Vastesaeger Nathan, Kutzbach Abraham Garcia, Amital Howard, Pavelka Karel, Lazaro María Alicia, Moots Robert J, Wollenhaupt Jürgen, Zerbini Cristiano A F, Louw Ingrid, Combe Bernard, Beaulieu Andre, Schulze-Koops Hendrik, Dasgupta Bhaskar, Fu Bo, Huyck Susan, Weng Haoling H, Govoni Marinella, Durez Patrick
Department of Medical Affairs, MSD Danmark ApS, Ballerup, Denmark
Department of Rheumatology, AGAR Francisco Marroquin University, Guatemala City, Guatemala.
Rheumatology (Oxford). 2016 Aug;55(8):1466-76. doi: 10.1093/rheumatology/kew179. Epub 2016 Apr 25.
OBJECTIVE: To create a tool to predict probability of remission and low disease activity (LDA) in patients with RA being considered for anti-TNF treatment in clinical practice. METHODS: We analysed data from GO-MORE, an open-label, multinational, prospective study in biologic-naïve patients with active RA (DAS28-ESR ⩾3.2) despite DMARD therapy. Patients received 50 mg s.c. golimumab (GLM) once monthly for 6 months. In secondary analyses, regression models were used to determine the best set of baseline factors to predict remission (DAS28-ESR <2.6) at month 6 and LDA (DAS28-ESR ⩽3.2) at month 1. RESULTS: In 3280 efficacy-evaluable patients, of 12 factors included in initial regression models predicting remission or LDA, six were retained in final multivariable models. Greater likelihood of LDA and remission was associated with being male; younger age; lower HAQ, ESR (or CRP) and tender joint count (or swollen joint count) scores; and absence of comorbidities. In models predicting 1-, 3- and 6-month LDA or remission, area under the receiver operating curve was 0.648-0.809 (R(2) = 0.0397-0.1078). The models also predicted 6-month HAQ and EuroQoL-5-dimension scores. A series of matrices were developed to easily show predicted rates of remission and LDA. CONCLUSION: A matrix tool was developed to show predicted GLM treatment outcomes in patients with RA, based on a combination of six baseline characteristics. The tool could help provide practical guidance in selection of candidates for anti-TNF therapy.
目的：创建一种工具，用于预测临床实践中考虑接受抗TNF治疗的类风湿关节炎（RA）患者的缓解概率和低疾病活动度（LDA）。 方法：我们分析了GO-MORE研究的数据，这是一项针对初治的活动性RA（疾病活动度评分28关节疾病活动指数基于血沉（DAS28-ESR）⩾3.2）患者的开放标签、多国、前瞻性研究，尽管这些患者接受了改善病情抗风湿药（DMARD）治疗。患者每月皮下注射50mg戈利木单抗（GLM），共6个月。在二次分析中，使用回归模型确定预测第6个月缓解（DAS28-ESR<2.6）和第1个月LDA（DAS28-ESR⩽3.2）的最佳基线因素组合。 结果：在3280例可进行疗效评估的患者中，最初预测缓解或LDA的回归模型纳入的12个因素中，有6个被保留在最终的多变量模型中。LDA和缓解可能性更高与男性、年龄较小、健康评估问卷（HAQ）、血沉（ESR）（或C反应蛋白（CRP））及压痛关节数（或肿胀关节数）评分较低以及无合并症相关。在预测1个月、3个月和6个月LDA或缓解的模型中，受试者工作特征曲线下面积为0.648 - 0.809（R² = 0.0397 - 0.1078）。这些模型还预测了6个月时的HAQ和欧洲五维健康量表（EuroQoL-5维度）评分。开发了一系列矩阵以方便展示缓解和LDA的预测概率。 结论：基于六个基线特征的组合，开发了一种矩阵工具来展示RA患者接受GLM治疗的预测结果。该工具可为抗TNF治疗候选者的选择提供实用指导。
Front Immunol. 2021
Arthritis Res Ther. 2014-2-21
Arthritis Care Res (Hoboken). 2014-9
Ann Rheum Dis. 2011-3-14
Arthritis Care Res (Hoboken). 2010-8
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