Development and external validation of a prediction model for the risk of relapse in psoriasis after discontinuation of biologics

BackgroundSome 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.ObjectiveTo develop and validate a risk prediction model for psoriasis relapse after biologics discontinu...

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Main Authors: Shan Huang, Bailin Chen, Yiming Qi, Xingwu Duan, Yanping Bai
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-11-01
Series:Frontiers in Medicine
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Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2024.1488096/full
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author Shan Huang
Shan Huang
Bailin Chen
Yiming Qi
Xingwu Duan
Yanping Bai
author_facet Shan Huang
Shan Huang
Bailin Chen
Yiming Qi
Xingwu Duan
Yanping Bai
author_sort Shan Huang
collection DOAJ
description BackgroundSome 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.ObjectiveTo develop and validate a risk prediction model for psoriasis relapse after biologics discontinuation.MethodsPublications 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.ResultsEight 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%.ConclusionMultivariate 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.
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spelling doaj-art-89c95f59a85d4acfb2b4c65b37655b6d2025-08-20T02:22:40ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2024-11-011110.3389/fmed.2024.14880961488096Development and external validation of a prediction model for the risk of relapse in psoriasis after discontinuation of biologicsShan Huang0Shan Huang1Bailin Chen2Yiming Qi3Xingwu Duan4Yanping Bai5Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, ChinaGraduate School, Beijing University of Chinese Medicine, Beijing, ChinaGraduate School, Beijing University of Chinese Medicine, Beijing, ChinaGraduate School, Beijing University of Chinese Medicine, Beijing, ChinaDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, ChinaDepartment of Dermatology, China-Japan Friendship Hospital, National Center for Integrative Chinese and Western Medicine, Beijing, ChinaBackgroundSome 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.ObjectiveTo develop and validate a risk prediction model for psoriasis relapse after biologics discontinuation.MethodsPublications 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.ResultsEight 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%.ConclusionMultivariate 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.https://www.frontiersin.org/articles/10.3389/fmed.2024.1488096/fullpsoriasisbiologicsprediction modelrisk factorrelapse
spellingShingle Shan Huang
Shan Huang
Bailin Chen
Yiming Qi
Xingwu Duan
Yanping Bai
Development and external validation of a prediction model for the risk of relapse in psoriasis after discontinuation of biologics
Frontiers in Medicine
psoriasis
biologics
prediction model
risk factor
relapse
title Development and external validation of a prediction model for the risk of relapse in psoriasis after discontinuation of biologics
title_full Development and external validation of a prediction model for the risk of relapse in psoriasis after discontinuation of biologics
title_fullStr Development and external validation of a prediction model for the risk of relapse in psoriasis after discontinuation of biologics
title_full_unstemmed Development and external validation of a prediction model for the risk of relapse in psoriasis after discontinuation of biologics
title_short Development and external validation of a prediction model for the risk of relapse in psoriasis after discontinuation of biologics
title_sort development and external validation of a prediction model for the risk of relapse in psoriasis after discontinuation of biologics
topic psoriasis
biologics
prediction model
risk factor
relapse
url https://www.frontiersin.org/articles/10.3389/fmed.2024.1488096/full
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