Constructing and validating a prognostic prediction nomogram model for hepatocellular carcinoma patients following
Hanyu Huang1, Fan Yang1,2, Pengcheng Liu1
1State Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, Chongqing, China.
Objective:
To develop and validate a nomogram model based on biological information and conventional imaging indicators for predicting overall survival (OS) in patients with hepatocellular carcinoma (HCC) following high-intensity focused ultrasound (HIFU) treatment.
Methods:
This retrospective study included 407 patients with HCC who received HIFU treatment at the Second Affiliated Hospital of Chongqing Medical University between January 1, 2013, and June 30, 2024. Patients were randomly divided into a training cohort (n = 244) and a validation cohort (n = 163) at a ratio of 6:4. In the training cohort, univariate and multivariate Cox regression analyses were performed to identify independent predictors of OS. A nomogram was subsequently constructed to predict 1, 3, and 5-year survival rates. The predictive performance of the model was evaluated by assessing the concordance index (C-index), area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA). Kaplan-Meier survival curves were plotted to compare survival between high-risk and low-risk groups stratified by the nomogram, thereby validating the model's ability for clinical risk stratification.
Results:
Univariate Cox regression analysis identified 15 factors significantly associated with OS. Multivariate Cox analysis further determined that lymphocyte count, maximum tumor diameter, alpha fetoprotein level, number of tumor lesions, and portal vein invasion were independent risk factors. In the training cohort, the model exhibited a C index of 0.783. The AUCs for 1, 3, and 5-year survival were 0.814, 0.895, and 0.825, respectively. Calibration curves for 1, 3, and 5-year survival showed close agreement between the nomogram-predicted probabilities (0.835, 0.587, 0.40) and the observed survival rates (0.843, 0.586, 0.551), indicating excellent consistency. In the validation cohort, the C-index was 0.701, and the AUCs were 0.778, 0.679, and 0.754, respectively. The calibration curves also demonstrated good agreement between predicted and observed survival rates, reflecting acceptable consistency. In comparison, the 8th edition AJCC staging system yielded C indices below 0.68 in both cohorts, and its calibration curves showed suboptimal fit.
Conclusion:
The nomogram model developed in this study can effectively predict the OS rates in HCC patients following HIFU treatment, potentially improving therapeutic strategies and promoting personalized treatment approaches.