Development and external validation of a prediction model for the risk of relapse in psoriasis after discontinuation of biologics - Huang, Shan; Chen, Bailin; Qi, Yiming; Duan, Xingwu; Bai, Yanping (Frontiers in Medicine, 2024)
Background: Some patients with psoriasis experience relapses shortly after discontinuation of biologics. However, there is a lack of risk prediction tools to identify those at high risk of relapse.Objective: To develop and validate a risk prediction model for psoriasis relapse after biologics discontinuation.Methods: Publications from PubMed, EMBASE, Medline, and the Cochrane Library were systematically searched and meta-analyses were conducted to identify risk factors for psoriasis relapse after biologics discontinuation. Statistically significant risk factors were identified and used to create a risk assessment model weighted by the impact of each factor. The model was externally validated using a cohort of 416 Chinese psoriasis patients.Results: Eight studies (N=2066) were included in the meta-analysis. Body mass index (BMI), smoking, disease duration, comorbid psoriatic arthritis (PsA), remission speed and extent during treatment, history of biologic therapy, and therapy duration were identified as correlates of relapse in the meta-analysis and were incorporated into the prediction model. The median age of the 416 patients in the validation cohort was 41.5 (IQR 32, 53) years, with 63% male, and a baseline PASI score of 15.4 (IQR 10.5,21). It was verified that the area under the curve (AUC) of the prediction model was 0.796 (95% CI: 0.753-0.839), with an optimal cut-off value of 11.25 points, sensitivity of 65.1%, and specificity of 82.2%. Conclusion: Multivariate models using available clinical parameters can predict relapse risk in psoriasis patients after biologics discontinuation. Early individual identification of patients at risk of relapse, and screening of candidate cohorts for long-term treatment or dose reduction may benefit both patients and physicians.