Prediction of fibrosis progression in chronic viral hepatitis

Prediction of liver fibrosis progression has a key role in the management of chronic viral hepatitis, as it will be translated into the future risk of cirrhosis and its various complications including hepatocellular carcinoma. Both hepatitis B and C viruses mainly lead to fibrogenesis induced by chronic inflammation and a continuous wound healing response. At the same time direct and indirect profibrogenic responses are also elicited by the viral infection. There are a handful of well-established risk factors for fibrosis progression including older age, male gender, alcohol use, high viral load and co-infection with other viruses. Metabolic syndrome is an evolving risk factor of fibrosis progression. The new notion of regression of advanced fibrosis or even cirrhosis is now strongly supported various clinical studies. Even liver biopsy retains its important role in the assessment of fibrosis progression, various non-invasive assessments have been adopted widely because of their non-invasiveness, which facilitates serial applications in large cohorts of subjects. Transient elastography is one of the most validated tools which has both diagnostic and prognostic role. As there is no single perfect test for liver fibrosis assessment, algorithms combining the most validated noninvasive methods should be considered as initial screening tools

Personalized management of cirrhosis by non-invasive tests of liver fibrosis

Owing to the high prevalence of various chronic liver diseases, cirrhosis is one of the leading causes of morbidity and mortality worldwide. In recent years, the development of non-invasive tests of fibrosis allows accurate diagnosis of cirrhosis and reduces the need for liver biopsy. In this review, we discuss the application of these non-invasive tests beyond the diagnosis of cirrhosis. In particular, their role in the selection of patients for hepatocellular carcinoma surveillance and varices screening is highlighted

Bacterial Microbiota Profiling in Gastritis without Helicobacter pylori Infection or Non-Steroidal Anti-Inflammatory Drug Use

Recent 16S ribosomal RNA gene (rRNA) molecular profiling of the stomach mucosa revealed a surprising complexity of microbiota. Helicobacter pylori infection and non-steroidal anti-inflammatory drug (NSAID) use are two main contributors to gastritis and peptic ulcer. However, little is known about the association between other members of the stomach microbiota and gastric diseases. In this study, cloning and sequencing of the 16S rRNA was used to profile the stomach microbiota from normal and gastritis patients. One hundred and thirty three phylotypes from eight bacterial phyla were identified. The stomach microbiota was found to be closely adhered to the mucosa. Eleven Streptococcus phylotypes were successfully cultivated from the biopsies. One to two genera represented a majority of clones within any of the identified phyla. We further developed two real-time quantitative PCR assays to quantify the relative abundance of the Firmicutes phylum and the Streptococcus genus. Significantly higher abundance of the Firmicutes phylum and the Streptococcus genus within the Firmicutes phylum was observed in patients with antral gastritis, compared with normal controls. This study suggests that the genus taxon level can largely represent much higher taxa such as the phylum. The clinical relevance and the mechanism underlying the altered microbiota composition in gastritis require further functional studies

Hepatocellular carcinoma surveillance after HBsAg seroclearance

Hepatitis B surface antigen (HBsAg) seroclearance is considered the functional cure and the optimal treatment endpoint for chronic hepatitis B (CHB). Patients with CHB who cleared HBsAg generally have a favorable clinical course with minimal risk of developing hepatocellular carcinoma (HCC) or cirrhotic complications. Nevertheless, a minority of patients still develop HCC despite HBsAg seroclearance. While patients with liver cirrhosis are still recommended for HCC surveillance, whether other non-cirrhotic patients who achieved HBsAg seroclearance should remain on HCC surveillance remains unclear. This review provides an overview of the incidence of HBsAg seroclearance, the factors associated with the occurrence of HBsAg seroclearance, the durability of HBsAg seroclearance, the risk of developing HCC after HBsAg seroclearance, the risk factors associated with HCC development after HBsAg seroclearance, the role of HCC risk scores, and the implications on HCC surveillance. Existing HCC risk scores have a reasonably good performance in patients after HBsAg seroclearance. In the era of artificial intelligence, future HCC risk prediction models based on artificial intelligence and longitudinal clinical data may further improve the prediction accuracy to establish a foundation of a risk score-based HCC surveillance strategy. As different novel hepatitis B virus (HBV) antiviral agents aiming at HBsAg seroclearance are under active development, new knowledge is anticipated on the natural history and HCC risk prediction of patients treated with new HBV drugs

Efficient Shapelet Discovery for Time Series Classification

Time-series shapelets are discriminative subsequences, recently found effective for time series classification (tsc). It is evident that the quality of shapelets is crucial to the accuracy of tsc. However, major research has focused on building accurate models from some shapelet candidates. To determine such candidates, existing studies are surprisingly simple, e.g., enumerating subsequences of some fixed lengths, or randomly selecting some subsequences as shapelet candidates. The major bulk of computation is then on building the model from the candidates. In this paper, we propose a novel efficient shapelet discovery method, called bspcover, to discover a set of high-quality shapelet candidates for model building. Specifically, bspcover generates abundant candidates via Symbolic Aggregate approXimation with sliding window, then prunes identical and highly similar candidates via Bloom filters, and similarity matching, respectively. We next propose a $p$p-Cover algorithm to efficiently determine discriminative shapelet candidates that maximally represent each time-series class. Finally, any existing shapelet learning method can be adopted to build a classification model. We have conducted extensive experiments with well-known time-series datasets and representative state-of-the-art methods. Results show that bspcover speeds up the state-of-the-art methods by more than 70 times, and the accuracy is often comparable to or higher than existing works

Type 2 Diabetes and Metformin Use Associate With Outcomes of Patients With Non-alcoholic Steatohepatitis-related, Child-Pugh A Cirrhosis

Background & Aims Factors that affect outcomes of patients with non-alcoholic steatohepatitis (NASH) related cirrhosis are unclear. We studied associations of type 2 diabetes, levels of hemoglobin A1c (HbA1c), and use antidiabetic medications with survival and liver-related events in patients with NASH and compensated cirrhosis. Methods We collected data from 299 patients with biopsy-proven NASH with Child-Pugh A cirrhosis from tertiary hospitals in Spain, Australia, Hong Kong, and Cuba, from April 1995 through December 2016. We obtained information on presence of type 2 diabetes, level of HbA1c, and use of antidiabetic medications. Cox proportional and competing risk models were used to estimate and compare rates of transplant-free survival, hepatic decompensation, and hepatocellular carcinoma (HCC). Results Two-hundred and twelve patients had type 2 diabetes at baseline and 8/87 patients developed diabetes during a median follow-up time of 5.1 y (range, 0.5–10.0 y). A lower proportion of patients with diabetes survived the entire follow-up period (38%) than of patients with no diabetes (81%) (adjusted hazard ratio [aHR], 4.23; 95% CI, 1.93–9.29). Higher proportions of patients with diabetes also had hepatic decompensation (51% vs 26% of patients with no diabetes; aHR, 2.03; 95% CI 1.005–4.11) and HCC (25% vs 7% of patients with no diabetes; aHR, 5.42; 95% CI 1.74–16.80). Averaged annual HbA1c levels over time were not associated with outcomes. Metformin use over time was associated with a significant reduction in risk of death or liver transplantation (aHR, 0.41; 95% CI, 0.26–0.45), hepatic decompensation (aHR, 0.80; 95% CI, 0.74–0.97), and HCC (aHR, 0.78; 95% CI, 0.69–0.96). Metformin significantly reduced risk of hepatic decompensation and HCC only in subjects with HbA1c levels above 7.0% (aHR, 0.97; 95% CI, 0.95–0.99 and aHR, 0.67; 95% CI, 0.43–0.94, respectively). Conclusions In an international cohort of patients with biopsy-proven NASH and Child-Pugh A cirrhosis, type 2 diabetes increased risk of death and liver-related outcomes, including HCC. Patients who took metformin had higher rates of survival and lower rates of decompensation and HCC

Low Accuracy of FIB-4 and NAFLD Fibrosis Scores for Screening for Liver Fibrosis in the Population

Background & AimsFibrosis-4 (FIB-4) and the nonalcoholic fatty liver disease fibrosis score (NFS) are the 2 most popular noninvasive blood-based serum tests proposed for widespread fibrosis screening. We therefore aimed to describe the accuracy of FIB-4 and NFS to detect elevated liver stiffness as an indicator of hepatic fibrosis in low-prevalence populations.MethodsThis study included a total of 5129 patients with concomitant measurement of FIB-4, NFS, and liver stiffness measurement (LSM) by Fibroscan (Echosens, France) from 5 independent population-based cohorts from Spain, Hong Kong, Denmark, England, and France; 3979 participants from the general population and 1150 from at-risk cohorts due to alcohol, diabetes, or obesity. We correlated LSM with FIB-4 and NFS, and calculated pre- and post-test predictive values of FIB-4 and NFS to detect elevated LSM at 8 kPa and 12 kPa cutoffs. The mean age was 53 ± 12 years, the mean body mass index was 27 ± 5 kg/m2, and 2439 (57%) were women. One in 10 patients (552; 11%) had liver stiffness ≥8 kPa, but 239 of those (43%) had a normal FIB-4, and 171 (31%) had normal NFS. The proportion of false-negatives was higher in at-risk patients than the general population. FIB-4 was false-negative in 11% of diabetic subjects, compared with 2.5% false-negatives with NFS. Waist circumference outperformed FIB-4 and NFS for detecting LSM ≥8 kPa in the general population. Almost one-third (28%–29%) of elevated FIB-4/NFS were false-positive in both the general population and at-risk cohorts.ConclusionsFIB-4 and NFS are suboptimal for screening purposes due to a high risk of overdiagnosis and a non-negligible percentage of false-negatives, especially in patients with risk factors for chronic liver disease. Waist circumference emerged as a potential first step to identify patients at risk for liver fibrosis in the general population