Interactive model for predicting the oncological outcome of patients with early-stage huge hepatocellular carcinoma after hepatectomy: a multicenter population-based study

This study was aimed at exploring the independent risk parameters and developing an interactive model for predicting the cancer-specific survival (CSS) of ES-HHCC. Data from patients with ES-HHCC who underwent hepatectomy were collected. The dimensionality of the clinical features was reduced by least absolute shrinkage and selection operator regression and further screened as predictors of CSS by Cox regression. Then, an interactive prediction model was developed and validated. Among the 514 screened patients, 311 and 203 of them were assigned into the training and validation cohort, respectively. Six independent variables, including alpha-fetoprotein, cirrhosis, microvascular invasion, satellite, tumor morphology, and tumor diameter, were identified and incorporated into the prediction model for CSS. The model achieved C-indices of 0.724 and 0.711 in the training and validation cohorts, respectively. Calibration curves showed general consistency in both cohorts. Compared with single predictor, the model had a better performance and greater benefit according to the time-independent receiver operating characteristic curve and decision curve analysis (P <  0.05). The calculator owned satisfactory accuracy and flexible operability for predicting the CSS of ES-HHCC, which could serve as a practical tool to stratify patients with different risks, and guide decision-making.
Source: Updates in Surgery - Category: Surgery Source Type: research