2026-03-15T20:01:39Z https://tokushima-u.repo.nii.ac.jp/oai

oai:tokushima-u.repo.nii.ac.jp:02012152 2025-04-28T06:01:33Z 1713829974766:1713854681789:1716364509801:1716365035561 1713853213384:1713853295607

Study on prediction of early adverse events by CapeOX therapy in patients with colorectal cancer Prediction of adverse events by CapeOX クミハシ, ユキ クミハシ, ユキ Kumihashi, Yuki カサイ, ヨウヘイ カサイ, ヨウヘイ Kasai, Yohei アカガワ, タクヤ アカガワ, タクヤ Akagawa, Takuya ユアサ, ヤスヒロ ユアサ, ヤスヒロ Yuasa, Yasuhiro イシクラ, ヒサシ イシクラ, ヒサシ Ishikura, Hisashi 10363160 佐藤, 陽一 サトウ, ヨウイチ Sato, Youichi 佐藤 サトウ Sato 陽一 ヨウイチ Youichi open access CapeOX early adverse events multivariate logistic regression nested k-fold cross validation prediction 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. Tokushima University Faculty of Medicine 2024-02 eng journal article VoR 405855 https://tokushima-u.repo.nii.ac.jp/records/2012152 https://doi.org/10.2152/jmi.71.141 10.2152/jmi.71.141 13496867 13431420 AA11166929 The Journal of Medical Investigation 71 1-2 141 147 https://tokushima-u.repo.nii.ac.jp/record/2012152/files/jmi_71_1-2_141.pdf application/pdf 415 KB 2024-07-04