Author information
1Medical School, University of Western Australia, Nedlands, Western Australia, Australia.
2Department of Hepatology, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia.
3Department of Anatomic Pathology, Pathwest, Nedlands, Western Australia, Australia.
4Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, New South Wales, Australia.
5Unit for the Clinical Management of Digestive Diseases and CIBEREHD, Virgen del Rocio University Hospital. Institute of Biomedicine of Seville (CSIC/US/HUVR). University of Seville, Seville, Spain.
6Department of Digestive Disease, Institute of Endocrinology and Nutrition, University of Valladolid, Valladolid, Spain, CIBER Infectious Diseases.
Abstract
Background and aims: Management of NAFLD involves noninvasive prediction of fibrosis, which is a surrogate for patient outcomes. We aimed to develop and validate a model predictive of liver-related events (LREs) of decompensation and/or HCC and compare its accuracy with fibrosis models.
Approach and results: Patients with NAFLD from Australia and Spain who were followed for up to 28 years formed derivation (n = 584) and validation (n = 477) cohorts. Competing risk regression and information criteria were used for model development. Accuracy was compared with fibrosis models using time-dependent AUC analysis. During follow-up, LREs occurred in 52 (9%) and 11 (2.3%) patients in derivation and validation cohorts, respectively. Age, type 2 diabetes, albumin, bilirubin, platelet count, and international normalized ratio were independent predictors of LRE and were combined into a model [NAFLD outcomes score (NOS)]. The NOS model calibrated well [calibration slope, 0.99 (derivation), 0.98 (validation)] with excellent overall performance [integrated Brier score, 0.07 (derivation) and 0.01 (validation)]. A cutoff ≥1.3 identified subjects at a higher risk of LRE, (sub-HR 24.6, p < 0.001, 5-year cumulative incidence 38% vs 1.0%, respectively). The predictive accuracy at 5 and 10 years was excellent in both derivation (time-dependent AUC,0.92 and 0.90, respectively) and validation cohorts (time-dependent AUC,0.80 and 0.82, respectively). The NOS was more accurate than the fibrosis-4 or NAFLD fibrosis score for predicting LREs at 5 and 10 years ( p < 0.001).
Conclusions: The NOS model consists of readily available measures and has greater accuracy in predicting outcomes in patients with NAFLD than existing fibrosis models.