BALAD and BALAD-2 predict survival of hepatocellular carcinoma patients: a North American cohort study

Area of Science:

• Hepatocellular Carcinoma (HCC) Research
• Biomarker Discovery and Validation
• Oncology Prognostics

Background:

• The BALAD score and BALAD-2 class, derived from bilirubin, albumin, alpha-fetoprotein (AFP), AFP-L3, and des-gamma-carboxyprothrombin (DCP), are established predictors of HCC mortality.
• Validation of these predictive models in North American HCC patient cohorts was previously lacking.

Purpose of the Study:

• To validate the efficacy of the BALAD score and BALAD-2 class in predicting overall survival for HCC patients in North America.
• To assess the performance of these models using a cohort of HCC patients diagnosed between 2000 and 2015.

Main Methods:

• A retrospective analysis included 148 HCC patients with all five key biomarkers (bilirubin, albumin, AFP, AFP-L3, DCP) tested at diagnosis.
• Hazard ratios (HR) were calculated to determine the association between BALAD scores/classes and mortality risk.
• Multivariate models incorporated clinical factors like tumor size, number, and neutrophil-lymphocyte ratio alongside BALAD scores.

Main Results:

• During a median follow-up of 21.9 months, 75 patients died, with 1- and 3-year survival rates of 70.8% and 47.6%, respectively.
• Increasing BALAD scores (1-4 vs. 0) and BALAD-2 classes (2-4 vs. 1) significantly correlated with increased mortality risk (HRs ranging from 1.24 to 7.19 and 1.25 to 6.20, respectively).
• Multivariate analysis confirmed BALAD (HR 1.43 per score increase) and BALAD-2 (HR 1.50 per class increase) as independent predictors of survival.

Conclusions:

• The BALAD score and BALAD-2 class are validated as effective tools for predicting HCC patient survival in North America.
• AFP, AFP-L3, and DCP are crucial biomarkers reflecting tumor progression and metastasis, enhancing the BALAD model's predictive power beyond other models.