The role of multicriteria decision analysis in the development of candidate classification criteria for antisynthetase syndrome: analysis from the CLASS project
Authors' conclusion
The MCDA-driven candidate classification criteria were consistent with published ASSD literature and yielded high accuracy and validity.
Study context
- Population
- Consensus cases and controls (clinical vignettes) and real-world data from participating centres; antisynthetase syndrome (ASyS)
- Outcome
- Performance of MCDA-driven candidate classification criteria for ASyS (AUC and diagnostic accuracy metrics)
Methodological detailssystematic literature review, expert preferences surveys, multicriteria decision analysis (MCDA), Potentially All Pairwise RanKings of all possible Alternatives method, ROC curves and diagnostic accuracy metrics
- Systematic literature review
- Expert preferences surveys
- Multicriteria decision analysis (MCDA)
- Potentially All Pairwise RanKings of all possible Alternatives method
- ROC curves and diagnostic accuracy metrics
Performance
As reported in the abstract
Performance of candidate classification criteria
Sensitivities, specificities, PPV and NPV
>80%
Further findings
Weights of key variables
- Antisynthetase antibody positivity had the highest weight
- Highest-ranked clinical manifestation interstitial lung disease (ILD), then myositis, mechanic's hands, joint involvement, inflammatory rashes, RP, fever and pulmonary hypertension
Original publication
The role of multicriteria decision analysis in the development of candidate classification criteria for antisynthetase syndrome: analysis from the CLASS project. Ann Rheum Dis. Published 18 March 2025. doi:10.
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