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- Ekstedt, Mattias, et al.
(författare)
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Fibrosis stage is the strongest predictor for disease-specific mortality in NAFLD after up to 33 years of follow-up
- 2015
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Ingår i: Hepatology. - : John Wiley & Sons. - 0270-9139 .- 1527-3350. ; 61:5, s. 1547-1554
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Tidskriftsartikel (refereegranskat)abstract
- Background and rationale for the study: Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease in the Western world, strongly associated with insulin resistance and the metabolic syndrome. Nonalcoholic steatohepatitis, i.e. fatty liver accompanied by necroinflammatory changes, is mostly defined by the NAFLD activity score (NAS). The aim of the current study was to determine disease-specific mortality in NAFLD, and evaluate the NAS and fibrosis stage as prognostic markers for overall and disease-specific mortality. Methods: In a cohort study, data from 229 well-characterized patients with biopsy-proven NAFLD were collected. Mean follow-up was 26.4 (± 5.6, range 6-33) years. A reference population was obtained from the National Registry of Population, and information on time and cause of death were obtained from the Registry of Causes of Death. Main results: NAFLD patients had an increased mortality compared with the reference population (HR 1.29, CI 1.04-1.59, p=0.020), with increased risk of cardiovascular disease (HR 1.55, CI 1.11-2.15, p=0.01), hepatocellular carcinoma (HR 6.55, CI 2.14-20.03, p=0.001), infectious disease (HR 2.71, CI 1.02-7.26, p=0.046), and cirrhosis (HR 3.2, CI 1.05-9.81, p=0.041). Overall mortality was not increased in patients with NAS 5-8 and fibrosis stage 0-2 (HR 1.41, CI 0.97-2.06, p=0.07), whereas patients with fibrosis stage 3-4, irrespective of NAS, had increased mortality (HR 3.3, CI 2.27-4.76, p<0.001). Conclusions: NAFLD patients have increased risk of death, with a high risk of death from cardiovascular disease and liver-related disease. The NAS was not able to predict overall mortality, whereas fibrosis stage predicted both overall and disease-specific mortality.
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| 3. |
- Lykiardopoulos, Byron, et al.
(författare)
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Development of Serum Marker Models to Increase Diagnostic Accuracy of Advanced Fibrosis in Nonalcoholic Fatty Liver Disease: The New LINKI Algorithm Compared with Established Algorithms
- 2016
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Ingår i: PLOS ONE. - : PUBLIC LIBRARY SCIENCE. - 1932-6203. ; 11:12
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Tidskriftsartikel (refereegranskat)abstract
- Background and Aim Detection of advanced fibrosis (F3-F4) in nonalcoholic fatty liver disease (NAFLD) is important for ascertaining prognosis. Serum markers have been proposed as alternatives to biopsy. We attempted to develop a novel algorithm for detection of advanced fibrosis based on a more efficient combination of serological markers and to compare this with established algorithms. Methods We included 158 patients with biopsy-proven NAFLD. Of these, 38 had advanced fibrosis. The following fibrosis algorithms were calculated: NAFLD fibrosis score, BARD, NIKEI, NASH-CRN regression score, APRI, FIB-4, Kings score, GUCI, Lok index, Forns score, and ELF. Study population was randomly divided in a training and a validation group. A multiple logistic regression analysis using bootstrapping methods was applied to the training group. Among many variables analyzed age, fasting glucose, hyaluronic acid and AST were included, and a model (LINKI-1) for predicting advanced fibrosis was created. Moreover, these variables were combined with platelet count in a mathematical way exaggerating the opposing effects, and alternative models (LINKI-2) were also created. Models were compared using area under the receiver operator characteristic curves (AUROC). Results Of established algorithms FIB-4 and Kings score had the best diagnostic accuracy with AUROCs 0.84 and 0.83, respectively. Higher accuracy was achieved with the novel LINKI algorithms. AUROCs in the total cohort for LINKI-1 was 0.91 and for LINKI-2 models 0.89. Conclusion The LINKI algorithms for detection of advanced fibrosis in NAFLD showed better accuracy than established algorithms and should be validated in further studies including larger cohorts.
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