HES V2.0 outperforms GALAD for detection of HCC: A phase 3 biomarker study in the United States.

BACKGROUND AND AIMS: The original hepatocellular carcinoma early detection screening (HES) score, which combines alpha-fetoprotein (AFP) with age, alanine aminotransferase, and platelets, has better performance than AFP alone for early HCC detection. We have developed HES V2.0 by adding AFP-L3 and des-gamma-carboxy prothrombin to the score and compared its performance to GALAD and ASAP scores among patients with cirrhosis. APPROACH AND RESULTS: We conducted a prospective-specimen collection, retrospective-blinded-evaluation phase 3 biomarker cohort study in patients with cirrhosis enrolled in imaging and AFP surveillance. True-positive rate (TPR)/sensitivity and false-positive rate for any or early HCC were calculated for GALAD, ASAP, and HES V2.0 scores within 6, 12, and 24 months of HCC diagnosis. We calculated the AUROC curve and estimated TPR based on an optimal threshold at a fixed false-positive rate of 10%. We analyzed 2331 patients, of whom 125 developed HCC (71% in the early stages). For any HCC, HES V2.0 had higher TPR than GALAD overall (+7.2%), at 6 months (+3.6%), at 12 months (+7.2%), and 24 months (+13.0%) before HCC diagnosis. HES V2.0 had higher TPR than ASAP for all time points (+5.9% to +12.0%). For early HCC, HES V2.0 had higher sensitivity/TPR than GALAD overall (+6.7%), at 12 months (+6.3%), and 24 months (+14.6%) but not at 6 months (+0.0%) and higher than ASAP for all time points (+13.4% to +18.0%). CONCLUSIONS: In a prospective cohort study, HES V2.0 had a significantly higher performance for identifying new HCC, including early stage, than GALAD or ASAP.

Serum biomarker signature is predictive of the risk of hepatocellular cancer in patients with cirrhosis.

BACKGROUND: Inflammatory and metabolic biomarkers have been associated with hepatocellular cancer (HCC) risk in phases I and II biomarker studies. We developed and internally validated a robust metabolic biomarker panel predictive of HCC in a longitudinal phase III study. METHODS: We used data and banked serum from a prospective cohort of 2266 adult patients with cirrhosis who were followed until the development of HCC (n=126). We custom designed a FirePlex immunoassay to measure baseline serum levels of 39 biomarkers and established a set of biomarkers with the highest discriminatory ability for HCC. We performed bootstrapping to evaluate the predictive performance using C-index and time-dependent area under the receiver operating characteristic curve (AUROC). We quantified the incremental predictive value of the biomarker panel when added to previously validated clinical models. RESULTS: We identified a nine-biomarker panel (P9) with a C-index of 0.67 (95% CI 0.66 to 0.67), including insulin growth factor-1, interleukin-10, transforming growth factor ß1, adipsin, fetuin-A, interleukin-1 ß, macrophage stimulating protein α chain, serum amyloid A and TNF-α. Adding P9 to our clinical model with 10 factors including AFP improved AUROC at 1 and 2 years by 4.8% and 2.7%, respectively. Adding P9 to aMAP score improved AUROC at 1 and 2 years by 14.2% and 7.6%, respectively. Adding AFP L-3 or DCP did not change the predictive ability of the P9 model. CONCLUSIONS: We identified a panel of nine serum biomarkers that is independently associated with developing HCC in cirrhosis and that improved the predictive ability of risk stratification models containing clinical factors.

Risk factors for HCC in contemporary cohorts of patients with cirrhosis.

BACKGROUND AND AIMS: Etiological risk factors for cirrhosis have changed in the last decade. It remains unclear to what extent these trends in cirrhosis risk factors have changed HCC risk. APPROACH AND RESULTS: We used data from two contemporary, prospective multiethnic cohorts of patients with cirrhosis: the Texas Hepatocellular Carcinoma Consortium Cohort and the Houston Veterans Administration Cirrhosis Surveillance Cohort. Patients with cirrhosis were enrolled from seven US centers and followed until HCC diagnosis, transplant, death, or June 30, 2021. We calculated the annual incidence rates for HCC and examined the effects of etiology, demographic, clinical, and lifestyle factors on the risk of HCC. We included 2733 patients with cirrhosis (mean age 60.1 years, 31.3% women). At enrollment, 19.0% had active HCV, 23.3% had cured HCV, 16.1% had alcoholic liver disease, and 30.1% had NAFLD. During 7406 person-years of follow-up, 135 patients developed HCC at an annual incidence rate of 1.82% (95% CI, 1.51-2.13). The annual HCC incidence rate was 1.71% in patients with cured HCV, 1.32% in patients with alcoholic liver disease, and 1.24% in patients with NAFLD cirrhosis. Compared to patients with NAFLD, the risk of progression to HCC was 2-fold higher in patients with cured HCV (HR, 2.04; 95% CI, 1.24-3.35). Current smoking (HR, 1.63; 95% CI, 1.01-2.63) and overweight/obesity (HR, 1.79; 95% CI, 1.08-2.95) were also associated with HCC risk. CONCLUSIONS: HCC incidence among patients with cirrhosis was lower than previously reported. HCC risk was variable across etiologies, with higher risk in patients with HCV cirrhosis and lower risk in those with NAFLD cirrhosis. Current smoking and overweight/obesity increased HCC risk across etiologies.

Risk Stratification Model for Hepatocellular Cancer in Patients With Cirrhosis.

BACKGROUND & AIMS: The available risk stratification indices for hepatocellular cancer (HCC) have limited applicability. We developed and externally validated an HCC risk stratification index in U.S. cohorts of patients with cirrhosis. METHODS: We used data from 2 prospective U.S. cohorts to develop the risk index. Patients with cirrhosis were enrolled from 8 centers and followed until development of HCC, death, or December 31, 2021. We identified an optimal set of predictors with the highest discriminatory ability (C-index) for HCC. The predictors were refit using competing risk regression and its predictive performance was evaluated using the area under the receiver-operating characteristic curve (AUROC). External validation was performed in a cohort of 21,550 patients with cirrhosis seen in the U.S Veterans Affairs system between 2018 and 2019 with follow-up through 2021. RESULTS: We developed the model in 2431 patients (mean age 60 years, 31% women, 24% cured hepatitis C, 16% alcoholic liver disease, and 29% nonalcoholic fatty liver disease). The selected model had a C-index of 0.77 (95% confidence interval [CI], 0.73-0.81), and the predictors were age, sex, smoking, alcohol use, body mass index, etiology, α-fetoprotein, albumin, alanine aminotransferase, and platelet levels. The AUROCs were 0.75 (95% CI, 0.65-0.85) at 1 year and 0.77 (95% CI, 0.71-0.83) at 2 years, and the model was well calibrated. In the external validation cohort, the AUROC at 2 years was 0.70 with excellent calibration. CONCLUSION: The risk index, including objective and routinely available risk factors, can differentiate patients with cirrhosis who will develop HCC and help guide discussions regarding HCC surveillance and prevention. Future studies are needed for additional external validation and refinement of risk stratification.

Bioimpedance analysis predicts the etiology of cirrhosis in a prospective cohort study.

BACKGROUND: Obesity is associated with an increased risk of developing cirrhosis. However, body mass index (BMI) and waist-to-hip ratio (WHR) may not be indicative of body composition parameters that predispose to cirrhosis. Bioimpedance analysis (BIA) is a noninvasive cost-efficient method for more detailed estimation of body composition. METHODS: We examined patients with cirrhosis who underwent BIA as part of enrollment into a prospective cohort study. We examined the correlation between BIA variables, BMI, and WHR. We performed sex-adjusted and race-adjusted and race-specific multivariable logistic regression analyses to examine the association between anthropometric variables and risk factors [NAFLD, alcohol-associated liver disease (ALD), and HCV]. RESULTS: We analyzed data from 348 cirrhosis patients; 23.3% were women; 48.3% were non-Hispanic White; 19.3% were Hispanic; and 30.7% were African American. The cirrhosis etiology was 21.8% NAFLD, 56.9% HCV mostly cured, and 11.5% ALD. Several BIA variables correlated well with BMI, and others showed modest correlations, but none correlated well with WHR. Higher body fat mass and basal metabolic rate were positively associated, while higher lean body mass, dry lean mass, total body water, or skeletal muscle mass were negatively associated with NAFLD. Associations between these BIA parameters and ALD-related cirrhosis were in the opposite direction. These associations of BIA variables were seen only in Hispanic and non-Hispanic White patients but not non-Hispanic Blacks. BIA variables were more predictive of cirrhosis etiology than BMI or WHR. CONCLUSIONS: Among patients with cirrhosis, several BIA-derived measurements indicative of body fat and muscle are associated with NAFLD and ALD etiology. BIA variables show stronger associations, as well as race/ethnicity-specific associations, with cirrhosis etiology than those of BMI or WHR.

Risk stratification for hepatocellular cancer among patients with cirrhosis using a hepatic fat polygenic risk score.

BACKGROUND: Polygenic risk scores (PRS) hold the promise to refine prognostication in hepatocellular cancer (HCC). The few available HCC PRS include germline risk variants identified among individuals of mostly European ancestry, but data are lacking on the transportability of these PRS in multiethnic U.S patients with cirrhosis from multiple etiologies. METHODS: We used data from 1644 patients with cirrhosis enrolled in two prospective cohort studies in the U.S. Patients were followed until HCC diagnosis, death, liver transplantation, or last study visit through June 30, 2021. The high-risk variants in PNPLA3-MBOAT7-TM6SF2-GCKR were combined in a PRS and we evaluated its association with HCC. Discriminatory accuracy was assessed using the C-statistic. RESULTS: During 4,759 person-years of follow-up, 93 patients developed HCC. Mean age was 59.8 years, 68.6% were male, 27.2% Hispanic, 25.1% non-Hispanic Black, 25.7% had NAFLD, 42.1% had heavy alcohol use, and 19.5% had active HCV. HCC risk increased by 134% per unit increase in PRS (HR = 2.30; 95% CI, 1.35-3.92). Compared to cirrhosis patients in the lowest tertile of the PRS, those in the highest tertile had 2-fold higher risk of HCC (HR = 2.05; 95% CI, 1.22-3.44). The PRS alone had modest discriminatory ability (C-statistic = 0.58; 95% CI, 0.52-0.63); however, adding PRS to a predictive model with traditional HCC risk factors had a C-statistic of 0.70 (95% CI, 0.64-0.76), increasing from 0.68 without the PRS (p = 0.0012). CONCLUSIONS: Our findings suggest that PRS may enhance risk prediction for HCC in contemporary U.S. cirrhosis patients.