Ningbo College of Health Sciences, No. 51, Xuefu Road, Yinzhou, Ningbo 315100, China.
Biomed Res Int. 2021 Feb 20;2021:6666453. doi: 10.1155/2021/6666453. eCollection 2021.
A prediction model can be developed to predict the risk of cancer-related cognitive impairment in colorectal cancer patients after chemotherapy.
A regression analysis was performed on 386 colorectal cancer patients who had undergone chemotherapy. Three prediction models (random forest, logistic regression, and support vector machine models) were constructed using collected clinical and pathological data of the patients. Calibration and ROC curves and -indexes were used to evaluate the selected models. A decision curve analysis (DCA) was used to determine the clinical utility of the line graph.
Three prediction models including a random forest, a logistic regression, and a support vector machine were constructed. The logistic regression model had the strongest predictive power with an area under the curve (AUC) of 0.799. Age, BMI, colostomy, complications, CRA, depression, diabetes, QLQ-C30 score, exercise, hypercholesterolemia, diet, marital status, education level, and pathological stage were included in the nomogram. The -index (0.826) and calibration curve showed that the nomogram had good predictive ability and the DCA curves indicated that the model had strong clinical utility.
A prediction model with good predictive ability and practical clinical value can be developed for predicting the risk of cognitive impairment in colorectal cancer after chemotherapy.
可以建立一个预测模型来预测结直肠癌患者化疗后与癌症相关的认知障碍风险。
对 386 例接受化疗的结直肠癌患者进行回归分析。使用患者的临床和病理数据构建了三个预测模型（随机森林、逻辑回归和支持向量机模型）。选择模型的校准和 ROC 曲线和 - 指数用于评估。决策曲线分析（DCA）用于确定折线图的临床实用性。
构建了三个预测模型，包括随机森林、逻辑回归和支持向量机。逻辑回归模型具有最强的预测能力，曲线下面积（AUC）为 0.799。年龄、BMI、结肠造口术、并发症、CRA、抑郁、糖尿病、QLQ-C30 评分、运动、高胆固醇血症、饮食、婚姻状况、教育水平和病理分期均包含在列线图中。- 指数（0.826）和校准曲线表明该列线图具有良好的预测能力，DCA 曲线表明该模型具有很强的临床实用性。
可以建立一个具有良好预测能力和实用临床价值的预测模型，用于预测结直肠癌患者化疗后认知障碍的风险。
