Increased predictive value of optical spectral transmission in early rheumatoid arthritis through use of patient-adjusted cut-off scores
Authors' conclusion
The development of patient-adjusted OST cut-off values and the suggested statistical models significantly enhance OST's diagnostic performance, supporting its utility in differentiating between RA and non-inflammatory conditions.
Study context
- Population
- Newly diagnosed early rheumatoid arthritis (RA) patients, healthy controls and patients with non-inflammatory arthralgia examined by optical spectral transmission (OST) (HandScan device)
- Participants
- 72 / 100 / 53
- Comparison
- OST in early RA vs healthy controls and vs non-inflammatory arthralgia
- Early RAn = 72
- Healthy controlsn = 100reference
- Non-inflammatory arthralgia (NIA)n = 53reference
- Outcome
- Diagnostic performance of OST for early RA (2010 ACR/EULAR criteria as reference standard)
Performance
As reported in the abstract
OST diagnostic performance (AUC)
AUC
0.810
95% CI 0.746–0.873P < 0.0001
Early RA vs Healthy controls · whole cohort
AUC
0.788
95% CI 0.709–0.867P < 0.0001
Early RA vs NIA
Further findings
| Outcome | AUC (95% CI) | P value |
|---|---|---|
| OST AUC in RA with ≥ 1 swollen wrist/finger joint(s) (subgroup)Early RA vs Healthy controls | 0.841 (0.773–0.908) | P < 0.0001 |
| OST AUC in RA with ≥ 1 swollen wrist/finger joint(s) (subgroup)Early RA vs NIA | 0.822 (0.74–0.90) | P < 0.0001 |
Patient-adjusted OST cut-offs, active disease
- Female cut-off
- 11.2
- Female sensitivity
- 93%
- Female specificity
- 71.2%
- Male cut-off
- 18.21
- Male sensitivity
- 67%
- Male specificity
- 90%
- Two gender-specific models based on OST values and patient age
Correlation of OST with RA activity (RA patients)
- DAS28, r = 0.42
- P < 0.001
- Swollen joint count, rho = 0.355
- P = 0.002
Original publication
Increased predictive value of optical spectral transmission in early rheumatoid arthritis through use of patient-adjusted cut-off scores. Arthritis Res Ther. Published 20 September 2024. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →