Risk assessment and prediction model for capecitabine-induced chemotherapy-related adverse reactions in colorectal cancer patients
Objective To explore the risk factors of chemotherapy-induced adverse reactions(CIAEs)caused by capecitabine in colorectal cancer(CRC)patients and to construct a risk prediction model for CIAEs.Methods We retrospectively collected data from postoperative CRC patients treated with capecitabine tablets at our hospital between January 2021 and December 2023.Patients were divided into CIAEs and NCIAEs groups based on the presence or absence of CIAEs.Variable differences were screened using t-tests and chi-square tests.Stepwise multivariate logistic regression was employed to identify independent factors influencing CIAEs in CRC patients.Based on these independent risk factors,a risk prediction model for CIAEs in CRC patients was constructed using R software.The model's predictive ability,calibration,and clinical net benefits were evaluated using receiver operating characteristic(ROC)analysis,calibration curves,and decision curves.Results A total of 253 postoperative CRC patients treated with capecitabine were included in this study.Among them,201 patients developed CIAEs,with nausea and vomiting being the most common(69.96％).Multiple logistic regression results indicated that age[OR=3.018,95％CI(1.404,6.487),P=0.005],prognosis nutrition index[OR=0.129,95％CI(0.06,0.278),P＜0.001],and systematic inflammation index[OR=4.074,95％CI(1.316,12.615),P=0.015]were independent risk factors for CIAEs in CRC patients.The constructed risk prediction model demonstrated good predictive ability,calibration,and clinical net benefit.Conclusion The risk prediction model for CIAEs can be used for individualized prediction of CIAEs in CRC patients and serves as a simple and practical tool for CIAE prevention and nursing management.
Colorectal cancerCapecitabineChemotherapy-induced adverse efectsRisk prediction model
万方数据
维普
