Predictive Factors of Chemotherapy-Induced Peripheral Neuropathy in Breast Cancer: A Decision Tree Model Approach.

IF 3.2 Q2 ONCOLOGY JCO Global Oncology Pub Date : 2024-11-01 Epub Date: 2024-11-14 DOI:10.1200/GO.24.00160
Juan Adrian Wiranata, Yufi Kartika Astari, Meita Ucche, Susanna Hilda Hutajulu, Dewi Kartikawati Paramita, Dian Caturini Sulistyoningrum, Yudiyanta Siswohadiswasana, Ahmad Asmedi, Mardiah Suci Hardianti, Kartika Widayati Taroeno-Hariadi, Johan Kurnianda, Ibnu Purwanto
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Abstract

Purpose: Chemotherapy-induced peripheral neuropathy (CIPN) poses a substantial challenge in breast cancer (BC) chemotherapy, affecting the patient's quality of life. Recent studies have focused on exploring predictors and patterns of CIPN occurrence. We aimed to develop a prediction model for CIPN occurrence using a classification and regression tree (CART) algorithm.

Methods: In this prospective study of 170 patients with BC undergoing chemotherapy, patient-reported adaptation of the Common Terminology Criteria for Adverse Events version 4.0 was used to assess CIPN occurrence. Multivariable analysis using the CART model was tuned using 10-fold cross-validation to identify baseline predictors for CIPN throughout chemotherapy. A receiver operating characteristic curve analysis was conducted for the CART model. A multivariable logistic regression was conducted from the variables included in the CART model to assess the strength and direction of the association.

Results: The prevalence of CIPN was 64.7% (n = 110). The most decisive predictor of CIPN occurrence in the CART model was the subject's C-reactive protein (CRP) level. CRP level >3.91 mg/dL, BMI >21.85 kg/m2, and a marital status of unmarried have predicted a probability of 100% in CIPN occurrence. The CART model showed an accuracy of 65.9%, sensitivity of 51.7%, specificity of 73.2%, and an area under the curve of 0.705. A CRP level of >3.91 mg/dL and a neutrophil-to-lymphocyte ratio (NLR) of >2.82 are significantly associated with the occurrence of CIPN (odds ratio [OR], 2.01 [95% CI, 1.01 to 4.01]; P = .046, OR, 2.09 [95%, CI, 1.02 to 4.24]; P = .042, respectively).

Conclusion: Baseline CRP, NLR, BMI level, and marital status are significant predictors of CIPN occurrence throughout chemotherapy. Our CART model was better at ruling out individuals who would not experience CIPN. The CART model may provide insight into the future development of individualized patient care and prevention strategies.

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乳腺癌化疗诱发周围神经病变的预测因素:决策树模型方法
目的:化疗诱发的周围神经病变(CIPN)是乳腺癌(BC)化疗中的一大挑战,会影响患者的生活质量。最近的研究主要集中在探索 CIPN 发生的预测因素和模式。我们的目标是利用分类和回归树(CART)算法建立一个 CIPN 发生的预测模型:在这项对170名接受化疗的BC患者进行的前瞻性研究中,采用患者报告的《不良事件通用术语标准4.0版》来评估CIPN的发生情况。使用 10 倍交叉验证对 CART 模型进行了多变量分析,以确定整个化疗过程中 CIPN 的基线预测因素。对 CART 模型进行了接收者操作特征曲线分析。根据CART模型中的变量进行多变量逻辑回归,以评估关联的强度和方向:结果:CIPN的发病率为64.7%(n = 110)。在 CART 模型中,对 CIPN 发生率最具决定性的预测因素是受试者的 C 反应蛋白(CRP)水平。CRP水平>3.91 mg/dL、体重指数>21.85 kg/m2和未婚婚姻状况预测CIPN发生的概率为100%。CART 模型的准确率为 65.9%,灵敏度为 51.7%,特异性为 73.2%,曲线下面积为 0.705。CRP水平>3.91 mg/dL和中性粒细胞与淋巴细胞比值(NLR)>2.82与CIPN的发生显著相关(几率比[OR],2.01 [95% CI,1.01至4.01];P = .046;OR,2.09 [95% CI,1.02至4.24];P = .042):结论:基线CRP、NLR、BMI水平和婚姻状况是整个化疗过程中CIPN发生的重要预测因素。我们的 CART 模型能更好地排除不会出现 CIPN 的个体。CART 模型可为今后制定个体化患者护理和预防策略提供启示。
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来源期刊
JCO Global Oncology
JCO Global Oncology Medicine-Oncology
CiteScore
6.70
自引率
6.70%
发文量
310
审稿时长
7 weeks
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