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Updated: May 8, 2025
Author Spotlight: Self-Assessment Protocol for Predicting Psoriatic Arthritis in Psoriasis Patients
Published on: March 1, 2024
Early detection of psoriatic arthritis in patients with psoriasis: construction of a multifactorial prediction model
Chunxiao Wang1,2, Sihan Wang1,2, Liu Liu1,2
1Department of Dermatology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Insights
Psoriatic arthritis (PsA) risk in psoriasis patients can be predicted using six key factors. A new calculator helps clinicians identify those needing early intervention for better outcomes.
Area of Science:
- Rheumatology
- Dermatology
- Clinical Prediction Modeling
Background:
- Psoriatic arthritis (PsA) affects a significant portion of psoriasis patients.
- Early identification of PsA risk is vital for preventing poor prognosis.
- Predictive models can aid in timely clinical decision-making.
Purpose of the Study:
- To develop and validate a predictive model for identifying psoriasis patients at high risk of developing PsA.
- To create a user-friendly web-based calculator for clinical application.
Main Methods:
- A derivation cohort of 1,661 psoriasis patients was analyzed.
- Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression were used for variable selection.
- A web-based calculator was developed based on the identified predictors.
Main Results:
- Six independent predictors for PsA development were identified: unexplained swollen joints, history of arthritis, swollen/painful digits, nail involvement, hyperlipidemia, and prolonged topical glucocorticosteroid use.
- Odds ratios and confidence intervals were calculated for each predictor.
- A web-based calculator was created to estimate PsA probability.
Conclusions:
- The developed prediction model and calculator can assist clinicians in identifying psoriasis patients at risk for PsA.
- Early risk assessment facilitates prompt intervention and potentially improves patient prognosis.
- This tool supports evidence-based clinical decision-making in managing psoriasis patients.
Abstract:
Psoriatic arthritis (PsA) affects approximately one in five individuals with psoriasis. Early identification of patients with psoriasis at risk of developing PsA is crucial to prevent poor prognosis. We established a derivation cohort comprising 1,661 patients with psoriasis from 49 hospitals. Clinical and demographic variables ascertained at hospital admission were screened using the Least Absolute Shrinkage and Selection Operator and logistic regression to construct a prediction model and a new web-based calculator. Ultimately, six significant independent predictors were identified: history of unexplained swollen joints (odds ratio [OR]: 5.814, 95% confidence interval [95% CI]: 3.304-10.117; p< 0.001), history of arthritis (OR: 3.543, 95% CI: 1.982-6.246; p< 0.001), history of unexplained swollen and painful fingers or toes (OR: 2.707, 95% CI: 1.463-4.915; p = 0.001), nail involvement (OR: 1.907, 95% CI: 1.235-2.912; p = 0.003), hyperlipidemia (OR: 4.265, 95% CI: 0.921-15.493; p = 0.042), and prolonged topical use of glucocorticosteroids (OR: 1.581, 95% CI: 1.052-2.384, p = 0.028). The web-based calculator derived from this model can assist clinicians in promptly determining the probability of developing PsA in patients with psoriasis, thereby facilitating improved clinical decision-making.
