护理研究2025，Vol.39Issue(22)：3751-3756,6.DOI:10.12102/j.issn.1009-6493.2025.22.004
基于Logistic回归和决策树构建卵巢癌病人营养风险预测模型
Construction of a nutritional risk prediction model for ovarian cancer patients based on Logistic regression and decision tree
摘要
Abstract
Objective:To construct a nutritional risk prediction model for ovarian cancer patients based on logistic regression and classification and regression tree(CART).Methods:A total of 326 ovarian cancer patients admitted to the oncology department of a tertiary hospital in Jiangxi province from November 2023 to September 2024 were selected as the study subjects by convenience sampling.General data of the patients were collected.The nutritional risk of the patients was assessed.A predictive model for nutritional risk in ovarian cancer patients was established based on Logistic regression and decision tree models.Influencing factors were analyzed.Results:The incidence of nutritional risk in ovarian cancer patients was 50.92%.The Logistic regression analysis showed that average monthly income,tumor pathological type,chemotherapy,and hypoproteinemia were influencing factors of nutritional risk in ovarian cancer patients(P<0.05).The decision tree model results indicated that chemotherapy,tumor pathological type,average monthly income,hypoalbuminemia,age,and employment status were influencing factors of nutritional risk in ovarian cancer patients.The area under the receiver operating characteristic curve(AUC)for the Logistic model was 0.800.The accuracy was 0.733.The sensitivity was 0.819.The specificity was 0.644.The Youden's index was 0.463.The AUC for the decision tree model was 0.802.The accuracy was 0.742.The sensitivity was 0.831.The specificity was 0.650.The Youden's index was 0.481.Conclusions:Both the Logistic regression and decision tree models showed good discriminatory ability.The combined use of two models was beneficial for the early identification and management of nutritional risk in ovarian cancer patients.It could provide a reference for the comprehensive prevention,treatment,and rehabilitation management of gynecological malignant tumors.关键词
卵巢癌/营养风险/Logistic回归/决策树/风险预测/影响因素Key words
ovarian cancer/nutritional risk/Logistic regression/decision tree/risk prediction/influencing factors引用本文复制引用
王静,胡诗音,龚倩,李红霞,刘毅,何林生..基于Logistic回归和决策树构建卵巢癌病人营养风险预测模型[J].护理研究,2025,39(22):3751-3756,6.基金项目
国家卫生健康委医院管理研究所医院药学高质量发展研究课题,编号:NIHAYSZX2544 （）
