Identifying Patients at Risk for Fibrosis in a Primary Care NAFLD Cohort

Abstract

Goals and Background: Using natural language processing to create a nonalcoholic fatty liver disease (NAFLD) cohort in primary care, we assessed advanced fibrosis risk with the Fibrosis-4 Index (FIB-4) and NAFLD Fibrosis Score (NFS) and evaluated risk score agreement. Materials and Methods: In this retrospective study of adults with radiographic evidence of hepatic steatosis, we calculated patient-level FIB-4 and NFS scores and categorized them by fibrosis risk. Risk category and risk score agreement was analyzed using weighted κ, Pearson correlation, and Bland-Altman analysis. A multinomial logistic regression model evaluated associations between clinical variables and discrepant FIB-4 and NFS results. Results: Of the 767 patient cohorts, 71% had a FIB-4 or NFS score in the indeterminate-risk or high-risk category for fibrosis. Risk categories disagreed in 43%, and scores would have resulted in different clinical decisions in 30% of the sample. The weighted κ statistic for risk category agreement was 0.41 [95% confidence interval (CI): 0.36-0.46] and the Pearson correlation coefficient for log FIB-4 and NFS was 0.66 (95% CI: 0.62-0.70). The multinomial logistic regression analysis identified black race (odds ratio=2.64, 95% CI: 1.84-3.78) and hemoglobin A1c (odds ratio=1.37, 95% CI: 1.23-1.52) with higher odds of having an NFS risk category exceeding FIB-4. Conclusions: In a primary care NAFLD cohort, many patients had elevated FIB-4 and NFS risk scores and these risk categories were often in disagreement. The choice between FIB-4 and NFS for fibrosis risk assessment can impact clinical decision-making and may contribute to disparities of care.