Danielle Brandman1, Marie Boyle2,3, Stuart McPherson2,3, Mark L Van Natta4, Arun J Sanyal5, Kris Kowdley6, Brent Neuschwander-Tetri7, Naga Chalasani8, Manal F Abdelmalek9, Norah A Terrault10, Art McCullough11, Ricki Bettencourt12, Cyrielle Caussy12, David E Kleiner13, Cynthia Behling14, James Tonascia4, Quentin M Anstee2, Rohit Loomba12. 1. Division of Gastroenterology, Department of Medicine, University of California San Francisco, San Francisco, California, USA. 2. Translational & Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK. 3. Newcastle NIHR Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK. 4. John Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA. 5. Department of Internal Medicine, Medical College of Virginia, Richmond, Virginia, USA. 6. Swedish Medical Group, Seattle, Washington, USA. 7. Division of Gastroenterology and Hepatology, Department of Medicine, Saint Louis University, Saint Louis, Missouri, USA. 8. Division of Gastroenterology and Hepatology, Department of Medicine, Indiana University, Indianapolis, Indiana, USA. 9. Division of Gastroenterology, Hepatology, and Nutrition, Duke University, Durham, North Carolina, USA. 10. Division of Gastroenterology and Liver, Keck Medicine, University of Southern California, Los Angeles, California, USA. 11. Department of Gastroenterology and Hepatology, Cleveland Clinic, Cleveland, Ohio, USA. 12. NAFLD Research Center, Department of Medicine, University of California San Diego, San Diego, California, USA. 13. Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA. 14. Analytic Pathology Medical Group, Sharp Memorial Hospital, San Diego, California, USA.
Abstract
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 <65, unlikely to have cirrhosis so higher-risk patients maintain access to specialty care.
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 <65, unlikely to have cirrhosis so higher-risk patients maintain access to specialty care.
Authors: Elizabeth M Brunt; David E Kleiner; Laura A Wilson; Patricia Belt; Brent A Neuschwander-Tetri Journal: Hepatology Date: 2011-02-11 Impact factor: 17.425
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Authors: Stuart McPherson; Tim Hardy; Jean-Francois Dufour; Salvatore Petta; Manuel Romero-Gomez; Mike Allison; Claudia P Oliveira; Sven Francque; Luc Van Gaal; Jörn M Schattenberg; Dina Tiniakos; Alastair Burt; Elisabetta Bugianesi; Vlad Ratziu; Christopher P Day; Quentin M Anstee Journal: Am J Gastroenterol Date: 2016-10-11 Impact factor: 10.864