Phase angle is a predictor for postoperative complications in colorectal cancer

Abstract

AimThe aim of this study was to develop a validated nomogram to predict the risk of postoperative complications in colorectal cancer (CRC) patients by analyzing the factors that contribute to these complications.MethodsWe retrospectively collected clinical information on patients who underwent CRC surgery at a single clinical center from January 2021 to December 2021. Univariate and multivariate logistic regression analysis to identify independent risk factors for postoperative complications and to develop a predictive model. A receiver operating characteristic (ROC) curve was used to calculate the area under the curve (AUC) to assess the predicted probability. Calibration curve was drawn to compare the predicted probability of the nomogram with the actual probability, and decision curve analysis (DCA) was employed to evaluate the clinical utility of the nomogram.ResultsA total of 190 CRC patients were included in this study. We retrospectively collected baseline information, clinical information, surgical information, and nutrition-related indicators for all patients. Through multivariate logistic regression analysis, preoperative albumin (p = 0.041, OR = 0.906, 95% CI = 0.824–0.996), surgical time (p = 0.009, OR = 1.006, 95% CI = 1.001–1.010), waistline (p = 0.049, OR = 1.011, 95% CI = 1.002–1.020) and phase angle (PA) (p = 0.022, OR = 0.615, 95% CI = 0.405–0.933) were identified as independent risk factors for postoperative complications in CRC, and a nomogram prediction model was established using the above four variables. The AUC of 0.706 for the ROC plot and the high agreement between predicted and actual probabilities in the calibration curves suggested that the prediction model has good predictive power. The DCA also confirmed the good clinical performance of the nomogram.ConclusionThis study developed a nomogram to predict the risk of postoperative complications in CRC patients, providing surgeons with a reliable reference to personalized patient management in the perioperative period and preoperative nutritional interventions.