医学
列线图
接收机工作特性
结直肠癌
内科学
阶段(地层学)
队列
癌症
置信区间
多元分析
曲线下面积
回顾性队列研究
优势比
体质指数
单变量分析
外科
生物
古生物学
作者
Zheng Ma,Ruiqing Liu,Huasheng Liu,Longbo Zheng,Xuefeng Zheng,Yinling Li,Haoyu Cui,Qin Chen,Jilin Hu
摘要
Postoperative complications are important clinical outcomes for colon cancer patients. This study aimed to investigate the predictive value of inflammatory-nutritional indicators combined with computed tomography body composition on postoperative complications in patients with stage II-III colon cancer.We retrospectively collected data from patients with stage II-III colon cancer admitted to our hospital from 2017 to 2021, including 198 patients in the training cohort and 50 patients in the validation cohort. Inflammatory-nutritional indicators and body composition were included in the univariate and multivariate analyses. Binary regression was used to develop a nomogram and evaluate its predictive value.In the multivariate analysis, the monocyte-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), nutritional risk score (NRS), skeletal muscle index (SMI), and visceral fat index (VFI) were independent risk factors for postoperative complications of stage II-III colon cancer. In the training cohort, the area under the receiver operating characteristic curve of the predictive model was 0.825 (95% confidence interval [CI] 0.764-0.886). In the validation cohort, it was 0.901 (95% CI 0.816-0.986). The calibration curve showed that the prediction results were in good agreement with the observational results. Decision curve analysis showed that colon cancer patients could benefit from the predictive model.A nomogram combining MLR, SII, NRS, SMI, and VFI with good accuracy and reliability in predicting postoperative complications in patients with stage II-III colon cancer was established, which can help guide treatment decisions.
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