van der Helm-van Mil Annette H M, le Cessie Saskia, van Dongen Henrike, Breedveld Ferdinand C, Toes René E M, Huizinga Tom W J
Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands.
Arthritis Rheum. 2007 Feb;56(2):433-40. doi: 10.1002/art.22380.
In patients with undifferentiated arthritis (UA), methotrexate is effective for inhibiting symptoms, structural damage, and progression to rheumatoid arthritis (RA). However, 40-50% of patients with UA experience spontaneous remission. Thus, adequate decision-making regarding treatment of patients with early UA requires identification of those patients in whom RA will develop.
A prediction rule was developed using data from the Leiden Early Arthritis Clinic, an inception cohort of patients with recent-onset arthritis (n = 1,700). The patients who presented with UA were selected (n = 570), and progression to RA or another diagnosis in this group was monitored for 1 year of followup. The clinical characteristics with independent predictive value for the development of RA were selected using logistic regression analysis. The diagnostic performance of the prediction rule was evaluated using the area under the curve (AUC). Cross-validation controlled for overfitting of the data (internal validation). An independent cohort of patients with UA was used for external validation.
The prediction rule consisted of 9 clinical variables: sex, age, localization of symptoms, morning stiffness, the tender joint count, the swollen joint count, the C-reactive protein level, rheumatoid factor positivity, and the presence of anti-cyclic citrullinated peptide antibodies. Each prediction score varied from 0 to 14 and corresponded to the percent chance of RA developing. For several cutoff values, the positive and negative predictive values were determined. The AUC values for the prediction rule, the prediction model after cross-validation, and the external validation cohort were 0.89, 0.87, and 0.97, respectively.
In patients who present with UA, the risk of developing RA can be predicted, thereby allowing individualized decisions regarding the initiation of treatment with disease-modifying antirheumatic drugs in such patients.
在未分化关节炎(UA)患者中,甲氨蝶呤可有效抑制症状、结构损伤以及向类风湿关节炎(RA)的进展。然而,40%-50%的UA患者会出现自发缓解。因此,对于早期UA患者的治疗做出充分决策需要识别出那些将会发展为RA的患者。
使用来自莱顿早期关节炎诊所的数据制定了一个预测规则,该诊所是一个新发关节炎患者的起始队列(n = 1700)。选取表现为UA的患者(n = 570),并对该组患者进展为RA或其他诊断进行为期1年的随访监测。使用逻辑回归分析选择对RA发生具有独立预测价值的临床特征。使用曲线下面积(AUC)评估预测规则的诊断性能。交叉验证控制数据的过度拟合(内部验证)。使用一个独立的UA患者队列进行外部验证。
预测规则由9个临床变量组成:性别、年龄、症状部位、晨僵、压痛关节数、肿胀关节数、C反应蛋白水平、类风湿因子阳性以及抗环瓜氨酸肽抗体的存在。每个预测分数从0到14不等,对应于发生RA的百分比概率。对于几个临界值,确定了阳性和阴性预测值。预测规则、交叉验证后的预测模型以及外部验证队列的AUC值分别为0.89、0.87和0.97。
在表现为UA的患者中,可以预测发生RA的风险,从而能够针对此类患者启动改善病情抗风湿药物治疗做出个体化决策。