Skip to main content
eScholarship
Open Access Publications from the University of California

UC San Diego

UC San Diego Previously Published Works bannerUC San Diego

Validation of Serum Test for Advanced Liver Fibrosis in Patients With Nonalcoholic Steatohepatitis

Published Web Location

https://www.sciencedirect.com/science/article/pii/S1542356518312473
No data is associated with this publication.
Abstract

Background & aims

We analyzed markers of fibrosis in serum samples from patients with nonalcoholic fatty liver disease (NAFLD), assessed by liver biopsy. We used serum levels of markers to develop an algorithm to discriminate patients with advanced fibrosis from those with mild or moderate fibrosis and validated its performance in 2 independent cohorts of patients with NAFLD.

Methods

We performed a retrospective analysis of serum samples from 396 patients with NAFLD and different stages of fibrosis (F0-F4), collected from 2007 through 2017 on the day of liver biopsy (training cohort 1). We measured serum concentrations of alpha-2 macroglobulin (A2M), hyaluronic acid (HA), and TIMP metallopeptidase inhibitor 1 (TIMP1), and used measurements to develop an algorithm that could discriminate patients with NAFLD with advanced fibrosis (F3-F4; 24.1% of cohort) from those with mild or moderate fibrosis (F0-F2; 79.5% of cohort). We validated the algorithm using serum samples collected from a separate 396 patients from the same time period and location (validation cohort 1), as well as 244 patients with NAFLD evaluated at a separate location, from 2011 through 2017, within a median of 11 days of liver biopsy (cohort 2).

Results

The algorithm identified patients with advanced fibrosis vs mild or moderate fibrosis in training cohort 1 with an area under the receiver operating characteristic (AUROC) curve of 0.867 (95% CI, 0.827-0.907), 84.8% sensitivity (95% CI, 75.5%-91.0%), and 72.3% specificity (95% CI, 66.9%-77.3%), at a cutoff score of 17. The AUROC for the combined validation cohorts 1 and 2 (n=640) was 0.856 (95% CI, 0.820-0.892), identifying patients with 79.7% sensitivity (95% CI, 71.9%-86.2%) and 75.7% specificity (95% CI, 71.8%-79.4%) at the predetermined cutoff score of 17. The algorithm had negative predictive values that ranged from 92.5% to 94.7% in the validation cohorts; it correctly classified 90.0% of F0 samples, 75.0% of F1 samples, 77.4% of F3 samples, and 94.4% of F4 samples.

Conclusion

We developed an algorithm that identifies patients with advanced fibrosis from those with mild to moderate fibrosis in patients with NAFLD with an AUROC value of approximately 0.86, based on levels of serum biomarkers. We validated the findings in 2 separate sets of patients with biopsy-proven NAFLD. The algorithm can be used non-invasively to determine risk of advanced fibrosis in patients with NAFLD.

Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.

Item not freely available? Link broken?
Report a problem accessing this item