The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD)-related advanced fibrosis and cirrhosis in the United States population utilizing AGILE 3 + and AGILE 4 scores: analysis of the NHANES 2017-2018 cycle.

BACKGROUND: Studies attempted to estimate MASLD-related advanced fibrosis (AF) and cirrhosis (MC) prevalence utilized tests with low positive predictive value (PPV) which overestimates prevalence. AGILE3 + and 4 scores were developed to increase the PPV of both; respectively. In this study, we used these scores to assess the prevalence of AF and MC. METHODS: Participants aged ≥ 18 years with VCTE exam in the NHANES 2017-2018 cycle were included. We excluded pregnant women, patients with excessive alcohol intake, hepatitis B/C, and ALT or AST > 500 IU/L. MASLD was defined with CAP score > 248 dB/m. MASLD subjects with AGILE 3 + score of ≥ 0.68 and AGILE 4 score of ≥ 0.57 were considered to have advanced fibrosis and cirrhosis; respectively. AGILE 3 + of 0.45-0.67 and AGILE 4 of 0.25-0.57 were grey zone, whereas AGILE 3 + < 0.45 and AGILE 4 < 0.25 were considered a rule-out. RESULTS: 1244 subjects were included in the final analysis. The Median age was 53 (51.4-54.6) years, 55.6% were male, median BMI was 33.8 kg/m2 and 41.1% had T2DM. Based on AGILE 3+, 80.3% of the MASLD population were at low risk for AF and 11.5% were in grey zone. The prevalence of AF due to MASLD was 8.1% corresponding to 4.5 million Americans. Based on AGILE 4 score, 96.5% of the MASLD population were at low risk for cirrhosis and 2.4% were in the grey zone. The prevalence of MASLD-cirrhosis was 1.1% corresponding to 610,000 Americans. CONCLUSION: Our results suggest that approximately 4.5 million people in the U.S. have AF and 0.6 million have cirrhosis due to MASLD.

Increased accuracy in identifying NAFLD with advanced fibrosis and cirrhosis: independent validation of the Agile 3+ and 4 scores.

BACKGROUND AND AIMS: We explored 2 novel scores, Agile 3+ and 4, to identify advanced fibrosis (≥F3) and cirrhosis (F4), respectively, in NAFLD and compared their diagnostic performances to liver stiffness measurement (LSM) by vibration-controlled transient elastography and fibrosis-4 index (FIB-4) (for Agile 3+). APPROACH AND RESULTS: This multicenter study included 548 NAFLD patients with laboratory testing, liver biopsy, and vibration-controlled transient elastography within 6 months. Agile 3+ and 4 were applied and compared with FIB-4 or LSM alone. Goodness of fit was evaluated using a calibration plot and discrimination using area under the receiver operating curve. Area under the receiver operating curves was compared using the Delong test. Dual cutoff approaches were applied to rule out and rule in ≥F3 and F4. Median (interquartile range) age was 58 (15) years. Median body mass index was 33.3 (8.5) kg/m2. Fifty-three percent had type 2 diabetes, 20% had F3, and 26% had F4. Agile 3+ demonstrated an area under the receiver operating curve of 0.85 (0.81; 0.88) similar to that of LSM [0.83 (0.79; 0.86), p=0.142] but significantly higher than that of FIB-4 [0.77 (0.73; 0.81), p<0.0001). Agile 4's area under the receiver operating curve [0.85 (0.81; 0.88)] was similar to that of LSM [0.85 (0.81; 0.88), p=0.065). However, the percentage of patients with indeterminate results was significantly lower with Agile scores compared with FIB-4 and LSM (Agile 3+: 14% vs. FIB-4: 31% vs. LSM: 13%, p<0.001; Agile 4: 23% vs. LSM: 38%, p<0.001). CONCLUSIONS: Agile 3+ and 4 are novel vibration-controlled transient elastography-based noninvasive scores that increase accuracy in the identification of advanced fibrosis and cirrhosis respectively and are ideal for clinical use due to a lower percentage of indeterminant outputs compared with FIB-4 or LSM alone.

Prevalence of at-risk NASH and its association with metabolic syndrome in US adults with NAFLD, 2017-2018.

Patients with metabolic syndrome (MetS) have a higher risk for NASH and significant fibrosis. Presence of NASH and advanced fibrosis are associated with adverse outcomes in patients with NAFLD. Using a noninvasive method, we determined the prevalence of at-risk NASH and its association with MetS components in a large population-based analysis. We used the 2017-2018 National Health and Nutrition Examination Survey and included adults ≥18 years with NAFLD (controlled attenuation parameter ≥274 dB/m). Pregnancy, subjects with other causes of liver disease or missing data were excluded. FibroScan-AST (FAST) score was calculated using aspartate aminotransferase, liver stiffness measurement, and controlled attenuation parameter. Patients with a FAST score >0.35 were considered to have at-risk NASH, defined as NASH with NAFLD activity score ≥4 and fibrosis stage ≥2 on liver biopsy. The sample included 687 patients. The overall prevalence of at-risk NASH was 11.6% (95% CI: 8.8-15.1) and was higher in males than females (15.8% vs. 6.5%; p < 0.001). Subjects with comorbidities (diabetes mellitus, obesity, MetS, and insulin resistance) had between 1.3 and 1.7 times higher prevalence than the general population. Among MetS components, elevated glucose/diabetes, large waist circumference, and low HDL were independent risk factors for at risk-NASH. The number of MetS components was also important-one additional component increased the odds of at-risk NASH by 2 times. The FAST score had the highest correlation with alanine aminotransferase (r= 0.70; p < 0.001). We estimated ~9 million people in the US have at-risk NASH and may benefit from active surveillance and therapy.

Simple diagnostic algorithm identifying at-risk nonalcoholic fatty liver disease patients needing specialty referral within the United States.

BACKGROUND: There is an urgent need to risk stratify patients with suspected nonalcoholic fatty liver disease (NAFLD) and identify those with fibrotic nonalcoholic steatohepatitis. This study aims to apply a simple diagnostic algorithm to identify subjects with at-risk NAFLD in the general population. AIM: To apply a simple diagnostic algorithm to identify subjects with at-risk NAFLD in the general population. METHODS: Adult subjects were included from the National Health and Nutrition Examination Survey database (2017-2018) if they had elevated alanine aminotransferase (ALT) and excluded if they had evidence of viral hepatitis or significant alcohol consumption. A fibrosis-4 (FIB4) cutoff of 1.3 differentiated patients with low risk vs high risk disease. If patients had FIB4 > 1.3, a FAST score < 0.35 ruled out advanced fibrosis. Patients with FAST > 0.35 were referred to a specialist. The same algorithm was applied to subjects with type 2 diabetes mellitus (T2DM). RESULTS: Three thousand six hundred and sixty-nine patients were identified who met all inclusion and exclusion criteria. From this cohort, 911 (28.6%) patients had elevated ALT of which 236 (22.9%) patients had elevated FIB4 scores ≥ 1.3. Among patients with elevated FIB4 score, 75 (24.4%) had elevated FAST scores, ruling in advanced fibrosis. This accounts for 2.0% of the overall study population. Applying this algorithm to 737 patients with T2DM, 213 (35.4%) patients had elevated ALT, 85 (37.9%) had elevated FIB4, and 42 (46.1%) had elevated FAST scores. This accounts for 5.7% of the population with T2DM. CONCLUSION: The application of this algorithm to identify at-risk NAFLD patients in need for specialty care is feasible and demonstrates that the vast majority of patients do not need subspecialty referral for NAFLD.