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Identifying High-Risk NASH Patients: What We Know so Far.

ABSTRACT: Steatosis is a condition of hepatic fat overload that is associated with overweight and the metabolic syndrome. Nonalcoholic fatty liver disease (NAFLD) has become the most common liver disease with a global impact on healthcare. A proportion of NAFLD patients develops nonalcoholic steatohepatitis (NASH), liver fibrosis, cirrhosis or hepatocellular carcinoma (HCC). Identifying patients at risk for potentially life-threatening complications is crucial in their prevention, surveillance and treatment. In addition to hepatic disease progression (cirrhosis, portal hypertension, HCC), NAFLD patients are also at risk of cardiovascular and metabolic diseases as well as extrahepatic malignancies. Liver fibrosis is related to morbidity and mortality in NASH patients, and biomarkers, imaging techniques (ultrasound, elastography, MRI) as well as liver biopsy help in diagnosing fibrosis. In this review, we discuss the tools for identifying patients at risk and their reasonable application in clinical routine in order to stratify prevention and treatment of this emerging disease.

SUBMITTER: Schulz M

PROVIDER: S-EPMC7493213 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identifying High-Risk NASH Patients: What We Know so Far.

Schulz Marten M Tacke Frank F

Hepatic medicine : evidence and research 20200821

Steatosis is a condition of hepatic fat overload that is associated with overweight and the metabolic syndrome. Nonalcoholic fatty liver disease (NAFLD) has become the most common liver disease with a global impact on healthcare. A proportion of NAFLD patients develops nonalcoholic steatohepatitis (NASH), liver fibrosis, cirrhosis or hepatocellular carcinoma (HCC). Identifying patients at risk for potentially life-threatening complications is crucial in their prevention, surveillance and treatme ...[more]

PMID: 32982495

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Project description:ObjectiveMany healthcare systems employ population-based risk scores to prospectively identify patients at high risk of poor outcomes, but it is unclear whether single point-in-time scores adequately represent future risk. We sought to identify and characterize latent subgroups of high-risk patients based on risk score trajectories.Study designObservational study of 7289 patients discharged from Veterans Health Administration (VA) hospitals during a 1-week period in November 2012 and categorized in the top 5th percentile of risk for hospitalization.MethodsUsing VA administrative data, we calculated weekly risk scores using the validated Care Assessment Needs model, reflecting the predicted probability of hospitalization. We applied the non-parametric k-means algorithm to identify latent subgroups of patients based on the trajectory of patients' hospitalization probability over a 2-year period. We then compared baseline sociodemographic characteristics, comorbidities, health service use, and social instability markers between identified latent subgroups.ResultsThe best-fitting model identified two subgroups: moderately high and persistently high risk. The moderately high subgroup included 65% of patients and was characterized by moderate subgroup-level hospitalization probability decreasing from 0.22 to 0.10 between weeks 1 and 66, then remaining constant through the study end. The persistently high subgroup, comprising the remaining 35% of patients, had a subgroup-level probability increasing from 0.38 to 0.41 between weeks 1 and 52, and declining to 0.30 at study end. Persistently high-risk patients were older, had higher prevalence of social instability and comorbidities, and used more health services.ConclusionsOn average, one third of patients initially identified as high risk stayed at very high risk over a 2-year follow-up period, while risk for the other two thirds decreased to a moderately high level. This suggests that multiple approaches may be needed to address high-risk patient needs longitudinally or intermittently.

Dataset Information

Identifying High-Risk NASH Patients: What We Know so Far.

Publications

Identifying High-Risk NASH Patients: What We Know so Far.

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