Dynamic personalized prediction of the individual liver-related risk after sustained viral response in HCV patients.

Sustained viral response (SVR) significantly improves the prognosis in patients with hepatitis C virus (HCV) chronic infection but does not totally alleviate the risk of liver-related complications (LRC). We aimed to evaluate whether the dynamics of multiple measurements of simple parameters after SVR enable the development of a personalized prediction of prognosis in HCV patients. HCV mono-infected patients who experienced SVR in two prospective cohorts (ANRS CO12 CirVir cohort: derivation set; ANRS CO22 HEPATHER cohort: validation set) were included. The study outcome was LRC, a composite criterion including decompensation of cirrhosis and/or hepatocellular carcinoma. Joint latent class modelling accounting for both biomarker trajectory and event occurrence during follow-up was developed in the derivation set to compute individual dynamic predictions, with further evaluation in the validation set. In the derivation set (n = 695; 50 LRC during the median 3.8 [1.6-7.5] years follow-up), FIB4 was identified as a biomarker associated with LRC occurrence after SVR. Joint modelling used sex and the dynamics of FIB4 and diabetes status to develop a personalized prediction of LRC. In the validation set (n = 7064; 273 LRC during the median 3.6 [2.5-4.9] years follow-up), individual dynamic predictions from the model accurately stratified the risk of LRC. Time-dependent Brier Score showed good calibration that improved with the accumulation of visits, justifying our modelling approach considering both baseline and follow-up measurements. Dynamic modelling using repeated measurements of simple parameters predicts the individual residual risk of LRC and improves personalized medicine after SVR in HCV patients.

Impact of direct-acting antiviral treatment for hepatitis C on cardiovascular diseases and extrahepatic cancers.

PURPOSE: The impact of direct-acting antivirals (DAAs) on extrahepatic complications in chronic hepatitis C (CHC) patients remains poorly described. We estimated the association of DAAs with cardiovascular events and extrahepatic cancers. METHODS: The prospective ANRS CO22 HEPATHER cohort was enriched with individual data until December 2018 from the French Health Insurance Database (SNDS). CHC patients were enrolled between August 2012 and December 2015 in 32 French hepatology centers. A total of 8148 CHC adults were selected. Cardiovascular events (stroke, acute coronary syndrome, pulmonary embolism, heart failure, arrhythmias and conduction disorders [ACD], peripheral arterial disease [PAD]) and extrahepatic solid cancers were derived from the SNDS. Associations between DAAs and extrahepatic events were estimated using marginal structural models, with adjustments for clinical confounders. RESULTS: Analyses of 12 905 person-years of no DAA exposure and 22 326 person-years following DAA exposure showed a decreased risk of PAD after DAA exposure (hazard ratio [HR], 0.54; 95% CI, 0.33-0.89), a beneficial effect of DAAs on overall cardiovascular outcomes in patients with advanced fibrosis (aHR, 0.58; 95% CI, 0.42-0.79), and an increased risk of ACD (hazard ratio [HR], 1.46; 95% CI, 1.04-2.04), predominant after the first year following DAA initiation. There was no association between DAAs and extrahepatic cancer risk (HR, 1.23; 95% CI, 0.50-3.03). CONCLUSIONS: DAAs were not associated with extrahepatic cancer development or reduction. They were associated with a decreased risk of PAD and an increased risk of ACD, supporting long-term cardiac monitoring after DAA therapy.

Prediction of hepatocellular carcinoma in Hepatitis C patients with advanced fibrosis after sustained virologic response.

BACKGROUND & AIMS: Prediction of hepatocellular carcinoma (HCC) occurrence in patients with chronic hepatitis C (HCV) who achieved a sustained virological response (SVR) after direct acting antivirals (DAAs) remains challenging. METHODS: Among HCC-free HCV patients with advanced fibrosis enrolled in the ANRS CO22 HEPATHER cohort who achieved SVR 12 weeks after treatment with DAAs, HCC predictive models were developed using Cox multivariable regression. The derived score was externally validated in a large Egyptian cohort. Our main outcome was the HCC-free survival. RESULTS: During follow-up (median 3.05 years), 153 out of 3531 patients developed a HCC. Main variables associated with HCC occurrence were: male gender, HCV genotype 3, esophageal varices, albumin < 40 g/L, total bilirubin >11 µmol/L and hypercholesterolemia before DAA initiation, together with age > 58 years, FIB-4 index ≥3.25 evaluated at SVR. A score was established allowing the stratification of patients by high (score ≥ 12/22), intermediate (7 ≤ score <12) and low risk of HCC (score < 7/22) with 3-yrs HCC incidence of 18.96%, 5.50% and 1.65%, respectively. The integrated time-dependent area under the ROC curve (i-AUC) was 0.76 in our patients and 0.61 in the validation cohort. CONCLUSION: The externally validated HEPATHER HCC score has good short-term predictive performance in HCV- patients who achieved SVR12 after DAAs allowing to identify high-risk patients in whom HCC screening may be cost-effective and low-risk patients in whom HCC screening may be superfluous in the first 3 years after SVR.

Predictive factors for hepatocellular carcinoma in chronic hepatitis B using structural equation modeling: a prospective cohort study.

BACKGROUND & AIMS: The factors predicting hepatocellular carcinoma (HCC) occurrence in chronic hepatitis B need to be precisely known to improve its detection. We identified pathways and individual predictive factors associated with HCC in the ANRS CO22 HEPATHER cohort. METHODS: The study analyzed HBV-infected patients recruited at 32 French expert hepatology centers from August 6, 2012, to December 31, 2015. We excluded patients with chronic HCV, HDV and a history of HCC, decompensated cirrhosis or liver transplantation. Structural equation models were developed to characterize the causal pathways leading to HCC occurrence. The association between clinical characteristics (age, gender, body-mass index, liver fibrosis, alcohol consumption, smoking status, diabetes, hypertension, dyslipidemia, alpha-fetoprotein, HBV DNA levels, antiviral therapy) and incident HCC was quantified. RESULTS: Among the 4489 patients included, 33 patients reported incident HCC. The median follow-up was 45.5 months. Age (ß = 0.18 by decade, 95% CI 0.14-0.23), male gender (ß = 0.23, 95% CI 0.18-0.29), metabolic syndrome (ß = 0.28, 95% CI 0.22-0.33), alcohol consumption (ß = 0.09, 95% CI 0.05-0.14) and HBV DNA (ß = 0.25, 95% CI 0.170.34) had a significant and direct effect on the occurrence of advanced liver fibrosis. Liver fibrosis (ß = 0.71, 95% CI 0.55-0.87) predicted, in turn, the occurrence of HCC. CONCLUSIONS: Liver fibrosis mediates the effects of age, gender, alcohol, metabolic syndrome and HBV DNA on the occurrence of HCC. Elderly men with chronic hepatitis B, risky alcohol use, advanced liver fibrosis, metabolic syndrome and high HBV DNA levels should be monitored closely to detect the development of HCC.

The dynamic effect of direct-acting antiviral treatments on the risk of hepatocellular carcinoma in patients with cirrhosis and chronic hepatitis C.

There is still some controversy over a potentially increased short-term risk of developing hepatocellular carcinoma (HCC) after the initiation of direct-acting antiviral (DAA) therapy, even though a decreased long-term risk of HCC has been reported following a sustained virological response in patients with chronic hepatitis C virus (HCV) infection. We characterized the time-varying effect of DAAs on the risk of the occurrence of HCC in patients with cirrhosis and HCV infection. We analysed patients with cirrhosis and chronic HCV infection from the ANRS CO22 HEPATHER cohort study. We excluded patients with active HBV coinfection, liver transplantation or a past history of HCC. We used a flexible weighted effect cumulative exposure Cox model to characterize the time-varying effect of DAAs on the risk of HCC. A total of 3595 patients, mean age 59.3 years old, 65% men, were eligible for the study. Median follow-up was 36.8 months (IQR 24.6-47.1). DAAs were started during follow-up in 3292 patients. Three hundred and fifty-six HCCs were reported (275 treated, 81 untreated). Overall, a constant decrease in the risk of occurrence of HCC (vs untreated) was found from the start of treatment. Results were similar in patients without a history of decompensated cirrhosis (DC). Analysis of patients with a past history of DC showed a nonsignificant increase in the occurrence of HCC over the first 6 months, while the HR was significantly decreased at 14 months. These findings support the urgent initiation of DAAs in all patients.

Performance of the marginal structural cox model for estimating individual and joined effects of treatments given in combination.

BACKGROUND: The Marginal Structural Cox Model (Cox-MSM), an alternative approach to handle time-dependent confounder, was introduced for survival analysis and applied to estimate the joint causal effect of two time-dependent nonrandomized treatments on survival among HIV-positive subjects. Nevertheless, Cox-MSM performance in the case of multiple treatments has not been fully explored under different degree of time-dependent confounding for treatments or in case of interaction between treatments. We aimed to evaluate and compare the performance of the marginal structural Cox model (Cox-MSM) to the standard Cox model in estimating the treatment effect in the case of multiple treatments under different scenarios of time-dependent confounding and when an interaction between treatment effects is present. METHODS: We specified a Cox-MSM with two treatments including an interaction term for situations where an adverse event might be caused by two treatments taken simultaneously but not by each treatment taken alone. We simulated longitudinal data with two treatments and a time-dependent confounder affected by one or the two treatments. To fit the Cox-MSM, we used the inverse probability weighting method. We illustrated the method to evaluate the specific effect of protease inhibitors combined (or not) to other antiretroviral medications on the anal cancer risk in HIV-infected individuals, with CD4 cell count as time-dependent confounder. RESULTS: Overall, Cox-MSM performed better than the standard Cox model. Furthermore, we showed that estimates were unbiased when an interaction term was included in the model. CONCLUSION: Cox-MSM may be used for accurately estimating causal individual and joined treatment effects from a combination therapy in presence of time-dependent confounding provided that an interaction term is estimated.