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乳腺癌中化疗诱导的外周神经病变的预测因素:一个决策树模型方法

Juan Adrian Wiranata¹, Yufi Kartika Astari², Meita Ucche³

¹Universitas Gadjah Mada Academic Hospital, Yogyakarta, Indonesia.

JCO global oncology

|November 14, 2024

概括

化疗诱导的周围神经病变 (CIPN) 影响了许多乳腺癌患者. 基线C反应蛋白 (CRP),BMI和婚姻状况预测CIPN,有助于识别不太可能发展这种疾病的患者.

科学领域:

在瘤学瘤学.
临床研究临床研究
生物统计学生物统计学

背景情况:

化疗诱导的周围神经病变 (CIPN) 显著影响乳腺癌患者的生活质量.
确定CIPN的预测因子对于主动管理和患者护理至关重要.

研究的目的:

在接受化疗的乳腺癌患者中开发CIPN发生的预测模型.
为了利用CIPN预测的分类和回归树 (CART) 算法.

主要方法:

一项涉及170名接受化疗的乳腺癌患者的前性研究.
患者报告的结果使用常用术语标准对不良事件 (CTCAE) v4.0来评估CIPN.
分类和回归树 (CART) 模型具有10倍的交叉验证,以确定基线预测因素.

主要成果:

CIPN的流行率为64.7%.
通过CART模型识别的关键预测因素包括C反应性蛋白 (CRP) 水平 (>3.91 mg/dL),体重指数 (BMI) (>21.85 kg/m2) 和未婚婚姻状况.
卡特模型的准确性为65.9%,AUC为0.705,更好地排除不会发展CIPN的个体.

结论:

基线CRP,中性粒细胞与淋巴细胞比率 (NLR),BMI和婚姻状况是CIPN的重要预测因素.
卡特模型为CIPN提供了个性化患者护理和预防策略的潜力.
该模型显示在识别患有CIPN风险较低的患者时具有实用性.

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