A Practical Nomogram and Risk Stratification System Predicting the Cancer-Specific Survival for Patients With Advanced Hepatocellular Carcinoma - Yang, Dashuai; Su, Yang; Zhao, Fangrui; Chen, Chen; Zhao, Kailiang; Xiong, Xiangyun; Ding, Youming (Frontiers in Oncology, 2022)
Background: Of all cancers, hepatocellular carcinoma (HCC) has the highest cancer-related mortality rate. Our purpose is to create a nomogram to predict the cancer-specific survival (CSS) in patients with advanced hepatocellular carcinoma. Methods: Patients diagnosed with advanced HCC (AJCC Stage III and IV) during 1975 to 2018 were obtained from the Surveillance, Epidemiology and End Results (SEER) database. They were randomized into training cohort and validation cohort at a ratio of 7:3. The results of univariate and multivariate Cox regression analyses were used to construct the nomogram. Consistency index (C-index), area under the time-dependent receiver operating characteristic (ROC) curve (time-dependent AUC), and calibration plots were used to identify and calibrate the nomogram. The net reclassification index (NRI), integrated discrimination improvement (IDI) and C-index, and decision curve analysis DCA were adopted to compare the nomogram’s clinical utility with the AJCC criteria. Results: 3103 patients with advanced hepatocellular carcinoma were selected (the training cohort: 2175 patients and the validation cohort: 928 patients). The C-index in both training cohort and validation cohort were greater than 0.7. The area under the curve (AUC) for ROC in the training cohort was 0.781, 0.771 and 0.791 at 1, 2 and 3 years CSS, respectively. Calibration plots showed good consistency between actual observations and the 1-, 2- and 3-year CSS predicted by the nomogram. 1-, 2-, and 3- year NRI were 0.77, 0.46, and 0.48, respectively. 1-, 2-, and 3- year IDI values were 0.16, 0.15 and 0.12 (P <0.001). DCA curves in both the training and validation cohorts demonstrated that the nomogram showed better predicted 1-, 2-, and 3-year CSS probabilities than AJCC criteria. Conclusions: We established a practical nomogram for predicting CSS in patients with advanced HCC and a risk stratification system that provided an applicable tool for clinical management.