Development of a prognostic scoring model for predicting the survival of elderly patients with hepatocellular carcinoma

BACKGROUND: The number of elderly hepatocellular carcinoma (HCC) patients is increasing, and precisely assessing of the prognosis of these patients is necessary. We developed a prognostic scoring model to predict survival in elderly HCC patients. METHODS: We extracted data from 4,076 patients ≥65 years old from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided them into training and validation groups. Cox regression analysis was used to screen for meaningful independent prognostic factors. The receiver operating characteristic curve reflected the model’s discrimination power. RESULTS: Age, race, American Joint Committee on Cancer stage, degree of tumour differentiation, tumour size, alpha-fetoprotein and tumour therapy were independent prognostic factors for survival in elderly HCC patients. We developed a prognostic scoring model based on the seven meaningful variables to predict survival in elderly HCC patients. The AUCs of the model were 0.805 (95% CI [0.788–0.821]) and 0.788 (95% CI [0.759–0.816]) in the training and validation groups, respectively. We divided the patients into low-risk groups and high-risk groups according to the optimal cut-off value. The Kaplan–Meier survival curve showed that in the training and validation groups, the survival rate of the low-risk group was significantly higher than that of the high-risk group (P < 0.001). CONCLUSION: Based on a large population, we constructed a prognostic scoring model for predicting survival in elderly HCC patients. The model may provide a reference for clinicians for preoperative and postoperative evaluations of elderly HCC patients.