Objectives We aimed to develop a prediction model identifying people presenting to primary care with musculoskeletal symptoms likely to be anti-CCP positive and therefore at risk of developing rheumatoid arthritis (RA). Methods Participants aged ≥16 years, with new-onset non-specific musculoskeletal symptoms and no history of clinical synovitis, completed a symptom questionnaire and had an anti-CCP test. Model development used LASSO-penalised logistic regression, performance was assessed using area under the receiver operating characteristic curve (AUROC) and decision curve analysis, model over-fit was estimated using bootstrapping and cross-validation. Participants were followed-up at 12 months for RA or seronegative/undifferentiated inflammatory arthritis (IA) diagnosis. Results Analysis included 6879 participants; 203 (2.95%) anti-CCP positive. Eleven predictors were retained: male sex, first-degree relative with RA, ever smoked, and joint pain in: back, neck, shoulders, wrists, hands/fingers, thumbs, knees, feet/toes. AUROC was 0.65 (95% CI:(0.61, 0.69), optimism = 0.03). Using a 4% decision threshold, the model recommended an anti-CCP test in 1288 (18.7%) participants, 78 (6.1%) of whom were anti-CCP positive, compared with 125/5591 (2.2%) below the threshold. Net benefit was 0.0040 (0.0020 corrected). Forty-eight participants were diagnosed with IA/RA within 12 months. Of those who were above the threshold and anti-CCP positive, 32.1% developed IA/RA compared with 0.4% of those who were anti-CCP negative. Of those below the threshold, 0.3% were diagnosed with IA/RA. Conclusions Targeted anti-CCP testing in primary care may aid earlier identification of people at risk of RA, prompting specialist referral to rheumatology for earlier diagnosis and initiation of disease modifying therapy.

中文翻译：

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一个多变量预测模型，用于识别初级保健中具有非特异性肌肉骨骼症状的人群中的抗 CCP 阳性人群


目的 我们旨在开发一个预测模型，识别出在初级保健机构就诊的肌肉骨骼症状可能是抗 CCP 阳性，因此有患类风湿性关节炎 （RA） 风险的人。方法 参与者年龄≥16 岁，新发非特异性肌肉骨骼症状，无临床滑膜炎病史，完成症状问卷并进行抗 CCP 测试。模型开发使用 LASSO 惩罚 logistic 回归，使用受试者工作特征曲线下面积 （AUROC） 和决策曲线分析评估性能，使用自举和交叉验证估计模型过拟合。参与者在 12 个月时接受 RA 或血清阴性/未分化炎症性关节炎 （IA） 诊断的随访。结果分析包括 6879 名参与者;203 例 （2.95%） 抗 CCP 阳性。保留了 11 个预测因子： 男性、RA 一级亲属、曾经吸烟以及以下部位的关节疼痛： 背部、颈部、肩部、手腕、手/手指、拇指、膝盖、脚/脚趾。AUROC 为 0.65 （95% CI：（0.61， 0.69），乐观 = 0.03）。该模型使用 4% 的决策阈值，建议对 1288 名 （18.7%） 参与者进行抗 CCP 测试，其中 78 名 （6.1%） 患者抗 CCP 阳性，而低于阈值的 125/5591 名 （2.2%）。净收益为 0.0040（校正后为 0.0020）。48 名参与者在 12 个月内被诊断出患有 IA/RA。在高于阈值且抗 CCP 阳性的患者中，32.1% 发生 IA/RA，而抗 CCP 阴性的患者中为 0.4%。在低于阈值的患者中，0.3% 被诊断患有 IA/RA。 结论 在初级保健机构中进行有针对性的抗 CCP 检测可能有助于早期识别有 RA 风险的人群，促使专科医生转诊至风湿病科进行早期诊断和开始疾病修正治疗。