使用计算机的科学分支），并确定了可能与治疗益处相关的因素。本研究分析了来自ACR-RISE登记处的2949人的常规数据，并显示在sar治疗6个月和12个月后RA症状有所改善，在先前接受其他药物治疗的患者中观察到更大的改善。在205人中测试了生物标志物，以检查它们是否可以预测日常生活中的治疗反应。如果人们对RF和/或ACPA检测呈阳性且CRP > 12.3 mg/l，则被称为规则阳性，否则为规则阴性。经过24周的治疗后，规则阳性的人比规则阴性的人有更大的机会改善疾病。这些结果显示了sar在常规护理中对RA的益处，并表明机器学习在识别医生可用于做出治疗决策的生物标志物方面的有用性。在线版本包含补充材料，可通过10.1007/s40744-023-00568-8获取。
Clinical trial findings may not be generalizable to routine practice. This study evaluated sarilumab effectiveness in patients with rheumatoid arthritis (RA) and tested the real-world applicability of a response prediction rule, derived from trial data using machine learning (based on C-reactive protein [CRP] > 12.3 mg/l and seropositivity [anticyclic citrullinated peptide antibodies, ACPA +]). Sarilumab initiators from the ACR-RISE Registry, with ≥ 1 prescription on/after its FDA approval (2017–2020), were divided into three cohorts based on progressively restrictive criteria: Cohort A (had active disease), Cohort B (met eligibility criteria of a phase 3 trial in RA patients with inadequate response/intolerance to tumor necrosis factor inhibitors [TNFi]), and Cohort C (characteristics matched to the phase 3 trial baseline). Mean changes in Clinical Disease Activity Index (CDAI) and Routine Assessment of Patient Index Data 3 (RAPID3) were evaluated at 6 and 12 months. In a separate cohort, predictive rule was tested based on CRP levels and seropositive status (ACPA and/or rheumatoid factor); patients were categorized into rule-positive (seropositive with CRP > 12.3 mg/l) and rule-negative groups to compare the odds of achieving CDAI low disease activity (LDA)/remission and minimal clinically important difference (MCID) over 24 weeks. Among sarilumab initiators (N = 2949), treatment effectiveness was noted across cohorts, with greater improvement noted for Cohort C at 6 and 12 months. Among the predictive rule cohort (N = 205), rule-positive (vs. rule-negative) patients were more likely to reach LDA (odds ratio: 1.5 [0.7, 3.2]) and MCID (1.1 [0.5, 2.4]). Sensitivity analyses (CRP > 5 mg/l) showed better response to sarilumab in rule-positive patients. In real-world setting, sarilumab demonstrated treatment effectiveness, with greater improvements in the most selective population, mirroring phase 3 TNFi-refractory and rule-positive RA patients. Seropositivity appeared a stronger driver for treatment response than CRP, although optimization of the rule in routine practice requires further data. The online version contains supplementary material available at 10.1007/s40744-023-00568-8. Rheumatoid arthritis (RA) is a condition that may cause joint damage, if untreated. Sarilumab is an advanced medication, approved for treating moderate-to-severe RA in patients not responding to initial standard medicines. Clinical trials have shown that sarilumab improves RA symptoms; however, some people do not respond. This is a common problem in RA treatment. Physicians measure proteins in people’s blood (called biomarkers; e.g., anticyclic citrullinated peptide antibodies [ACPA], C-reactive protein [CRP], and rheumatoid factor [RF]) to predict a medicine’s response. A previous study showed that people with positive blood tests for ACPA and CRP (> 12.3 mg/l) responded well to sarilumab; this study was based on machine learning (a branch of science using computers) and identified factors that could be linked to treatment benefits. The present study analyzed routine data of 2949 people from the ACR-RISE Registry and showed an improvement in RA symptoms after 6 and 12 months of sarilumab, with a greater improvement noted in patients previously treated with other medicines. Biomarkers were tested in 205 people to check whether they could predict treatment response in day-to-day life. People were called rule-positive if they tested positive for RF and/or ACPA with CRP > 12.3 mg/l, and otherwise rule-negative. After 24 weeks of treatment, rule-positive people had a greater chance of disease improvement than rule-negative people. These results showed the benefits of sarilumab in RA in routine care and suggested the usefulness of machine learning in identifying biomarkers that physicians can use to make treatment decisions. The online version contains supplementary material available at 10.1007/s40744-023-00568-8.
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3.8
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