Spondyloarthritis & psoriatic arthritis
Clinical Validation of Digitally Acquired Clinical Data and Machine Learning Models for Remote Measurement of Psoriasis and Psoriatic Arthritis: A Proof-of-Concept Study
Authors' conclusion
The Psorcast digital assessments achieved significant clinical validity, although they require further validation in larger cohorts before use in evidence-based medicine or clinical trial settings.
Study context
- Population
- Participants with PsO or psoriatic arthritis (PsA) and healthy controls, 2 academic medical centers, June 5, 2019 to November 10, 2021 (mean age 42.3 years)51 female, 53 male
- Participants
- 104 participants
- Comparison
- Smartphone-based digital assessments (Psorcast app) and image-based machine learning models vs analogous clinical measures by trained rheumatologists and dermatologists
- PsAn = 79
- PsOn = 16
- Healthy controlsn = 9
- Outcome
- Concordance and accuracy of digital measures vs clinical measures
Methodological detailsproof-of-concept, 2 academic medical centers
- Proof-of-concept
- 2 academic medical centers
Performance
As reported in the abstract
- Digital patient-assessed % body surface area (BSA) with PsO vs physician-assessed BSA, Lin CCC
- 0.94 (95% CI 0.91-0.96)
- In-clinic vs remote target plaque PGA, CCC erythema (0.59-0.85)
- 0.72
- In-clinic vs remote target plaque PGA, CCC induration (0.62-0.82)
- 0.72
- In-clinic vs remote target plaque PGA, CCC scaling (0.48-0.72)
- 0.60
- Machine learning models of patient hand photos identifying clinically diagnosed nail PsO, accuracy
- 0.76
- Digital Jar Open assessment categorising physician-assessed upper extremity involvement (joint tenderness or enthesitis), AUROC (0.47-0.85)
- 0.68
Original publication
Clinical Validation of Digitally Acquired Clinical Data and Machine Learning Models for Remote Measurement of Psoriasis and Psoriatic Arthritis: A Proof-of-Concept Study. J Rheumatol. Published 15 June 2024. doi:10.
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