Individualized Risk Stratification for Early Recurrence of Hepatocellular Carcinoma: A Clinical Tool Derived from a Large-Scale (n=3084) Cohort Study

Beyond Single Biomarkers: A Multidimensional Risk Score for Improved Post-Transplant Prognosis Prediction in Hepatocellular Carcinoma

Introduction Inflammation- and nutrition-related biomarkers are associated with prognosis in hepatocellular carcinoma (HCC), but most studies have focused on single markers. This study aimed to develop and internally validate a multidimensional inflammatory-nutritional risk score (RS) for predicting post-transplant outcomes in HCC patients. Materials and methods This single-center retrospective cohort included 239 patients with pathologically confirmed HCC who underwent liver transplantation between April 2013 and July 2023. Fourteen preoperative inflammation- and nutrition-related markers were calculated from laboratory data obtained within one week before transplantation. A bootstrap LASSO-Cox framework with 2000 resampling iterations was used to identify stable prognostic markers, and those selected in >70% of iterations were retained for the primary RS. Overall survival (OS) and recurrence-free survival (RFS) were assessed. Model performance was evaluated using Cox regression, C-index, time-dependent ROC analysis, calibration, decision curve analysis, and bootstrap optimism-corrected internal validation. Results During a median follow-up of 53 months, 83 OS events and 89 RFS events occurred. Four markers, including fibrinogen-to-albumin ratio, gamma-glutamyl transpeptidase-to-prealbumin ratio, gamma-glutamyl transpeptidase-to-albumin ratio, and aspartate aminotransferase-to-neutrophil ratio index, were selected to construct the primary RS. Patients with high RS had significantly worse OS and RFS than those with low RS, and RS remained independently associated with both outcomes in multivariable Cox analyses. Adding RS improved prognostic performance beyond Milan criteria, Hangzhou criteria, UCSF criteria, and clinicopathological models incorporating alpha-fetoprotein, tumor burden, portal vein tumor thrombus, and microvascular invasion. The final RS-plus clinicopathological model achieved apparent C-indices of 0.766 for OS and 0.759 for RFS, with bootstrap optimism-corrected C-indices of 0.756 and 0.749, respectively. Conclusion A four-marker inflammatory-nutritional RS based on routinely available preoperative biomarkers was independently associated with OS and RFS after liver transplantation for HCC and provided incremental prognostic information beyond established criteria and clinicopathological factors. Because the RS-plus model incorporates microvascular invasion, it should be interpreted as a postoperative prognostic tool. External validation is required before clinical application.

Development and Internal Validation of the SPR-HCC Score System: A Prognostic Tool for Survival Prediction in Hepatocellular Carcinoma in a Resource-Limited Setting.

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.

Prognostic Models and Predictors of Recurrence in Resectable Colorectal Liver Metastases: A Systematic Review and Meta-analysis.

We systematically reviewed prognostic models for recurrence after curative-intent locoregional treatment of colorectal liver metastases (CRLM) and quantitatively synthesized prognostic factors associated with recurrence-free survival (RFS). From 2,208 records across 26 years of literature, 293 studies were included, encompassing 85,150 patients in development cohorts and 5,549 patients in validation cohorts. Most models targeted risk stratification rather than clinically actionable prediction, and Cox proportional hazards regression remained the dominant modelling approach despite increasing use of artificial intelligence and machine learning terminology. External validation was uncommon (33/293 studies), performance reporting was heterogeneous, and overall methodological quality was limited, restricting cross-study comparability and clinical translation. Imaging-based modelling represented a small subset (19 studies; 23 RFS models), generally characterized by small cohorts and predominantly conventional regression-based pipelines. Meta-analysis identified several clinicopathological, molecular, and treatment-related predictors consistently associated with recurrence, including primary lymph node positivity (HR 1.58), multiple liver metastases (HR 1.49), positive resection margins (HR 1.73), postoperative carcinoembryonic antigen >5ng/mL (HR 2.79), poor response to neoadjuvant therapy according to RECIST criteria (HR 2.76), and postoperative circulating tumor DNA positivity (HR 4.78), the strongest prognostic factor identified. Adjuvant and peri-operative systemic therapies were associated with lower recurrence risk. The study showed that current prognostic models incompletely capture the biological heterogeneity underlying CRLM recurrence. Dynamic biomarkers and treatment-response indicators may support future multimodal prognostic frameworks and improve risk stratification following curative-intent treatment.

Clinically meaningful risk factors for recurrence in T1 colorectal cancer treated with endoscopic resection alone identified by unsupervised machine learning: a multicenter study

Abstract Background Identifying patients at high risk for recurrence after endoscopic resection of T1 colorectal cancer (CRC) remains challenging. This study aimed to identify recurrence risk subtypes and develop an interpretable risk stratification framework. Methods This retrospective study analyzed 1123 patients with T1 CRC treated with endoscopic resection alone across 26 Japanese institutions (July 2009–December 2016). Patients were divided into development (68%) and evaluation (32%) cohorts based on institutional stratification. K-means clustering was applied to clinicopathologic variables to identify recurrence risk subtypes. A decision tree classifier was subsequently developed to generate transparent risk stratification rules. Results Three distinct subtypes were identified in the development cohort. Subtype 1 exhibited a numerically higher recurrence rate (5.4%) than Subtype 2 (0.9%) and Subtype 3 (1.4%). Although subtypes 2 and 3 showed comparable recurrence rates, they were clearly differentiated by morphology (flat vs. polypoid). In the evaluation cohort, Subtype 1 continued to show a numerically higher recurrence (4.8%) compared with subtypes 2 (1.6%) and 3 (1.1%). The decision tree model stratified recurrence risk hierarchically: submucosal invasion <1000 μm indicated low risk, whereas invasion ≥1000 μm required morphologic assessment, with polypoid lesions classified as high risk and flat lesions further stratified using a 2000-μm threshold. Conclusions Three clinically distinct recurrence risk subtypes were identified in T1 CRC following endoscopic resection, suggesting that morphologic subclassification of T1b lesions may refine stratification beyond conventional depth-based criteria. The decision framework offers a preliminary exploratory basis for recurrence risk assessment in this population.

A simplified MRI‑based risk score and nomogram to predict initial objective response in unresectable hepatocellular carcinoma treated with HAIC, targeted therapy, and immunotherapy: a multicenter study.

Young patients with hepatocellular carcinoma beyond Milan criteria had higher early recurrence and poorer long-term outcomes after hepatectomy.

BACKGROUND Hepatocellular carcinoma (HCC) in young patients is uncommon, and their postoperative prognosis remains poorly defined. This study aimed to evaluate the impact of young age on tumor characteristics, recurrence, and long-term outcomes after hepatectomy in patients with HCC. METHODS We reviewed 5465 patients who underwent curative-intent hepatectomy for HCC at Asan Medical Center between December 2008 and March 2019. Patients were categorized into younger (< 40 years, n = 265) and older (≥ 40 years, n = 5200) groups. Clinicopathological characteristics, recurrence rates, overall survival (OS), and recurrence-free survival (RFS) were compared between groups before and after 1:10 propensity score matching (PSM). Multivariate logistic regression analysis was performed to identify independent predictors of 2-year recurrence. RESULTS Younger patients were more likely to have hepatitis B virus-related HCC (81.1% vs. 65.3%, P < 0.001) and a lower prevalence of cirrhosis (38.5% vs. 45.9%, P = 0.018), and they exhibited a higher 2-year recurrence rate than older patients (39.6% vs. 31.7%, P = 0.007). Among patients within Milan criteria, younger patients showed superior OS (P = 0.028) and RFS (P = 0.013). In contrast, among patients beyond Milan criteria, younger patients had significantly poorer OS (P < 0.001) and RFS (P = 0.003) compared with older patients. These patterns persisted after PSM. Multivariate analysis identified age < 40 years as an independent predictor of 2-year recurrence in the beyond Milan criteria group, but not in the within Milan criteria group. CONCLUSIONS Young patients with HCC, particularly those beyond Milan criteria, were at increased risk of early recurrence and poorer long-term outcomes. These findings support the need for closer surveillance and tailored treatment strategies in this population.