Albumin ratio and liver-to-abdominal area ratio are promising prognostic indicators for patients with post-hepatitis B cirrhosis

白蛋白比值和肝腹面积比是乙型肝炎后肝硬化患者预后的潜在指标。

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Abstract

OBJECTIVE: To evaluate the clinical relevance of the Albumin Ratio (AR) and Liver-to-Abdominal Area Ratio (LAAR) as prognostic markers for patients with hepatitis B-related cirrhosis. METHODS: A retrospective cohort study was conducted on 278 patients diagnosed with hepatitis B-associated cirrhosis at Baoji Central Hospital from January 2017 to December 2020. Clinical data, laboratory results (AR), and imaging data (LAAR) were collected. Prognostic value of AR and LAAR was assessed using Kaplan-Meier survival analysis, Cox proportional hazards regression, and receiver operating characteristic (ROC) curves. A nomogram integrating multiple variables was developed and validated to dynamically predict 6-, 12-, and 24-month survival outcomes. RESULTS: Both AR and LAAR were significantly reduced in the deceased group compared to survivors (P<0.05). Cox regression analysis identified AR (HR=1.86, 95% CI: 1.40-2.45, P<0.001) and LAAR (HR=1.67, 95% CI: 1.25-2.22, P=0.002) as independent prognostic factors. Kaplan-Meier survival curves revealed significantly shorter survival in patients with lower AR and LAAR (P<0.001). Time-dependent ROC analysis indicated good predictive performance for AR (AUC up to 0.85), while LAAR showed relatively low discrimination, with AUCs ranging from 0.507 to 0.623. The nomogram, incorporating both AR and LAAR, exhibited excellent discrimination (C-index =0.950), and its predictive accuracy was validated through calibration curves. CONCLUSION: AR and LAAR are critical prognostic indicators in hepatitis B-related cirrhosis. The nomogram model, integrating these values, supports tailored treatment plans and monitoring strategies in clinical settings. Patients with lower AR and LAAR have poorer survival outcomes, and the model's robust predictive capacity has been validated, enhancing precision in patient management and supporting individualized therapeutic decisions.

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