European journal of medical research · 2025
High-risk factors and predictive models for hemorrhagic chronic radiation proctitis.
СтатьяНазвание и аннотация: Перевод в очереди
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Liao Zhongli, Hu Xiaogang, Hu Liuling, Yang Jian
Аннотация
INTRODUCTION: Hemorrhagic chronic radiation proctitis (CRP) is a common and challenging complication after pelvic radiation therapy. Identifying high-risk factors, predicting its occurrence, and optimizing radiotherapy plans are key to preventing hemorrhagic CRP. This study retrospectively examined potential risk factors and developed a nomogram to predict its onset.
METHODS: This retrospective study included cervical carcinoma patients who received pelvic radiotherapy at Chongqing University Cancer Hospital from March 2014 to December 2021. Hemorrhagic CRP was diagnosed by colonoscopy. Logistic regression identified factors for a nomogram model, which was evaluated using ROC curve, calibration curve, and decision curve analysis.
RESULTS: Among 221 patients, 125 were diagnosed with hemorrhagic CRP, occurring at a median of 14.45 months after pelvic radiotherapy. Age (≥ 54 years), weight (< 52 kg), and radiation dose (≥ 72 Gy) were identified as risk factors. A nomogram was developed, with AUC values of 0.741 and 0.74 in the training and validation cohorts. Decision and clinical impact curves showed the model's benefit over a probability range of 0.25 to 0.85 in both sets.
CONCLUSION: In this study, we constructed and developed a nomogram for predicting hemorrhagic CRP risk. The good results in calibration curves, ROC curve analysis, and decision curves indicated that the nomogram had promise for clinical application. It may serve as a reference for radiologists in designing radiotherapy plan to help mitigate the risk of hemorrhagic CRP.
METHODS: This retrospective study included cervical carcinoma patients who received pelvic radiotherapy at Chongqing University Cancer Hospital from March 2014 to December 2021. Hemorrhagic CRP was diagnosed by colonoscopy. Logistic regression identified factors for a nomogram model, which was evaluated using ROC curve, calibration curve, and decision curve analysis.
RESULTS: Among 221 patients, 125 were diagnosed with hemorrhagic CRP, occurring at a median of 14.45 months after pelvic radiotherapy. Age (≥ 54 years), weight (< 52 kg), and radiation dose (≥ 72 Gy) were identified as risk factors. A nomogram was developed, with AUC values of 0.741 and 0.74 in the training and validation cohorts. Decision and clinical impact curves showed the model's benefit over a probability range of 0.25 to 0.85 in both sets.
CONCLUSION: In this study, we constructed and developed a nomogram for predicting hemorrhagic CRP risk. The good results in calibration curves, ROC curve analysis, and decision curves indicated that the nomogram had promise for clinical application. It may serve as a reference for radiologists in designing radiotherapy plan to help mitigate the risk of hemorrhagic CRP.