New scoring system combining computed tomography body composition analysis and inflammatory-nutritional indicators to predict postoperative complications in stage II-III colon cancer.

Background And Aim: 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.

Methods: 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.

Results: 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.

Conclusions: 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.