通讯作者: 常鑫, 1732651699@qq.com

DOI：10.12201/bmr.202604.00056

Development and Validation of a Nomogram for Predicting Radiation Dermatitis in Cervical Cancer Radiotherapy

• 摘要：目的：调查宫颈癌患者放疗期间放射性皮炎(radiation dermatitis, RD)的发生情况,构建并验证宫颈癌放疗患者 RD 列线图预测模型。方法：前瞻性选取 2025 年 9 月至 12 月于广西医科大学附属肿瘤医院行放疗的宫颈癌患者 110 例,分为 RD 组和非 RD 组。采用单因素分析筛选潜在影响因素,结合 LASSO 回归与二元 Logistic 回归进行变量筛选,通过比较不同变量组合模型的区分度和校准度,结合模型简约性确定最终预测模型,采用 Bootstrap 法进行内部验证,评估模型的区分度、校准度和临床实用性。结果：共纳入 110 例宫颈癌患者,RD 发生率为 82.8%(91/110)。预后营养指数(prognostic nutritional index, PNI)是宫颈癌放疗患者 RD 的独立影响因素,其最佳截断值为 46.525。经分阶段变量筛选,最终纳入年龄、手术及 PNI 构建列线图预测模型。模型验证结果显示：AUC 为 0.840(95% CI: 0.744～0.936)；Hosmer-Lemeshow 检验结果为 = 6.965(P = 0.540)；校准曲线与理想曲线基本重合,Brier 评分为 0.1066；10%～40% 预测范围内模型净获益良好。结论：基于年龄、手术和 PNI 构建的宫颈癌放疗患者 RD 列线图预测模型具有良好的预测效能与临床实用性,有助于临床早期识别高危人群并进行干预。

  关键词： 宫颈癌; 放射性皮炎; 影响因素; 预后营养指数; 风险预测模型; 列线图

   

  Abstract: Objective: To investigate the incidence of radiation dermatitis (RD) in patients with cervical cancer during radiotherapy, and to construct and validate a nomogram prediction model for RD in this population. Methods: A total of 110 patients with cervical cancer who underwent radiotherapy at the Affiliated Tumor Hospital of Guangxi Medical University from September to December 2025 were prospectively enrolled and divided into RD and non-RD groups. Univariate analysis was used to identify potential influencing factors. Variable selection was performed using LASSO regression combined with binary logistic regression. The final prediction model was determined by comparing the discrimination and calibration of models with different variable combinations while considering model parsimony. Internal validation was conducted using the Bootstrap method, and the models discrimination, calibration, and clinical utility were evaluated. Results: A total of 110 patients with cervical cancer were included, and the incidence of RD was 82.8% (91/110). The prognostic nutritional index (PNI) was an independent influencing factor for RD in patients undergoing radiotherapy for cervical cancer, with an optimal cutoff value of 46.525. Following staged variable selection, age, surgery, and PNI were ultimately included in the nomogram prediction model. Model validation results showed an AUC of 0.840 (95% CI: 0.744–0.936); the Hosmer–Lemeshow test yielded χ2 = 6.965 (P = 0.540); the calibration curve closely aligned with the ideal curve, with a Brier score of 0.1066; and the model demonstrated good net benefit within the 10%–40% predicted risk range. Conclusion: The nomogram prediction model for RD in patients undergoing radiotherapy for cervical cancer, constructed based on age, surgery, and PNI, exhibits good predictive performance and clinical utility, facilitating early identification of high-risk individuals and timely intervention in clinical practice.

  Key words: Cervical cancer; Radiation dermatitis; Influencing factors; Prognostic nutritional index; Risk prediction model; Nomogram

  提交时间：2026-04-08

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• 序号	提交日期	编号	操作
  1	2026-03-29	10.12201/bmr.202604.00056V1	下载

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