A simple algorithm to predict the development of radiological erosions in patients with early rheumatoid arthritis: prospective cohort study
A simple algorithm to predict the development of radiological erosions in patients with early rheumatoid arthritis: prospective cohort study
复制标题
预测早期类风湿关节炎患者放射性侵蚀发展的简单算法：前瞻性队列研究
作者：
P. Brennan;B. Harrison;E. Barrett;K. Chakravarty;D. Scott;A. Silman;D. Symmons
摘要目的：提出一种实用的算法来预测早期类风湿关节炎患者发生放射性侵蚀。设计：基于初级保健的前瞻性队列研究。设定：所有的一般做法，在诺维奇卫生局，诺福克主题：175例患者通知诺福克关节炎登记后不久，他们提出了他们的全科医生与炎症性多关节炎，并再次在12个月后，由计量学家访问。所有患者均符合美国风湿协会1987年的类风湿性关节炎标准，并在症状发作后6个月内接受计量学家检查。研究人群被随机分为一个预测样本（n = 105）生成的算法和验证样本（n = 70）进行测试it.Main结果measures：在基线测量的预测变量包括类风湿因子的状态，肿胀的特定关节区域，晨僵的持续时间，结节，残疾评分，年龄，性别和疾病持续时间时，病人第一次出现。结果变量是12个月后手或脚或两者的放射性侵蚀的存在。结果如下：一个简单的算法基于三个变量的组合类风湿因子检测阳性，至少两个大关节肿胀，疾病持续时间超过三个月，最能预测糜烂。当使用验证样本测试该算法的准确性时，79%的患者的侵蚀状态被正确预测。结论：基于三个易于测量的信息项的简单算法可以预测哪些患者处于放射性侵蚀的高风险中，哪些患者处于放射性侵蚀的低风险中。
Abstract Objective: To produce a practical algorithm to predict which patients with early rheumatoid arthritis will develop radiological erosions. Design: Primary care based prospective cohort study. Setting: All general practices in the Norwich Health Authority, Norfolk Subjects: 175 patients notified to the Norfolk Arthritis Register were visited by a metrologist soon after they had presented to their general practitioners with inflammatory polyarthritis, and again after a further 12 months. All the patients satisfied the American Rheumatism Association's 1987 criteria for rheumatoid arthritis and were seen by a metrologist within six months of the onset of symptoms. The study population was randomly split into a prediction sample (n = 105) for generating the algorithm and a validation sample (n = 70) for testing it. Main outcome measures: Predictor variables measured at baseline included rheumatoid factor status, swelling of specific joint areas, duration of morning stiffness, nodules, disability score, age, sex, and disease duration when the patient first presented. The outcome variable was the presence of radiological erosions in the hands or feet, or both, after 12 months. Results: A simple algorithm based on a combination of three variables—a positive rheumatoid factor test, swelling of at least two large joints, and a disease duration of more than three months—was best able to predict erosions. When the accuracy of this algorithm was tested with the validation sample, the erosion status of 79% of patients was predicted correctly. Conclusions: A simple algorithm based on three easily measured items of information can predict which patients are at high risk and which are at low risk of developing radiological erosions.