Development and validation of a predictive model for radiation dermatitis risk in cancer patients during radiotherapy

To develop a risk prediction model for radiation dermatitis in cancer patients during radiotherapy, validate its predictive performance, and provide a theoretical basis for reducing the incidence of radiation dermatitis in clinical practice. A prospective study design was adopted. A convenience sampling method was used to select 296 cancer patients who received radiotherapy at Fudan Tumor Minhang Branch from January 2023 to January 2025 as the modeling group. Based on the occurrence of radiation dermatitis, patients were divided into a radiation dermatitis group ( n = 150) and a non-radiation dermatitis group ( n = 146). Data from the two groups were compared, and a risk prediction model was constructed based on the results of logistic regression analysis. The predictive performance of the model was evaluated using the area under the receiver operating characteristic (ROC) curve. From February to June 2025, 126 cancer patients receiving radiotherapy were selected as the validation group for external validation of the model. Among the 296 patients in the modeling group, the mean age of the radiation dermatitis group was 61.45 ± 9.67 years, while that of the non-radiation dermatitis group was 57.06 ± 10.78 years. The incidence of radiation dermatitis was 50.67% (150/296) in the modeling group and 42.9% (54/126) in the validation group. The final predictive variables included in the model were age (OR = 1.030, 95% CI 1.004–1.057), total radiation dose (OR = 1.035, 95% CI 1.002–1.069), body mass index (BMI) (OR = 1.255, 95% CI 1.141–1.380), serum retinol (OR = 1.035, 95% CI 1.016–1.054), and serum albumin (OR = 3.078, 95% CI 1.759–5.385) (all P < 0.05). The area under the ROC curve for the prediction model was 0.792 (95% CI 0.741–0.843), with a sensitivity of 0.80, specificity of 0.78, and Youden index of 0.58. Validation results showed an area under the ROC curve of 0.768 (95% CI: 0.710–0.826), a maximum Youden index of 0.56, sensitivity of 0.78, specificity of 0.78, and an accuracy of 78.6%, indicating good predictive performance. The risk prediction model for radiation dermatitis in cancer patients during radiotherapy developed in this study demonstrates good predictive performance. It can effectively predict the incidence of radiation dermatitis during radiotherapy and provides a reference for clinical staff in designing and implementing intervention measures.

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Journal
European journal of medical research
Published
2026-07-16
DOI
https://doi.org/10.1186/s40001-026-04797-9
Primary Topic
Effects of Radiation Exposure
Type
article
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article

Development and validation of a predictive model for radiation dermatitis risk in cancer patients during radiotherapy

Author Fengrong Tang, Aihong Wan, Xiaochen Mo, Lei Zhang
European journal of medical research
Effects of Radiation Exposure
article

Development and validation of a predictive model for radiation dermatitis risk in cancer patients during radiotherapy

Author Fengrong Tang, Aihong Wan, Xiaochen Mo, Lei Zhang
article en

Abstract

To develop a risk prediction model for radiation dermatitis in cancer patients during radiotherapy, validate its predictive performance, and provide a theoretical basis for reducing the incidence of radiation dermatitis in clinical practice. A prospective study design was adopted. A convenience sampling method was used to select 296 cancer patients who received radiotherapy at Fudan Tumor Minhang Branch from January 2023 to January 2025 as the modeling group. Based on the occurrence of radiation dermatitis, patients were divided into a radiation dermatitis group ( n = 150) and a non-radiation dermatitis group ( n = 146). Data from the two groups were compared, and a risk prediction model was constructed based on the results of logistic regression analysis. The predictive performance of the model was evaluated using the area under the receiver operating characteristic (ROC) curve. From February to June 2025, 126 cancer patients receiving radiotherapy were selected as the validation group for external validation of the model. Among the 296 patients in the modeling group, the mean age of the radiation dermatitis group was 61.45 ± 9.67 years, while that of the non-radiation dermatitis group was 57.06 ± 10.78 years. The incidence of radiation dermatitis was 50.67% (150/296) in the modeling group and 42.9% (54/126) in the validation group. The final predictive variables included in the model were age (OR = 1.030, 95% CI 1.004–1.057), total radiation dose (OR = 1.035, 95% CI 1.002–1.069), body mass index (BMI) (OR = 1.255, 95% CI 1.141–1.380), serum retinol (OR = 1.035, 95% CI 1.016–1.054), and serum albumin (OR = 3.078, 95% CI 1.759–5.385) (all P < 0.05). The area under the ROC curve for the prediction model was 0.792 (95% CI 0.741–0.843), with a sensitivity of 0.80, specificity of 0.78, and Youden index of 0.58. Validation results showed an area under the ROC curve of 0.768 (95% CI: 0.710–0.826), a maximum Youden index of 0.56, sensitivity of 0.78, specificity of 0.78, and an accuracy of 78.6%, indicating good predictive performance. The risk prediction model for radiation dermatitis in cancer patients during radiotherapy developed in this study demonstrates good predictive performance. It can effectively predict the incidence of radiation dermatitis during radiotherapy and provides a reference for clinical staff in designing and implementing intervention measures.

European journal of medical research
Fudan University Shanghai Cancer Center (CN), Shanghai Sixth People's Hospital (CN)
Good health and well-being
Openalex Percentile: Top 9%
Effects of Radiation Exposure
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