Noninvasive Means of Identifying Patients With High-Risk Nonalcoholic Fatty Liver Disease

Study data published in Clinical and Translational Gastroenterology describe the use of a multistep algorithm to identify patients with high-risk nonalcoholic fatty liver disease (NAFLD). Using certain clinical markers and results from noninvasive fibrosis tests (NITs), investigators were reliably able to identify patients with high-risk NAFLD and link them with gastroenterology-hepatology clinics. High NIT scores were associated with higher liver stiffness as confirmed by transient elastography (TE).

Current methods of identifying patients with high-risk NAFLD are lacking. Patients with NAFLD who progress to nonalcoholic steatohepatitis are at increased risk for cirrhosis and liver-related mortality. While histological fibrosis degree can be determined through liver biopsy, routine biopsy collection is invasive and impractical for routine practice.

To develop a noninvasive method of identifying high-risk NAFLD, investigators designed a multistep algorithm which incorporated medical record data and outcomes from NITs. The algorithm was tested in a cohort of patients recruited from primary care practices and endocrinology outpatient offices in the United States. Patients were eligible for study inclusion if they had a clinical diagnosis of type 2 diabetes mellitus and at least 2 other metabolic risk factors (hypertension, hyperlipidemia, or body mass index [BMI] >29.9 kg/m²). After enrollment, medical record review was conducted to extract demographic and clinical characteristics.

Based on laboratory figures, 3 NIT scores were calculated: (1) aspartate aminotransferase [AST]-to-platelet ratio index (APRI), (2) NAFLD Fibrosis Score (NFS), and (3) Fibrosis-4 (FIB-4) Index for Liver Fibrosis. Patients were considered to have high-risk NAFLD if they had at least 2 NIT values above certain thresholds (APRI >1.0, NFS >-1.45, or FIB-4 >1.45). Patients determined to have high-risk NAFLD were linked to gastrohepatology care for clinical assessment and TE; cutoff liver stiffness values of ≥8 and ≥12 kPa were used to determine the presence of clinically significant fibrosis and advanced fibrosis, respectively. The clinical characteristics of patients determined to have NAFLD per NIT scores were summarized.

Of 7555 patients initially screened, 1707 (22.6%) met inclusion criteria and 716 agreed to enroll. Among enrollees, 184 (25.7%) met NIT criteria for high-risk NAFLD and 103 patients agreed to undergo linkage assessment and TE. Mean age of patients who were linked to gastrohepatology care was 68.4±9.4 years, 49.5% were men, 56.3% were White, and 28.2% were Black.

Mean APRI, NFS, and FIB-4 scores in the linkage assessment group were 0.38±0.24, 0.36±1.03, and 1.98±0.87, respectively. Mean liver stiffness per TE was 6.7±4.2 kPa; 17.5% of patients had liver stiffness >8 kPa and 82.5% had liver stiffness ≤8 kPa. Eight patients (7.8%) had liver stiffness >12 kPa, indicating advanced fibrosis. Patients with liver stiffness >8 kPa had a younger mean age (61.3 vs 69.9 years; P =.0011) and a greater mean BMI (36.5 vs 30.5 kg/m²; P =.0014) compared against patients with liver stiffness ≤8 kPa.

Alanine aminotransferase and AST levels were elevated in the >8 vs ≤8 kPa group (both P <.0001); hemoglobin A1c levels were greater in the >8 kPa group (P =.0258).

Per these results, a simple multistep algorithm was able to identify patients with high-risk NAFLD and link them to appropriate care. TE data suggest that NIT score cutoffs could be reliably used to identify patients with clinically significant fibrosis. Investigators noted that the study was limited to 10 gastroenterology practices and that the cohort was small; results may not be generalizable to the larger population affected by NAFLD.

“[T]his study demonstrates that a stepwise prospective application of an algorithm using NITs and TE in clinical practice setting can lead to identification of patients with high-risk NAFLD,” investigators wrote. “Further studies are needed to use this or other similar algorithms in clinical practice using electronic health records.”

Disclosure: One study author declared affiliations with biotech, pharmaceutical, and/or device companies. Please see the original reference for a full list of authors’ disclosures. 

Reference

Younossi ZM, Pham H, Felix S, et al. Identification of high-risk patients with nonalcoholic fatty liver disease using noninvasive tests from primary care and endocrinology real-world practices. Clin Transl Gastroenterol. 2021;12(4):e00340. doi: 10.14309/ctg.0000000000000340

This article originally appeared on Gastroenterology Advisor