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使用随机森林模型分析影响乳腺癌患者化疗引起的周围神经病变的因素。

Analysis of factors influencing chemotherapy-induced peripheral neuropathy in breast cancer patients using a random forest model.

作者信息

Xu Huiqian, Li Hong, Fan Yijing, Wang Yaqi, Li Zeyuan, Zhou Lizhi, Hao Xijun

机构信息

North China University of Science and Technology, Tangshan, 063210, China.

Tangshan People's Hospital, Tangshan, 063000, China.

出版信息

Breast. 2025 Jun;81:104457. doi: 10.1016/j.breast.2025.104457. Epub 2025 Apr 11.

Abstract

OBJECTIVE

This study aimed to analyze the factors influencing chemotherapy-induced peripheral neuropathy (CIPN) in breast cancer patients, identify modifiable factors, and provide a theoretical basis for targeted interventions.

METHODS

A total of 542 patients with breast cancer who were hospitalized for chemotherapy in multiple hospitals from September 2022 to September 2023 were selected as the study objects. Data were collected using questionnaires covering demographic characteristics, disease-related information, lifestyle, and psychological status. Lasso-logistic regression was employed to identify influencing factors, and a random forest model was used to rank the importance of variables.

RESULTS

Lasso-logistic regression analysis identified age, BMI, cumulative chemotherapy dose, hypertension, physical activity level, and depression as significant factors associated with CIPN (P < 0.05). The variable importance ranking from the random forest model was as follows: age, BMI, cumulative chemotherapy dose, physical activity, hypertension, and depression.

CONCLUSION

Early identification of high-risk CIPN patients is crucial for guiding clinical nursing practices. These findings provide a foundation for the management and intervention of CIPN in breast cancer patients.

摘要

目的

本研究旨在分析影响乳腺癌患者化疗引起的周围神经病变(CIPN)的因素,识别可改变的因素,并为针对性干预提供理论依据。

方法

选取2022年9月至2023年9月期间在多家医院住院接受化疗的542例乳腺癌患者作为研究对象。通过问卷调查收集患者的人口统计学特征、疾病相关信息、生活方式和心理状态等数据。采用Lasso逻辑回归分析确定影响因素,并使用随机森林模型对变量的重要性进行排序。

结果

Lasso逻辑回归分析确定年龄、体重指数(BMI)、累积化疗剂量、高血压、身体活动水平和抑郁是与CIPN相关的显著因素(P<0.05)。随机森林模型的变量重要性排序如下:年龄、BMI、累积化疗剂量、身体活动、高血压和抑郁。

结论

早期识别CIPN高危患者对指导临床护理实践至关重要。这些发现为乳腺癌患者CIPN的管理和干预提供了依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6478/12144932/250f762765ec/gr1.jpg

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