The pre- and postoperative nomograms to predict the textbook outcomes of patients who underwent hepatectomy for hepatocellular carcinoma.

Background and aims: An increasing number of studies have confirmed that non-textbook outcomes (non-TO) are a risk factor for the long-term outcome of malignant tumors. It is particularly important to identify the predictive factors of non-TO to improve the quality of surgical treatment. We attempted to construct two nomograms for preoperative and postoperative prediction of non-TO after laparoscopic hepatectomy for hepatocellular carcinoma (HCC). Methods: Patients who underwent curative-intent hepatectomy for HCC between 2014 and 2021 at two Chinese hospitals were analyzed. Using univariate and multivariate analyses, the independent predictors of non-TO were identified. The prediction accuracy is accurately measured by the receiver operating characteristic (ROC) curve and calibration curve. ROC curves for the preoperative and postoperative models, Child-Pugh grade, BCLC staging, and 8th TNM staging were compared relative to predictive accuracy for non-TO. Results: Among 515 patients, 286 patients (55.5%) did not achieve TO in the entire cohort. Seven and eight independent risk factors were included in the preoperative and postoperative predictive models by multivariate logistic regression analysis, respectively. The areas under the ROC curves for the postoperative and preoperative models, Child-Pugh grade, BCLC staging, and 8th TNM staging in predicting non-TO were 0.762, 0.698, 0.579, 0.569, and 0.567, respectively. Conclusion: Our proposed preoperative and postoperative nomogram models were able to identify patients at high risk of non-TO following laparoscopic resection of HCC, which may guide clinicians to make individualized surgical decisions, improve postoperative survival, and plan adjuvant therapy against recurrence.