ArticleFrontiers in public health2025
A nomogram model to predict grade ≥2 acute radiation enteritis in older adult patients with cervical cancer.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Comparative predictive performance of three machine learning algorithms for acute radiation enteritis risk among patients with cervical cancer undergoing radiotherapy: A prospective cohort study.Asia-Pacific journal of oncology nursing · 2026Article
- Mechanistic pathways predictive modeling and translational interventions for radiation enteritis in cervical cancer radiotherapy.Frontiers in cellular and infection microbiology · 2025Review
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10 authors.
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Abstract
Introduction: Acute Radiation Enteritis (ARE) is a common complication of pelvic radiotherapy, with incidence rates exceeding 60% in older adult populations. Especially, grade ≥2 ARE can lead to treatment interruptions, malnutrition, and even septic shock, thereby impairing patients' quality of life and survival outcomes. However, existing risk prediction models are predominantly developed based on younger populations or mixed cohorts, lacking sophisticated evaluation tools tailored to older adult patients. Methods: To establish a predictive nomogram for grade ≥2 ARE in older adult cervical cancer patients undergoing radiotherapy, a retrospective cohort study of 251 older adult cervical cancer patients who received pelvic radiotherapy between January 2018 and March 2024 was conducted. Independent risk factors identified through univariate and multivariate logistic regression were incorporated into a nomogram. The model performance was validated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Results: The incidence of grade ≥2 ARE in our cohort was 61.35%. Independent risk factors included age (OR = 1.881, 95%CI: 1.015-3.484), hypertension (OR = 4.577, 95%CI: 2.402-8.720), diabetes (OR = 5.503, 95%CI: 2.206-13.726), Dmean_R (OR = 1.309, 95%CI: 1.155-1.483), and lactate dehydrogenase-to-albumin ratio (LAR), (OR = 1.872, 95%CI: 1.381-2.538). The nomogram exhibited strong discriminative ability (0.825, 95% CI: 0.774-0.877), and excellent calibration (Hosmer-Lemeshow test, Conclusion: This nomogram integrates both clinical and dosimetric parameters to enable precise risk stratification for grade ≥2 ARE in older adult cervical cancer patients, facilitating personalized prevention strategies and optimized treatment planning.
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