Background and aims: Atezolizumab plus bevacizumab (AB) has become the standard first-line treatment for advanced HCC. However, identifying reliable prognostic biomarkers remains a critical challenge. We aimed to develop a comprehensive scoring system to predict overall survival (OS) in advanced HCC patients receiving first-line AB.
Approach and results: We included patients with advanced HCC receiving first-line AB from multiple centers in Korea, forming a derivation cohort ( n =456) and a validation cohort ( n =205). Multivariable analysis identified 5 independent prognostic factors: C-reactive protein ≥1.0 mg/dL (HR 2.07; p <0.001), albumin <3.5 g/dL (HR 1.60; p =0.002), protein induced by vitamin K absence or antagonist-II ≥1500 mAU/mL (HR 1.60; p =0.002), total bilirubin ≥1.0 mg/dL (HR 1.50; p =0.006), and macrovascular invasion (HR 1.49; p =0.009). We developed the CRAPT-M model, named after these factors' initial letters. Patients were categorized into low (≤4), intermediate (5-12), and high (≥13) risk groups by CRAPT-M score. Median OS differed significantly: 22.4 (95% CI, 18.6-25.0), 12.9 (95% CI, 8.7-14.8), and 6.7 (95% CI, 5.1-7.7) months for low-risk, intermediate-risk, and high-risk groups, respectively ( p <0.001). Time-dependent area under the receiver operating characteristic for CRAPT-M demonstrated consistently higher predictive accuracy than the CRAFITY model, with values of 0.785, 0.737, and 0.742 at 12, 24, and 36 months, respectively. The model demonstrated robust predictive performance in the external validation cohort, with excellent calibration and consistent discrimination across sensitivity analyses.
Conclusions: The CRAPT-M model demonstrated robust OS prediction, offering a valuable tool for prognosis estimation and clinical decision-making in advanced HCC patients receiving AB.
Keywords: C-reactive protein; HCC; immuno-oncology; risk prediction model.
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