Predictive value and model construction of preoperative nutritional indexes for postoperative leakage in gastric cancer.

OBJECTIVE

We aimed to explore the predictive significance of the nutritional indexes in the occurrence of postoperative leakage after gastrectomy, aiming to develop and validate a predictive nomogram for assessing the risk of these complications.

METHODS

Patients undergoing radical gastrectomy for gastric cancer were studied, using data from The Sixth Affiliated Hospital of Sun Yat-sen University (2019-2022, n = 1075) for nomogram development and an external cohort from Sun Yat-sen University Cancer Center (2022, n = 286) for validation. The model, focusing on postoperative leakage, was constructed through univariate and backward stepwise regression. The performance of nomogram was assessed using the receiver operating characteristic (ROC) curve, calibration plots, decision curve analysis (DCA), and clinical impact curves (CIC).

RESULTS

The incidence rates of postoperative leakage were 6.51% in the training cohort and 6.71% in the external validation cohort, respectively. The nomogram effectively identifies critical factors influencing postoperative leakage risk, including NRS-2002 score, SFMAI, VSR, blood loss, intraoperative time, type of reconstruction, and Lauren type. The areas under the curve (AUC) for the development and external validation cohorts were 0.763 and 0.761, respectively, demonstrating acceptable predictive accuracy. The validation study showed the nomogram's satisfactory calibration, and both DCA and CIC confirmed its significant clinical utility.

CONCLUSIONS

The nomogram offers an efficient and precise tool for initial screening, effectively identifying individuals at elevated risk for postoperative leakage.