A nomogram for prognostic prediction and for therapeutic decision making of elderly HCC patients

Hepatocellular carcinoma (HCC) has a poor prognosis, especially in elderly HCC patients. A growing number of studies have confirmed that nomogram based on demographic information, pathologic information, and treatment modalities are effective in predicting the prognosis of cancer patients. We aimed to develop an individualized and clinically useful nomogram for elderly patients.We also aimed to investigate the prognostic significance of different treatment modalities.

A total of 7694 eligible elderly patients with HCC were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2020. The patients were randomized into the training cohort (n = 5385) and the validation cohort (n = 2309) at a 7:3 ratio. Univariate and multivariate COX regression analyses were performed in the training cohort. Based on the results of the regression analysis, a nomogram model for predicting the prognosis of elderly HCC patients was established and verified in the validation cohort. The performance of the nomogram was evaluated by using receiver operating characteristic curve (ROC) and calibration curve.Finally, we grouped patients by surgery, chemotherapy, radiotherapy separately, and then used Propensity Score Matching (PSM) to balance other variables to explore prognostic significance of different treatment modalities for elderly Hepatocellular carcinoma.

Regression analysis showed that Age, Grade, T.stage, N.stage, M.stage, Chemotherapy, Radiotherapy, and Surgery had significant prognosis and developed nomogram based on the above 8 variables.This nomogram showed good accuracy in predicting one-year OS of the training cohort (AUC = 0.745) and was confirmed in the validation cohort (AUC = 0.786). The calibration curve shows that the actual survival probability and the predicted survival probability are in good agreement. A risk classification system was established to risk-stratify elderly patients with HCC, ROC was used to validate the efficacy of nomogram model in differentiating between high and low risk groups(p < 0.01),and verify in the validation cohort(p < 0.01).Finally, after grouping elderly HCC patients according to different treatment modalities, subgroup analysis showed that: The survival time of the surgery group was longer than that of the no-surgery group. Median overall survival was longer in the chemotherapy group than in the no-chemotherapy group, but there was no advantage in long-term prognosis. Median overall survival was also significantly longer in the radiotherapy group than in the no-radiotherapy group, but when analyzed in subgroups, it was found that in the T4 stage and GradeIV subgroups, radiotherapy patients had a worse prognosis than those who did not receive radiotherapy.

The nomogram established based on demographic characteristics and other clinical parameters can be used as an effective tool to predict the prognosis of elderly HCC patients, and its good prediction efficiency can realize the individualized treatment plan formulation and follow-up management of elderly HCC patients.