Hospital for Special Surgery, Weill Cornell Medicine, New York City, New York.
CHRU-Nancy, Nancy University Hospital, INSERM UMR-S 1116, University of Lorraine, F-54000 Nancy, France.
Arthritis Care Res (Hoboken). 2024 Dec;76(12):1617-1625. doi: 10.1002/acr.25415. Epub 2024 Sep 30.
The 2023 American College of Rheumatology/EULAR antiphospholipid syndrome (APS) classification criteria development, which aimed to identify patients with high likelihood of APS for research, employed a four-phase methodology. Phase I and II resulted in 27 proposed candidate criteria, which are organized into laboratory and clinical domains. Here, we summarize the last stage of phase III efforts, employing a consensus-based multicriteria decision analysis (MCDA) to weigh candidate criteria and identify an APS classification threshold score.
We evaluated 192 unique, international real-world patients referred for "suspected APS" with a wide range of APS manifestations. Using proposed candidate criteria, subcommittee members rank ordered 20 representative patients from highly unlikely to highly likely to have APS. During an in-person meeting, the subcommittee refined definitions and participated in an MCDA exercise to identify relative weights of candidate criteria. Using consensus decisions and pairwise criteria comparisons, 1000Minds software assigned criteria weights, and we rank ordered 192 patients by their additive scores. A consensus-based threshold score for APS classification was set.
Premeeting evaluation of 20 representative patients demonstrated variability in APS assessment. MCDA resolved 81 pairwise decisions; relative weights identified domain item hierarchy. After assessing 192 patients by weights and additive scores, the Steering Committee reached consensus that APS classification should require separate clinical and laboratory scores, rather than a single-aggregate score, to ensure high specificity.
Using MCDA, candidate criteria preliminary weights were determined. Unlike other disease classification systems using a single-aggregate threshold score, separate clinical and laboratory domain thresholds were incorporated into the new APS classification criteria.
旨在为研究确定具有高 APS 可能性的患者的 2023 年美国风湿病学会/欧洲抗风湿病联盟（ACR/EULAR）抗磷脂综合征（APS）分类标准制定，采用了四阶段方法。第 I 阶段和第 II 阶段产生了 27 项拟议的候选标准，这些标准分为实验室和临床领域。在这里，我们总结了第三阶段工作的最后阶段，采用基于共识的多标准决策分析（MCDA）来权衡候选标准并确定 APS 分类阈值评分。
我们评估了 192 名具有各种 APS 表现的独特的国际真实世界的“疑似 APS”患者。使用拟议的候选标准，小组委员会成员对 20 名具有高度可能或低度可能患有 APS 的代表性患者进行了排序。在一次现场会议上，小组委员会完善了定义并参与了 MCDA 练习，以确定候选标准的相对权重。使用共识决策和成对标准比较，1000Minds 软件分配了标准权重，并根据他们的加和评分对 192 名患者进行了排序。设定了基于共识的 APS 分类阈值评分。
在会议前对 20 名代表性患者的评估显示 APS 评估存在差异。MCDA 解决了 81 对决策；相对权重确定了域项目层次结构。根据权重和加和评分对 192 名患者进行评估后，指导委员会达成共识，认为 APS 分类应要求单独的临床和实验室评分，而不是单一的综合评分，以确保高特异性。
使用 MCDA，确定了候选标准的初步权重。与其他使用单一综合阈值评分的疾病分类系统不同，新的 APS 分类标准纳入了单独的临床和实验室域阈值。
