A Practical Model is Equivalent to the BALAD or BALAD-2 Score in Predicting Long-term Survival after Hepatectomy in Chinese Patients with Hepatocellular Carcinoma

Aim: To evaluate the predictive value of the BALAD and BALAD-2 scores on long-term survival after hepatectomy in Chinese hepatocellular carcinoma (HCC) patients and to attempt to establish a more practical or effective model. Methods: A total of 251 HCC patients underwent hepatectomy were recruited. The BALAD and BALAD-2 scores were calculated with total bilirubin, albumin, alpha-fetoprotein, Lens culinaris agglutinin-reactive fraction of alpha-fetoprotein and des-gamma-carboxyprothrombin. The associations of the two scores and their components with the overall survival were analyzed. Finally, three prediction models were explored and constructed. Results: We observed that HCC patients had 5-year survival rates that worsened with increasement of BALAD and BALAD-2 scores. The BALAD and BALAD-2 scores demonstrated fine value in predicting overall survival with Harrell-C statistics of 0.665 (0.618-0.712) and 0.603 (0.554-0.636). After two variables, largest tumor size and BMI, were included in BALAD [0.720 (0.671-0.769)] or BALAD-2 [0.701 (0.649-0.751)] multivariate models, the Harrell-C statistic increased significantly than BALAD (P=0.048) or BALAD-2 (P<0.001) alone. Taking into account availability and expense, an equivalent BAA-BS model was established based on total bilirubin, albumin, AFP, BMI and largest tumor size. The Harrell-C statistic of BAA-BS model [0.723(0.674-0.772)] was similar to that of BALAD (P=0.820) or BALAD-2 (P=0.209) multivariate model. And, the continuous net reclassification index and integrated discriminatory improvement were not statistically different. Finally, a nomogram of the equivalent BAA-BS model was constructed to assist surgeons and patients in predicting 5-year survival rates. Conclusion: Both BALAD and BALAD-2 scores were highly suitable for predicting long-term survival after hepatectomy in Chinese HCC patients. A significant increase in predictive efficacy was observed after the addition of largest tumor size and BMI to BALAD or BALAD-2 score. Even if AFP-L3 and DCP are not detected, an equivalent BAA-BS model also obtained an excellent discriminatory performance.