Related Experiment Video
Updated: Oct 29, 2026
Measuring Psoriasis Severity at Home
Published on: March 1, 2024
Vitamin D status and systemic inflammatory burden as a predictor of biologic treatment response in psoriasis -A pilot
Kazi Lutfar Rahman1, Kevin McKenna2, Niamh Kearney3
1School of Biomedical Science, Ulster University, Northern Ireland, UK.
Background:
Psoriasis is a chronic, immune-mediated disorder affecting over 60 million people globally. Biologic therapies have improved treatment for moderate-severe disease, yet variability in response and high costs highlight the need for predictive biomarkers to support personalised care.
Objective:
To evaluate whether serum 25-hydroxyvitamin D (25(OH)D), body mass index (BMI), and C-reactive protein (CRP) predict biologic treatment response in moderate-severe psoriasis.
Methods:
This cross-sectional study at Belfast City Hospital, in collaboration with Ulster University, enrolled 120 adults receiving biologic therapy classified by Psoriasis Area and Severity Index (PASI) response. Serum 25(OH)D, BMI, and CRP were compared across responder categories, and logistic regression assessed predictors of outcome.
Results:
Significant variation in BMI, CRP, and 25(OH)D was observed across groups (BMI p = 0.021; CRP p = 0.044; 25(OH)D p < 0.001). Super-Responders had lower BMI and CRP and higher 25(OH)D, whereas Frequent Switchers showed higher BMI and CRP with reduced 25(OH)D. Excellent Responders (PASI ≥90%) had higher 25(OH)D (60.3 nmol/L vs 30.3 nmol/L, p < 0.001) and lower BMI (27.7 kg/m2 vs 32.2 kg/m2, p = 0.013), with 25(OH)D independently predicting PASI ≥90% (OR = 1.032 per nmol/L, p < 0.001). At PASI ≥75%, 25(OH)D remained predictive (OR = 1.016, p = 0.045). CRP was higher in Frequent Switchers (p = 0.009). Higher BMI reduced the odds of Super-Responder status (OR = 0.891, p = 0.027), and higher CRP reduced biologic stability (OR = 0.864, p = 0.012).
Conclusion:
Routine screening of 25(OH)D and CRP with ascertainment of BMI may help inform the development of predictive algorithms to identify patients more or less likely to respond to biologics. This pilot study provides preliminary insights relevant to personalised psoriasis management.
