Author
Listed:
- Jie Wang
- Yangqi Yin
- Jiaqi Qu
- Zhongbin Tao
- Xuyang Chi
- Xinyue Zhang
Abstract
Background: Antiphospholipid syndrome is an autoimmune disorder characterized by recurrent thrombotic events and/or adverse pregnancy outcomes. Although three classification criteria—the 1999 Sapporo criteria, the Revised Sapporo criteria, and the 2023 ACR/EULAR antiphospholipid syndrome classification—have been developed primarily for research purposes to standardize patient selection, clinicians sometimes apply these criteria to aid in diagnostic decision-making. However, direct head-to-head studies comparing these three criteria remain scarce, and a comprehensive systematic review with network meta-analysis of their classification performance is lacking. Objectives: The primary objective is to conduct a traditional meta-analysis to evaluate and compare the performance (sensitivity, specificity, positive likelihood ratio [PLR], negative likelihood ratio [NLR]) of each individual classification criterion. Secondary objectives include: 1) Conducting a Bayesian network meta-analysis (NMA) to compare and rank the three criteria using superiority index (SI); and 2) Exploring sources of heterogeneity through predefined subgroup analyses (primary vs. secondary APS, thrombotic vs. obstetric APS). Methods: Adhering to the PRISMA-P statement, this protocol has been registered in PROSPERO (CRD420251074199). A comprehensive literature search will be performed in electronic databases (PubMed/MEDLINE, Embase, the Cochrane Library, Web of Science) and gray literature sources (ClinicalTrials.gov, abstracts from international congresses including ACR, EULAR) from their inception to October 2025. Eligible studies are classification performance studies (cross-sectional, cohort, or case-control) that assess at least one of the three criteria against the reference standard (expert clinical diagnosis by rheumatologists/APS specialists, based on comprehensive evaluation of clinical history, persistent antiphospholipid antibodies [aPLs] testing, and exclusion of alternative causes). The quality of included studies will be assessed using the QUADAS-2 tool. Bayesian NMA will be conducted in R version 4.3.0 with the RStan package, adopting a random-effects ANOVA model. Heterogeneity will be assessed via Cochrane’s Q test and the inconsistency index (I²), while publication bias will be evaluated using Deeks’ funnel plot asymmetry test.
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