A novel nomogram based on clinical features and laboratory parameters to predict biologic-refractory psoriasis...

Biologic-refractory psoriasis has emerged as an area of unmet need in a landscape of generally well-controlled disease. The study aimed to establish a predictive model grounded in the clinical features and laboratory parameters to assess the risk of biologic-refractory patient (BRP) prior to initiating biologic therapy.

Biologic-naïve psoriasis patients who initiated their first biologic at the Department of Dermatology of Xiangya Hospital were included and randomized into training and validation sets in a 6:4 ratio. Logistic regression and lasso analysis were performed to screen the risk variables for BRP status.

Seven hundred and forty-two psoriatic patients comprising 40 BRPs were included. Body mass index, nonalcoholic fatty liver disease, psoriasis area and severity index, direct bilirubin level, indirect bilirubin level, and erythrocyte sedimentation rate level were identified as predictive factors of BRP. Nomogram models incorporating these factors demonstrated excellent discrimination capabilities with areas under the curve of 0.915 (95%CI, 0.846-0.916) in the training cohort and 0.933 (95%CI, 0.884-0.934) in the validation cohort. Calibration curves indicated good calibration for both cohorts, and decision curve analysis (DCA) revealed the excellent clinical utility of the predictive model.

We developed the nomogram that integrated clinical features and laboratory parameters, providing a convenient and efficient method for predicting BRP risk.