Centre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Manchester Academic Health Science Centre, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PG, UK.
Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, University of Manchester, Manchester, UK.
Semin Arthritis Rheum. 2022 Oct;56:152076. doi: 10.1016/j.semarthrit.2022.152076. Epub 2022 Jul 27.
In the management of rheumatoid arthritis (RA), there is a clinical need to identify which patients are at high-risk of not responding to methotrexate (MTX), or experiencing adverse events (AEs), to enable earlier alternative treatments. Many clinical prediction models (CPMs) have previously been developed, but a summary of such models and their methodological quality is lacking. This systematic review aimed to (i) identify and summarize previously published CPMs of MTX outcomes in biologic-naïve RA patients, and (ii) critically appraise their methodological properties.
Medline and Embase were searched to identify studies developing or validating CPMs of MTX outcomes in RA patients. The risk of bias (ROB) was assessed using PROBAST (prediction model risk of bias assessment tool). A fixed effects meta-analysis summarised discrimination for models with multiple external validations.
The systematic review identified 20 CPMs across 13 studies, and 4 validation studies. Three outcome types were used: a state of disease activity (n = 14, 70%); EULAR response criteria (n = 4, 20%); or discontinuation due to AEs (n = 2, 10%). Only one model accounted for potential competing risks, and nine (45%) were internally validated. Eight (40%) models used multiple imputation for missing data, others were often limited to complete case analysis. There was overall high ROB. The meta-analysis summarised c-statistics for two models with multiple external validations was 0.77 (95% CI: 0.69, 0.84) and 0.68 (0.64, 0.71).
This review highlights several methodological shortcomings that should be addressed in future model development to increase potential for implementation into practice.
在类风湿关节炎（RA）的治疗中，临床需要识别哪些患者对甲氨蝶呤（MTX）无应答或发生不良反应（AE）的风险较高，以便及早采用替代治疗。此前已经开发了许多临床预测模型（CPM），但缺乏对这些模型及其方法学质量的总结。本系统综述旨在：（i）识别和总结此前发表的生物初治 RA 患者 MTX 结局的 CPM，并（ii）对其方法学特性进行批判性评估。
检索 Medline 和 Embase 以识别开发或验证 RA 患者 MTX 结局 CPM 的研究。采用 PROBAST（预测模型风险偏倚评估工具）评估偏倚风险（ROB）。对具有多次外部验证的模型进行固定效应荟萃分析，以总结区分度。
系统综述共纳入 13 项研究的 20 项 CPM 和 4 项验证研究。使用了 3 种结局类型：疾病活动状态（n=14，70%）；EULAR 缓解标准（n=4，20%）；或因 AE 停药（n=2，10%）。仅有 1 项模型考虑了潜在的竞争风险，9 项（45%）模型进行了内部验证。8 项（40%）模型使用多重插补处理缺失数据，其他模型通常仅限于完全案例分析。整体 ROB 较高。对具有多次外部验证的两项模型进行荟萃分析，其 C 统计量分别为 0.77（95%CI：0.69，0.84）和 0.68（0.64，0.71）。
本综述突出了未来模型开发中应解决的几个方法学缺陷，以提高其在实践中的应用潜力。
