Systematic review: identifying patients with chronic hepatitis C in need of early treatment and intensive monitoring--predictors and predictive models of disease progression.

BACKGROUND: Advances in hepatitis C therapies have led to increasing numbers of patients seeking treatment. As a result, logistical and financial concerns regarding how treatment can be provided to all patients with chronic hepatitis C (CHC) have emerged. AIM: To evaluate predictors and predictive models of histological progression and clinical outcomes for patients with CHC.
METHODS: MEDLINE via PubMed, EMBASE, Web of Science and Scopus were searched for studies published between January 2003 and June 2014. Two authors independently reviewed articles to select eligible studies and performed data abstraction.
RESULTS: Twenty-nine studies representing 5817 patients from 20 unique cohorts were included. The outcome incidence rates were widely variable: 16-61% during median follow-up of 2.5-10 years for fibrosis progression; 13-40% over 2.3-14.4 years for hepatic decompensation and 8-47% over 3.9-14.4 years for overall mortality. Multivariate analyses showed that baseline steatosis and baseline fibrosis score were the most consistent predictors of fibrosis progression (significant in 6/21 and 5/21, studies, respectively) while baseline platelet count (significant in 6/13 studies), aspartate and alanine aminotransferase (AST/ALT) ratio, albumin, bilirubin and age (each significant in 4/13 studies) were the most consistent predictors of clinical outcomes. Five studies developed predictive models but none were externally validated.
CONCLUSIONS: Our review identified the variables that most consistently predict outcomes of patients with chronic hepatitis C allowing the application of risk based approaches to identify patients in need of early treatment and intensive monitoring. This approach maximises effective use of resources and costly new direct-acting anti-viral agents.