Prognostic Value of Fibrosis-4 in Male Patients with Alcohol-Related Hepatocellular Carcinoma: Implications for Ultrasound-Based Therapeutic Strategies

<b><i>Background:</i></b> Hepatocellular carcinoma (HCC) is still the largest cause of cancer-related death globally, with alcohol-related HCC (AR-HCC) being a particularly difficult subtype with poor clinical results. Noninvasive biomarkers, such as the fibrosis-4 (FIB-4) index, may provide significant prognostic information that might aid in guiding new interventional techniques, such as ultrasound-based treatments. <b><i>Methods:</i></b> The authors did a retrospective cohort analysis on male AR-HCC patients diagnosed between January 2008 and December 2018. Clinical data and survival outcomes were obtained from electronic medical records, with HCC diagnosed as the baseline. The major endpoint was 12-month mortality. Multivariate logistic regression and limited cubic spline analysis were used to assess the relationship between FIB-4 and mortality risk. <b><i>Results:</i></b> Among 786 AR-HCC patients (mean age 57 years), 90.1% reported a history of alcohol usage for more than 10 years. The Barcelona Clinic Liver Cancer staging showed 42.8% in stage 0/A, 45.9% in stage B/C, and 11.3% in stage D. Deceased individuals had substantially higher FIB-4 levels (<i>p</i> < 0.05). Logistic regression demonstrated that higher FIB-4 was independently related with increased mortality, and spline analysis revealed a linear risk increase with a threshold of 5.61. <b><i>Conclusion:</i></b> Elevated FIB-4 (≥5.61) predicts worse mortality in AR-HCC, indicating its potential relevance in stratifying patients for ultrasound-based cancer therapy. The level of fibrosis may impact both therapeutic response and procedural risk. Routine incorporation of FIB-4 into clinical processes may aid precision decision-making in choosing AR-HCC patients most likely to benefit from ultrasound-guided or ultrasound-enhanced biotherapeutic. <b>Keywords:</b> alcohol, hepatocellular carcinoma, FIB-4, multivariate logistic regression analyses, mortality.