Quantifying the benefit of nonselective beta-blockers in the prevention of hepatic decompensation: A Bayesian reanalysis of the PREDESCI trial.

BACKGROUND AND AIMS: Beta-blockers have been studied for the prevention of variceal bleeding and, more recently, for the prevention of all-cause decompensation. Some uncertainties regarding the benefit of beta-blockers for the prevention of decompensation remain. Bayesian analyses enhance the interpretation of trials. The purpose of this study was to provide clinically meaningful estimates of both the probability and magnitude of the benefit of beta-blocker treatment across a range of patient types. APPROACH AND RESULTS: We undertook a Bayesian reanalysis of PREDESCI incorporating 3 priors (moderate neutral, moderate optimistic, and weak pessimistic). The probability of clinical benefit was assessed considering the prevention of all-cause decompensation. Microsimulation analyses were done to determine the magnitude of the benefit. In the Bayesian analysis, the probability that beta-blockers reduce all-cause decompensation was >0.93 for all priors. The Bayesian posterior hazard ratios (HR) for decompensation ranged from 0.50 (optimistic prior, 95% credible interval 0.27-0.93) to 0.70 (neutral prior, 95% credible interval 0.44-1.12). Exploring the benefit of treatment using microsimulation highlights substantial treatment benefits. For the neutral prior derived posterior HR and a 5% annual incidence of decompensation, at 10 years, an average of 497 decompensation-free years per 1000 patients were gained with treatment. In contrast, at 10 years 1639 years per 1000 patients were gained from the optimistic prior derived posterior HR and a 10% incidence of decompensation. CONCLUSIONS: Beta-blocker treatment is associated with a high probability of clinical benefit. This likely translates to a substantial gain in decompensation-free life years at the population level.

The Natural History of Advanced Chronic Liver Disease Defined by Transient Elastography.

BACKGROUND & AIMS: The clinical course of cirrhosis does not follow a predictable trajectory. Transient elastography (TE) is commonly used in clinical practice to diagnose liver fibrosis and increasingly to risk stratify patients. The aim of this study was to assess the natural history of advanced chronic liver disease (ACLD) defined by TE using electronic health record (EHR) data in a multistate framework. METHODS: TE data were collected between 2008 and 2019. Patients with a liver stiffness measurement (LSM) >10 kPa were included. Disease and procedure code information held in EHR was analyzed. Clinical events including decompensation, hepatocellular carcinoma (HCC), and death were identified. Outcomes were described in a multistate model using flexible parametric survival methods including LSM and the albumin bilirubin (ALBI) score. RESULTS: Three thousand and twenty eight patients were included. Median follow up was 3.1 years. LSM and ALBI were associated with the development of varices and decompensation, and ALBI, age, sex, and viral liver disease were associated with the development of HCC from the compensated state. The cumulative incidence of HCC before decompensation was low for patients with alcohol-related liver disease (3.8%) and nonalcoholic fatty liver disease (1.3%) at 5 years after TE. Importantly, death was predicted to occur before decompensation or HCC in most cases. CONCLUSIONS: Liver stiffness, ALBI score, and disease etiology are each associated with outcomes in a large contemporary cohort with ACLD. EHR data can be used to define clinical progression in these patients, facilitating large clinical effectiveness trials and cost-effectiveness analyses.

Systematic review: development of a consensus code set to identify cirrhosis in electronic health records.

BACKGROUND: Electronic health records (EHRs) collate longitudinal data that can be used to facilitate large-scale research in patients with cirrhosis. However, there is no consensus code set to define the presence of cirrhosis in EHR. This systematic review aims to evaluate the validity of diagnostic coding in cirrhosis and to synthesise a comprehensive set of ICD-10 codes for future EHR research. METHOD: MEDLINE and EMBASE databases were searched for studies that used EHR to identify cirrhosis and cirrhosis-related complications. Validated code sets were summarised, and the performance characteristics were extracted. Citation analysis was done to inform development of a consensus code set. This was then validated in a cohort of patients. RESULTS: One thousand six hundred twenty-six records were screened, and 18 studies were identified. The positive predictive value (PPV) was the most frequently reported statistical estimate and was ≥80% in 17/18 studies. Citation analyses showed continued variation in those used in contemporary research practice. Nine codes were identified as those most frequently used in the literature and these formed the consensus code set. This was validated in diverse patient populations from Europe and North America and showed high PPV (83%-89%) and greater sensitivity for the identification of cirrhosis than the most often used code set in the recent literature. CONCLUSION: There is variation in code sets used to identify cirrhosis in contemporary research practice. A consensus set has been developed and validated, showing improved performance, and is proposed to align EHR study designs in cirrhosis to facilitate international collaboration and comparisons.