Nomogram for predicting postoperative recurrence in elderly patients with hepatocellular carcinoma based on...

To develop and validate a nomogram prediction model for postoperative recurrence in elderly patients with hepatocellular carcinoma (HCC) based on multimodal ultrasound parameters.

Clinical data of 299 elderly HCC patients who underwent laparoscopic hepatectomy in our hospital from January 2021 to June 2024 were retrospectively collected. Patients were randomly divided into a training cohort (n = 209) and a validation cohort (n = 90) at a ratio of 7:3. According to tumor recurrence within 1 year after surgery, patients were classified into recurrence and non-recurrence groups. Preoperative multimodal ultrasound parameters and other clinical characteristics were recorded. Multivariate logistic regression analysis was performed to identify independent risk factors for postoperative recurrence. A nomogram prediction model was constructed based on multimodal ultrasound parameters using R software. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

No significant differences were observed in baseline characteristics between the training and validation cohorts (P > 0.05). In the training cohort, the recurrence group had a lower proportion of intact tumor capsules, lower hepatic artery pulsatility index (HA-PI) and resistive index (HA-RI), higher tumor stiffness and strain ratio (SR), shorter washout time (WT), and a higher prevalence of chronic viral hepatitis compared with the non-recurrence group (all P < 0.05). Multivariate logistic regression revealed that non-intact tumor capsule, lower HA-RI, higher SR, shorter WT, and concomitant chronic viral hepatitis were independent risk factors for postoperative recurrence (P < 0.05). Based on these predictors, a nomogram prediction model was developed. ROC analysis showed areas under the curve (AUC) of 0.906 (95% CI: 0.866-0.947) in the training cohort and 0.926 (95% CI: 0.868-0.983) in the validation cohort, indicating excellent discrimination. Calibration curves demonstrated good agreement between predicted and observed outcomes in both cohorts (P > 0.05). DCA demonstrated substantial clinical net benefit across a wide range of threshold probabilities (0.01-0.92 in the training cohort; 0.01-0.96 in the validation cohort).

The nomogram prediction model based on multimodal ultrasound parameters demonstrates favorable predictive performance for postoperative recurrence in elderly HCC patients.