From the University of Alabama at Birmingham, Birmingham, Alabama, USA.
J Rheumatol. 2013 May;40(5):572-8. doi: 10.3899/jrheum.120715. Epub 2013 Apr 15.
Rapidly predicting future outcomes based on short-term clinical response would be helpful to optimize rheumatoid arthritis (RA) management in early disease. Our aim was to derive and validate a clinical prediction rule to predict low disease activity (LDA) at 1 year among patients participating in the Treatment of Early Aggressive Rheumatoid Arthritis (TEAR) trial escalating RA therapy by adding either etanercept or sulfasalazine + hydroxychloroquine [triple therapy (TT)] after 6 months of methotrexate (MTX) therapy.
Eligible subjects included in the derivation cohort (used for model building, n = 186) were participants with moderate or higher disease activity [Disease Activity Score 28-erythrocyte sedimentation rate (DAS-ESR) > 3.2] despite 24 weeks of MTX monotherapy who added either etanercept or sulfasalazine + hydroxychloroquine. Clinical characteristics measured within the next 12 weeks were used to predict LDA 1 year later using multivariable logistic regression. Validation was performed in the cohort of TEAR patients randomized to initially receive either MTX + etanercept or TT.
The derivation cohort yielded 3 prediction models of varying complexity that included age, DAS28 at various timepoints, body mass index, and ESR (area under the receiver-operator characteristic curve up to 0.83). Accuracy of the prediction models ranged between 80% and 95% in both derivation and validation cohorts, depending on the complexity of the model and the cutpoints chosen for response and nonresponse. About 80% of patients could be predicted to be responders or nonresponders at Week 12.
Clinical data collected early after starting or escalating disease-modifying antirheumatic drug/biologic treatment could accurately predict LDA at 1 year in patients with early RA. For patients predicted to be nonresponders, treatment could be changed at 12 weeks to optimize outcomes.
基于短期临床应答快速预测未来结局，有助于优化早期疾病类风湿关节炎（RA）的管理。我们的目的是推导并验证一个临床预测规则，以预测接受甲氨蝶呤（MTX）治疗 6 个月后加用依那西普或柳氮磺胺吡啶+羟氯喹[三联疗法（TT）]的患者在治疗早期侵袭性类风湿关节炎（TEAR）试验中达到低疾病活动度（LDA）的 1 年结局。
在推导队列中纳入了符合条件的受试者（用于模型构建，n=186），他们在接受 MTX 单药治疗 24 周后疾病活动仍处于中高度[DAS28-红细胞沉降率（DAS-ESR）>3.2]，加用依那西普或柳氮磺胺吡啶+羟氯喹。在接下来的 12 周内测量的临床特征，用于通过多变量逻辑回归预测 1 年后的 LDA。在 TEAR 患者中进行了验证，这些患者最初随机接受 MTX+依那西普或 TT。
推导队列产生了 3 种不同复杂程度的预测模型，包括年龄、不同时间点的 DAS28、体重指数和 ESR（受试者工作特征曲线下面积高达 0.83）。在推导和验证队列中，预测模型的准确性在 80%至 95%之间，具体取决于模型的复杂程度和选择的反应和非反应的切点。大约 80%的患者在第 12 周可以预测为应答者或非应答者。
在开始或调整疾病修饰抗风湿药物/生物制剂治疗后早期收集的临床数据，可以准确预测早期 RA 患者 1 年的 LDA。对于预测为非应答者的患者，可以在 12 周时改变治疗方案以优化结局。
