Development and validation of a postoperative infection nomogram for hepatitis B-associated hepatocellular carcinoma patients after hepatectomy / 中华肝胆外科杂志

ABSTRACT

Objective:To develop and validate a postoperative infection nomogram of hepatitis B-associated hepatocellular carcinoma (HCC) after hepatectomy.Methods:Clinical data of 229 patients with HCC undergoing hepatectomy at the Department of Hepatobiliary Surgery of Tianjin Third Central Hospital from January 2014 to December 2022 were retrospectively analyzed, including 174 males and 55 females, aged (58.2±11.4) years. LASSO regression analysis screened the factors associated with hepatitis B-associated HCC infection after hepatectomy, which were further incorporated into multivariate logistic regression analysis. A nomographic prediction model was established based on the results of multivariate logistic regression analysis. Concordance index (C-index), calibration curve and receiver operating characteristic (ROC) curve were used to evaluate the model, and decision curve analysis (DCA) was used to analyze the clinical applicability of the model. Internal validation of the model was performed using bootstrap method.Results:A total of nine variables were screened as factors associated with the postoperative infections using LASSO regression, including gender, smoking history, body mass index (BMI), serum level of alpha fetoprotein, resection fashion (anatomical or non-anatomical), intraoperative blood loss, surgical method (laparoscopy or open), serum level of creatinine, and postoperative biliary fistula. Multivariate logistic regression analysis showed that BMI, resection fashion, intraoperative blood loss >500 ml, and postoperative biliary fistula were risk factors for postoperative infection (all P<0.05). Based on the above risk factors, a postoperative infection nomogram of hepatitis B-associated HCC after hepatectomy was established. The C-index was 0.839 (95% CI 0.768-0.910), and the area under ROC curve was 0.853 (95% CI 0.795-0.912), indicating that the model had a good predictive ability. The calibration curve was basically consistent with the ideal curve. The DCA showed that the model had a good clinical applicability. Internal validation C-index was 0.829 (95% CI 0.766-0.892). Conclusion:The nomogram based on BMI, surgical resection fashion, intraoperative blood loss >500 ml, and postoperative biliary fistula has a high predictive accuracy and can be used to predict postoperative infections after hepatectomy for HCC.