Sjögren's disease & overlap diseases
A non-invasive model for diagnosis of primary Sjogren’s disease based on salivary biomarkers, serum autoantibodies, and Schirmer’s test
Authors' conclusion
The 6-biomarker panel could provide a novel non-invasive tool for the classification of pSjD.
Study context
- Population
- Patients with primary Sjögren's disease (pSjD) and non-Sjögren control subjects (non-pSjD)derivation 186, validation 72
- Comparison
- 6-biomarker model for pSjD vs non-pSjD
- Outcome
- Discrimination of pSjD from non-pSjD (ROC AUC, sensitivity, specificity)
Methodological detailsproteomic discovery (LC-MS/MS) with ELISA confirmation, multivariate logistic regression, derivation and validation cohorts
- Proteomic discovery (LC-MS/MS) with ELISA confirmation
- Multivariate logistic regression
- Derivation and validation cohorts
Performance
As reported in the abstract
Diagnosis of pSjD, derivation cohort
| Test or model | AUC | Sensitivity | Specificity |
|---|---|---|---|
| 6-biomarker model | 0.930 (95% CI 0.877-0.965, P < 0.001) | 84.85% | 92.45% |
6-biomarker model
AUC0.930 (95% CI 0.877-0.965, P < 0.001)
Sensitivity84.85%
Specificity92.45%
Further findings
Diagnosis of pSjD, validation cohort
- Similar results obtained in a validation cohort
Independent predictors of pSS (multivariate analyses)
- Complement factor B (CFB), clusterin (CLU), and neutrophil elastase (NE) were independent predictors of pSS
Original publication
A non-invasive model for diagnosis of primary Sjogren’s disease based on salivary biomarkers, serum autoantibodies, and Schirmer’s test. Arthritis Res Ther. Published 19 December 2024. doi:10.
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