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

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.

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.

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).

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.