Researchers have developed a noninvasive score that can be used in a primary care setting to screen patients with dysmetabolism for fibrotic nonalcoholic steatohepatitis (NASH).
They used routine laboratory tests to develop a simple, noninvasive score to identify patients with fibrotic NASH, defined as NASH, nonalcoholic fatty liver disease (NAFLD) activity score (NAS) of 4 or higher, and fibrosis stage of 2 or higher. The derivation cohort included 264 patients with severe obesity who were undergoing liver biopsy from May 2020 to June 2021. Fifteen predictors were included in the score: age, gender, body mass index (BMI), waist circumference, glucose, HbA1c, total cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyltransferase, platelet count, albumin, and total bilirubin.
The researchers developed and internally validated the best predictive model using a bootstrapping stepwise logistic regression analysis and estimated performance by the area under the receiver-operating characteristic curve (AUROC). They externally validated the score using three independent European cohorts of patients at high risk for NAFLD: 370 patients in Finland, 947 in Italy, and 5,368 in England. The results were published early online March 28 by Clinical Gastroenterology and Hepatology.
The final predictive model, the Fibrotic NASH Index (FNI), combined levels of AST, HDL cholesterol, and HbA1c. The FNI is a predicted probability score and ranges from 0 to 1; that is, a patient with a score of 0.10 would have a 10% predicted probability of fibrotic NASH. The FNI can be calculated online. The performance of the FNI for fibrotic NASH was satisfactory in the derivation and external validation cohorts (AUROCs, 0.78 and 0.80 to 0.95, respectively). In the derivation cohort, rule-out and rule-in cutoffs were 0.10 for a sensitivity of 0.89 or greater (negative predictive value [NPV], 0.93) and 0.33 for a specificity of 0.90 or greater (positive predictive value [PPV], 0.57), respectively. In the external validation cohorts, sensitivity ranged from 0.87 to 1 (NPV, 0.99 to 1) and specificity ranged from 0.73 to 0.94 (PPV, 0.12 to 0.49) for the rule-out and rule-in cutoffs, respectively.
The authors noted that the score has been specifically designed for and validated in individuals with dysmetabolism and not in those referred for NAFLD in liver secondary/tertiary care settings. Also, they were unable to compare FNI with other noninvasive blood-based scores for fibrotic NASH because the latter were not available in most cohorts.
“In conclusion, we developed and validated the FNI, an accurate, simple, and affordable non-invasive score for fibrotic NASH based on routine laboratory tests, namely AST, HDL cholesterol, and HbA1c,” the authors wrote. “This score may help clinicians identify at-risk individuals in primary healthcare and diabetology/endocrinology clinics who require a referral to the liver specialist.”