Asian Pacific journal of cancer prevention : APJCP · 2026
Development and Internal Validation of the SPR-HCC Score System: A Prognostic Tool for Survival Prediction in Hepatocellular Carcinoma in a Resource-Limited Setting.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод в очереди
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Neesanun Sunee, Patumanond Jayanton
Аннотация
BACKGROUND: Hepatocellular carcinoma (HCC) is a heterogeneous disease, in which survival is influenced by various factors beyond tumor characteristics. Although many prognostic models have been developed, they often have limitations, and the models do not include data from Thai patients. This study aimed to develop and internally validate a prognostic scoring system (SPR-HCC) using routinely available clinical and laboratory parameters.
METHODS: This retrospective cohort study analyzed 484 HCC patients diagnosed between October 2018 and April 2023 at a Thai tertiary center. Clinical, laboratory, and treatment data were extracted from electronic records. Independent mortality predictors were identified via multivariable Cox regression. Model performance was evaluated using Harrell's C-statistic, calibration plots, bootstrap resampling, and decision curve analysis.
RESULTS: Among 484 patients, 399 (82.4%) had died. The median overall survival (mOS) was 4.73 months (95% CI: 3.68-6.51). Eight independent predictors were identified: ECOG performance status, Child-Pugh class, tumor size >5 cm, bone metastasis, ALP >120 IU/L, AFP ≥400 ng/mL, PLR ≥150, and treatment aim. The final SPR-HCC model demonstrated strong discrimination (C-statistic = 0.797) and good calibration. Patients were stratified into low- (0-5 points), intermediate- (5.5-9.5 points), and high-risk (≥10 points) groups, with corresponding mOS of 29.12, 6.24, and 1.51 months (log-rank p < 0.001). Bootstrap validation showed minimal optimism (0.0000442) and a shrinkage factor of 0.9995. DCA indicated net clinical benefit across a threshold probability range of 0.15-0.60, with optimal benefit between 0.25-0.45.
CONCLUSIONS: The model demonstrated good performance in stratifying patients into three risk groups with significantly different survival. This scoring system may be applied to clinical decision-making by providing risk group stratification for HCC patients.
METHODS: This retrospective cohort study analyzed 484 HCC patients diagnosed between October 2018 and April 2023 at a Thai tertiary center. Clinical, laboratory, and treatment data were extracted from electronic records. Independent mortality predictors were identified via multivariable Cox regression. Model performance was evaluated using Harrell's C-statistic, calibration plots, bootstrap resampling, and decision curve analysis.
RESULTS: Among 484 patients, 399 (82.4%) had died. The median overall survival (mOS) was 4.73 months (95% CI: 3.68-6.51). Eight independent predictors were identified: ECOG performance status, Child-Pugh class, tumor size >5 cm, bone metastasis, ALP >120 IU/L, AFP ≥400 ng/mL, PLR ≥150, and treatment aim. The final SPR-HCC model demonstrated strong discrimination (C-statistic = 0.797) and good calibration. Patients were stratified into low- (0-5 points), intermediate- (5.5-9.5 points), and high-risk (≥10 points) groups, with corresponding mOS of 29.12, 6.24, and 1.51 months (log-rank p < 0.001). Bootstrap validation showed minimal optimism (0.0000442) and a shrinkage factor of 0.9995. DCA indicated net clinical benefit across a threshold probability range of 0.15-0.60, with optimal benefit between 0.25-0.45.
CONCLUSIONS: The model demonstrated good performance in stratifying patients into three risk groups with significantly different survival. This scoring system may be applied to clinical decision-making by providing risk group stratification for HCC patients.