NEW YORK (Reuters Health) – Researchers from the U.S. and Canada have teamed up to develop and validate a model for predicting end-stage liver disease (ESLD) in people living with HIV (PWH).
“This model of readily accessible clinical parameters predicted ESLD in a large diverse population of PWH,” they write in JAIDS Journal of Acquired Immune Deficiency Syndromes.
ESLD remains a leading non-AIDS-related cause of death in PWH, largely due to a higher prevalence of chronic viral hepatitis in this patient group, relative to the general population. However, there current is no “cohesive and comprehensive” tool to predict ESLD.
Dr. H. Nina Kim of the University of Washington in Seattle and colleagues developed and validated such a tool using data from PWH participating in 12 cohorts of the North American AIDS Cohort Collaboration on Research and Design between 2000 and 2016.
At baseline, all participants had a Fibrosis-4 Index for liver fibrosis (FIB-4) greater than 1.45, which is suggestive of liver disease without ESLD.
The training set included 13,787 PWH (mean age, 48 years; 82% men; 54% Black), with 390 ESLD events occurring over an average of 5.4 years.
Among the ESLD cases, 52% had hepatitis C virus (HCV), 15% had hepatitis B virus (HBV) and 31% had alcohol use disorder. The incidence rate of ESLD per 1,000 person-year was 8.21 with these comorbidities versus 2.79 without.
According to the researchers, 12 factors together predicted ESLD risk moderately well with a C-statistic of 0.79 (95% CI, 0.76 to 0.81): age, sex, race/ethnicity, chronic hepatitis B or C, and routinely collected laboratory values reflecting hepatic impairment (serum albumin, AST, total bilirubin, platelets) and lipid metabolism (triglycerides, HDL, total cholesterol).
This model also performed well in the test (validation) set made up of 3,173 patients (C-statistic, 0.81; 95% CI, 0.76 to 0.86), the team reports.
“This prediction model for ESLD is among the first of its kind, derived for PWH using routinely collected data and carefully adjudicated outcomes. It can be readily calculated using standard laboratory measures with the possibility of auto-populating its elements if embedded within the electronic health record, a key practical feature for risk estimations when used,” write Dr. Kim and colleagues.
The model does not rely on the diagnosis of cirrhosis, which is often missed or poorly documented, and is more applicable than existing liver-related models such as Child-Turcotte Pugh or MELD scores, they add.
The researchers developed an online calculator based on this prediction model for clinicians to determine their patient’s risk of ESLD.
“This ESLD estimator could have a key role in identifying those patients who will require more attention as well as guiding counseling and decision-making in ESLD prevention and management,” they conclude.
SOURCE: https://bit.ly/3pCAqEd JAIDS Journal of Acquired Immune Deficiency Syndromes, online December 14, 2021.
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