Comparison of clinical prediction rules for ruling out cirrhosis in nonalcoholic fatty liver disease (NAFLD)
Résumé
BACKGROUND AND AIMS: Patients with nonalcoholic fatty liver disease (NAFLD) cirrhosis benefit from referral to subspecialty care. While several clinical prediction rules exist to identify advanced fibrosis, the cutoff for excluding cirrhosis due to NAFLD is unclear. This analysis compared clinical prediction rules for excluding biopsy-proven cirrhosis in NAFLD. METHODS: Adult patients were enrolled in the NASH Clinical Research Network (US) and the Newcastle Cohort (UK). Clinical and laboratory data were collected at enrolment, and a liver biopsy was taken within 1 year of enrolment. Optimal cutoffs for each score (eg, FIB-4) to exclude cirrhosis were derived from the US cohort, and sensitivity, specificity, positive predictive value, negative predictive value and AUROC were calculated. The cutoffs were evaluated in the UK cohort. RESULTS: 147/1483 (10%) patients in the US cohort had cirrhosis. All prediction rules had similarly high NPV (0.95-0.97). FIB-4 and NAFLD fibrosis scores were the most accurate in characterising patients as having cirrhosis (AUROC 0.84-0.86). 59/494 (12%) patients in the UK cohort had cirrhosis. Prediction rules had high NPV (0.92-0.96), and FIB-4 and NAFLD fibrosis score the most accurate in the prediction of cirrhosis in the UK cohort (AUROC 0.87-0.89). CONCLUSIONS: This cross-sectional analysis of large, multicentre international datasets shows that current clinical prediction rules perform well in excluding cirrhosis with appropriately chosen cutoffs. These clinical prediction rules can be used in primary care to identify patients, particularly those who are white, female, and \textless65, unlikely to have cirrhosis so higher-risk patients maintain access to specialty care.