A prediction nomogram for postoperative gastroparesis syndrome in right colon cancer: a retrospective study.

Purpose: To investigate the high-risk factors for postoperative gastroparesis syndrome (PGS) in right colon cancer and to build a prediction nomogram for personalized prediction of PGS.

Methods: Our study retrospectively analyzed 361 patients with right colon cancer who underwent right hemicolectomy at The First Hospital of Putian City in Fujian Province, China and who were hospitalized between January 2012 and July 2022. Multivariate logistic regression was used to determine the independent risk factors for PGS and to establish a nomogram model. Furthermore, discrimination, calibration, and clinical benefits were used to evaluate the model.

Results: The multivariate logistic regression revealed that dissection of the subpyloric lymph nodes (No. 206 lymph node) (OR 5.242, P = 0.005), preoperative fasting blood glucose level (OR 3.708, P = 0.024), preoperative albumin level (OR 3.503, P = 0.020), and total operative time (OR 4.648, P = 0.014) were independent risk factors for PGS. Based on the above four factors, the area under the ROC curve (AUC) and C-index of the nomogram were 0.831. The prediction nomogram's calibration curve was closer to the ideal diagonal, and the Hosmer‒Lemeshow test indicated that the nomogram fit well (P = 0.399). Moreover, the decision curve analysis revealed that the model can present better clinical benefits when the threshold probability was between 1 and 28%, and the internal validation verified the dependability of the model (C-index = 0.948).

Conclusions: A risk prediction nomogram based on perioperative factors provided the physician with a simple, visual, and efficient tool for the prediction and management of PGS in right colon cancer.