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Simple Summary: This study evaluated the impact of alpha-fetoprotein (AFP) testing frequency on survival rates in hepatocellular carcinoma (HCC) patients. Analyzing data from 81,520 patients in Korea, it was found that increased AFP testing significantly improved survival, particularly in patients with hepatitis B undergoing antiviral treatment. Those tested three or more times before diagnosis had a higher likelihood of receiving curative treatments, such as liver transplantation. The study suggests that combining AFP tests with ultrasound screenings could better detect HCC early, offering enhanced treatment opportunities and improved survival chances, especially for hepatitis B patients. Guidelines vary on alpha-fetoprotein (AFP) testing for hepatocellular carcinoma (HCC) screening. This study aims to reassess AFP's role in HCC surveillance, utilizing a comprehensive, recent, nationwide cohort. Utilizing the National Health Claims Database from the Korean National Health Insurance Service, this research included data from 185,316 HCC patients registered between 2008 and 2018. Specifically, 81,520 patients diagnosed with HCC from 2008 to 2014 were analyzed. The study focused primarily on mortality and, secondarily, on the status of curative treatments. Multivariate analysis revealed that frequent AFP testing significantly impacts overall survival in HCC patients. Specifically, each additional AFP test correlated with a 6% relative improvement in survival (hazard ratio = 0.94, 95% CI: 0.940–0.947, p < 0.001). Patients who underwent AFP testing three or more times within two years prior to HCC diagnosis showed improved survival rates, with 55.6% receiving liver transplantation or hepatectomy. This trend was particularly pronounced in hepatitis B patients undergoing antiviral treatment. The findings highlight the potential of regular AFP testing to enhance survival in HCC patients, especially those with hepatitis B. Integrating frequent AFP testing with ultrasonography could increase the likelihood of early detection and access to curative treatments. [ABSTRACT FROM AUTHOR]

Considering the lower risk of hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) patients receiving long‐term potent antiviral therapy, models predicting HCC after 5 years of therapy are needed. We conducted a multicenter retrospective cohort study to construct and validate a model predicting HCC after 5 years of entecavir (ETV) or tenofovir (TFV) therapy for CHB. The endpoint was HCC after 5 years of ETV/TFV therapy. Information on age, sex, liver cirrhosis (assessed by diagnosis code and confirmed by clinical findings) and type of antiviral agent was obtained at baseline (initiation of ETV/TFV). Laboratory values were collected at baseline and 5 years. Risk factors for HCC were identified in the training set and the final prediction model was validated using the test set. Among 7542 patients, 345 (4.6%) developed HCC after 5 years of ETV/TFV therapy. HCC risk after 5 years of ETV/TFV therapy was increased by 4‐fold in patients with liver cirrhosis than in those without cirrhosis at baseline. Furthermore, Platelet counts and Prothrombin time at 5 years, Age at baseline and Sex were associated with risk of HCC and were incorporated into a prediction model, PPACS. PPACS showed a good performance with a time‐dependent area under the curve of 0.80 (95% confidence interval, 0.75‐0.85) at 8‐year of ETV/TFV therapy, a Brier score of 0.031 and an integrated Brier score of 0.006 in the test set. In conclusion, the PPACS model provides a reliable assessment of HCC risk after 5 years of ETV/TFV therapy (https://ppacs.shinyapps.io/shiny_app_up/). [ABSTRACT FROM AUTHOR]

Background: Machine learning (ML) algorithms can be used to overcome the prognostic performance limitations of conventional hepatocellular carcinoma (HCC) risk models. We established and validated an ML‐based HCC predictive model optimized for patients with chronic hepatitis B (CHB) infections receiving antiviral therapy (AVT). Methods: Treatment‐naïve CHB patients who were started entecavir (ETV) or tenofovir disoproxil fumarate (TDF) were enrolled. We used a training cohort (n = 960) to develop a novel ML model that predicted HCC development within 5 years and validated the model using an independent external cohort (n = 1937). ML algorithms consider all potential interactions and do not use predefined hypotheses. Results: The mean age of the patients in the training cohort was 48 years, and most patients (68.9%) were men. During the median 59.3 (interquartile range 45.8–72.3) months of follow‐up, 69 (7.2%) patients developed HCC. Our ML‐based HCC risk prediction model had an area under the receiver‐operating characteristic curve (AUC) of 0.900, which was better than the AUCs of CAMD (0.778) and REAL B (0.772) (both p <.05). The better performance of our model was maintained (AUC = 0.872 vs. 0.788 for CAMD and 0.801 for REAL B) in the validation cohort. Using cut‐off probabilities of 0.3 and 0.5, the cumulative incidence of HCC development differed significantly among the three risk groups (p <.001). Conclusions: Our new ML model performed better than models in terms of predicting the risk of HCC development in CHB patients receiving AVT. [ABSTRACT FROM AUTHOR]

Background: Since atezolizumab plus bevacizumab (ATE+BEV) regimen for patients with unresectable hepatocellular carcinoma (HCC) was released quite recently, real‐world data are lacking. We evaluated efficacy, safety, and predictive biomarkers for survival in patients receiving ATE+BEV. Methods: Between 2020 and 2021, HCC patients receiving ATE+BEV at academic teaching hospitals were recruited. Treatment response was assessed using the Response Evaluation Criteria in Solid Tumors (version 1.1.). Results: Among 121 patients enrolled, the median age was 63 years, with male predominance (82.6%). Complete response, partial response, stable disease, and progressive disease were identified in 2.5%, 26.4%, 54.5%, and 16.6%, respectively. Patients with alpha‐fetoprotein and des‐gamma‐carboxy prothrombin (DCP) response, defined as ≥30% and ≥50% decreases, respectively, at the first response evaluation relative to baseline, and those with neutrophil‐to‐lymphocyte ratio (NLR) <2.5, had significantly higher objective response rates (42.6% vs. 21.5%, 50.0% vs. 26.2%, and 39.0% vs. 19.4%, respectively; all p < 0.05). During follow‐up, the median overall survival (OS) was not reached, and the median progression‐free survival (PFS) was 5.7 months. Multivariable analyses showed that macrovascular invasion (adjusted hazard ratio [aHR] 2.541; p = 0.017), DCP ≥186 mAU/ml (aHR 5.102; p < 0.001), NLR ≥2.5 (aHR 3.584; p = 0.001), and an NLR decrease ≥10% at the first response (aHR 0.305; p = 0.002) were independent predictors of OS, and DCP ≥186 mAU (aHR 2.311; p = 0.002) and NLR ≥2.5 (aHR 1.938; p = 0.012) were independent predictors of PFS. Grade ≥3 treatment‐related adverse events (AEs) occurred in 33 (27.3%) patients. Conclusion: ATE+BEV showed favorable efficacy and safety. Baseline high DCP and NLR may be useful prognostic predictors for OS and PFS. [ABSTRACT FROM AUTHOR]

Genetic and nutritional factors contribute to the development of non-alcoholic fatty liver disease (NAFLD); however, gene–diet interactions in NAFLD development are poorly understood. In this case–control study, a large dataset from the Korean Genome and Epidemiology Study cohort (n = 72,299) comprising genomic data, medical records, social history, and dietary data was used. We investigated the interactions between the PNPLA3 rs738409 genotype and nutritional factors and their possible effect on the risk of NAFLD development in 2950 patients with NAFLD and 12,907 controls. In the PNPLA3 risk allele group, high protein, fat, sodium, phosphorus, niacin, and vitamin B6 intakes were associated with a decreased risk of NAFLD. In the non-risk allele group, only high fat intake was associated with a decreased risk of NAFLD. Among these nutrients, high sodium intake had a significant protective interaction with the PNPLA3 genotype against NAFLD (p = 0.002). Among salty foods, only kimchi had a significant protective effect against the PNPLA3 genotype (p = 0.012). Thus, the PNPLA3 genotype is differentially associated with nutritional factors. In particular, it interacts with kimchi, a fermented vegetable dish. Therefore, fermented vegetables may serve as a tailored therapeutic food for people with the PNPLA3 risk allele. [ABSTRACT FROM AUTHOR]