Study on prediction of early adverse events by CapeOX therapy in patients with colorectal cancer

CapeOX is a regimen used as postoperative adjuvant chemotherapy for the treatment of advanced recurrent colorectal cancer. If early adverse events occur, treatment may not progress as planned and further dose reduction may be necessary. In this study, we investigated whether pre-treatment medical records could be used to predict adverse events in order to prevent adverse events caused by CapeOX treatment. The 178 patients were classified into two groups (97 in the adverse event positive group and 81 in the adverse event-negative group) based on withdrawal or postponement of four or fewer courses. In univariate analysis, age, height, weight, body surface area (BSA), creatinine clearance, muscle mass, and lean body mass were associated with early adverse events (P < 0.05). The area under the receiver operating characteristic curve obtained by Stepwise logistic regression analysis using the Akaike information criterion method was 0.832. For nested k-fold cross validation, the accuracy rates of the support vector machine, random forest, and logistic regression algorithms were 0.71, 0.70, and 0.75, respectively. The results of the present study suggest that a logistic regression prediction model may be useful in predicting early adverse events caused by CapeOX therapy in patients with colorectal cancer.