中国麻风皮肤病杂志 ›› 2025, Vol. 41 ›› Issue (8): 571-577.doi: 10.12144/zgmfskin202508571

• 论著 • 上一篇    下一篇

司库奇尤单抗治疗中重度斑块状银屑病影响因素分析

何筱君,韩君雅,王德丞,黄亚群,方险峰   

  1. 三峡大学第一临床医学院，宜昌市中心人民医院皮肤病与性病科，湖北宜昌，443003
  • 出版日期:2025-08-15 发布日期:2025-07-31

Analysis of factors influencing the treatment of moderate to severe plaque psoriasis with secukinumab

HE Xiaojun, HAN Junya, WANG Decheng, HUANG Yaqun, FANG Xianfeng   

  1. Department of Dermatology and Venereology, Yichang Central People's Hospital, the First College of Clinical Medical Science, China Three Gorges University, Yichang 443003, China
  • Online:2025-08-15 Published:2025-07-31

PDF (PC)

19

摘要： 目的：分析影响司库奇尤单抗治疗中重度斑块状银屑病患者应答情况的相关因素，并构建列线图预测模型。方法：回顾性分析2019年9月至2024年6月我院就诊的276例中重度斑块状银屑病患者的临床资料、实验室检查结果及皮损特征。根据银屑病皮损面积和严重程度指数（PASI）评分评估治疗效果。采用单因素和多因素Logistic回归分析影响应答的因素，并构建列线图预测模型，通过ROC曲线和Bootstrap内部验证评估模型效能。结果：单因素分析显示，斑块大小、BMI、血糖水平、总胆固醇水平、甘油三酯水平、基线总PASI评分、基线BSA及基线皮损浸润评分等与治疗应答相关（P＜0.05）。多因素Logistic回归分析显示，基线头颈部PASI评分、BMI、血糖水平和甘油三酯水平是独立影响因素（P＜0.05）。基于上述相关因素构建的列线图预测模型ROC曲线面积为0.901（95% CI：0.860~0.943）。Bootstrap内部验证的C指数为0.901（95% CI：0.898~0.904），校准曲线和决策曲线显示模型具有良好的预测效能和临床应用价值。结论：基线头颈部PASI评分、BMI、血糖水平和甘油三酯水平是影响司库奇尤单抗治疗中重度斑块状银屑病患者应答情况的独立相关因素。基于以上变量构建的列线图预测模型预测效能良好，可为银屑病患者的治疗提供指导。

关键词: 银屑病, 司库奇尤单抗, 应答情况, 相关因素, 列线图

Abstract: Objective: To analyze the relevant factors affecting the response of patients with moderate to severe plaque psoriasis treated with secukinumab and establish a nomogram prediction model. Methods: A retrospective analysis was conducted on the clinical data, laboratory test results and lesion characteristics of 276 patients with moderate to severe plaque psoriasis who visited our hospital from September 2019 to June 2024. The therapeutic effect was evaluated based on the Psoriasis Lesion Area and Severity Index (PASI) score. Univariate and multivariate Logistic regression analyses were used to analyze the factors influencing the response, and a nomogram prediction model was constructed. The model efficacy was evaluated through the ROC curve and internal validation of Bootstrap. Results: Univariate analysis showed that plaque size, BMI, blood glucose level, total cholesterol level, triglyceride level, baseline total PASI score, baseline BSA and baseline lesion infiltration score were correlated with treatment response (P＜0.05). Multivariate Logistic regression analysis showed that baseline head and neck PASI score, BMI, blood glucose level and triglyceride level were independent influencing factors (P＜0.05). The area of the ROC curve of the nomogram prediction model constructed based on the above related factors was 0.901 (95% CI: 0.860-0.943). The C-index of Bootstrap's internal validation was 0.901 (95% CI: 0.898-0.904), and the calibration curve and decision curve indicated that the model had good predictive efficacy and clinical application value. Conclusion: Baseline PASI score of the head and neck, BMI, blood glucose level and triglyceride level are independent related factors affecting the response of patients with moderate to severe plaque psoriasis treated with secukinumab. The nomogram prediction model constructed based on the above variables has good prediction efficacy and can provide guidance for the treatment of patients with psoriasis.

Key words: psoriasis, secukinumab, treatment response, relevant factors, nomogram model