Using Polygenic Risk Scores to Aid Diagnosis of Patients With Early Inflammatory Arthritis: Results From the Norfolk Arthritis Register
Authors' conclusion
G-PROB converts complex genetic information into meaningful and interpretable conditional probabilities, which may be especially helpful at eliminating unlikely diagnoses in the rheumatology outpatient setting.
Study context
- Population
- Patients presenting with early inflammatory arthritis, Norfolk Arthritis Register (NOAR)
- Participants
- 1,047 patients
- Comparison
- G-PROB genetic probabilities vs clinician diagnosis
- G-PROBn = 1,047
- Outcome
- Performance of G-probabilities compared with clinician diagnosis
Methodological detailsprospective observational cohort
- Prospective observational cohort
Performance
As reported in the abstract
Performance of G-probabilities vs clinician diagnosis
| Test or model | Calibration regression coefficient (1.00 ideal) | Pooled AUC | NPV (G-probabilities <5%) | PPV (G-probabilities >50%) | Highest G-probability matched clinician diagnosis |
|---|---|---|---|---|---|
| G-PROB | 1.047 | 0.85 (95% CI 0.84-0.86) | 96.0% | 70.4% | 55.7% |
G-PROB
Calibration regression coefficient (1.00 ideal)1.047
Pooled AUC0.85 (95% CI 0.84-0.86)
NPV (G-probabilities <5%)96.0%
PPV (G-probabilities >50%)70.4%
Highest G-probability matched clinician diagnosis55.7%
Further findings
| Outcome | G-PROB |
|---|---|
| Unlikely diseases suggested (G-probabilities <5%) | |
| >2 unlikely diseases | 94% |
| >3 unlikely diseases | 53.7% |
Original publication
Using Polygenic Risk Scores to Aid Diagnosis of Patients With Early Inflammatory Arthritis: Results From the Norfolk Arthritis Register. Arthritis Rheumatol. Published 17 January 2024. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →