Nomogram for Predicting Chemotherapy-Induced Nausea and Vomiting for Breast Cancer Patients

Abstract

Chemotherapy-induced nausea and vomiting (CINV) is a common side effect of cancer treatment. The factors influencing CINV in breast cancer patients remain unclear. In this study, we developed a nomogram for predicting the occurrence of CINV in this group using prospective clinical data. We pooled data from multiple studies which focused on the emetogenic chemotherapy. Then, we collected 334 breast cancer patients at Hunan Cancer Hospital (training set) to analyze the demographic and clinical variables. Using multivariate logistic regression, we identified the five significant factors that were associated with CINV: history of CINV, chemotherapy regimen, chemotherapy cycle, metastasis, and symptoms of distress. Then, we construct a prediction nomogram. The external validation set comprised an additional 66 patients. The reliability of the nomogram was assessed by bootstrap resampling. The C-index was 0.78 (95% confidence interval [CI], 0.73-0.85) for the training set and 0.74 (95% CI, 0.62-0.85) for the validation set. Calibration curves showed good concordance between predicted and actual occurrence of CINV. In conclusions, our nomogram model can reliably predict the occurrence of CINV in breast cancer patients based on five significant variables, which might be useful in clinical decision-making.

Keywords: breast cancer; chemotherapy-induced nausea and vomiting (CINV); nomogram; predictive model; risk factors.