Literature DB >> 32157645

Predictive Factors and Time to Development of Hepatic Decompensation in Patients with Non-alcoholic Fatty Liver Disease.

Heidi S Ahmed1,2, Natalie Pedersen3, Manju Bengaluru Jayanna3,4, Patrick Ten Eyck5, Antonio Sanchez3, Arvind R Murali3,6.   

Abstract

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of cirrhosis in the USA.
OBJECTIVES: We aimed to determine the time to develop hepatic events in patients with NAFLD and develop a simple model to identify patients at risk for hepatic decompensation.
DESIGN: Retrospective cohort study. PATIENTS: Seven hundred patients with NAFLD met inclusion criteria for the study. Patients were divided into model construction (n = 450) and validation (n = 250) cohorts. MAIN MEASURES: Demographic, clinical, and laboratory variables were gathered at the time of diagnosis of NAFLD. Kaplan-Meier analysis determined the time to development of hepatic events from initial diagnosis. A time-to-event prediction model was established in the model construction cohort using the multivariate Cox proportional hazards model and was then internally validated. KEY
RESULTS: Forty-nine (7%) patients developed hepatic events at a mean duration of 6.2 ± 4.2 years from initial diagnosis. Kaplan-Meier probability of developing a hepatic event at 5-, 10-, and 12-year intervals was 4.8%, 10.6%, and 11.3%, respectively. Age, presence of diabetes, and platelet count were identified as significant variables to predict hepatic events. NAFLD decompensation risk score was developed as "age × 0.06335 + presence of diabetes (yes = 1, no = 0) × 0.92221 - platelet count × 0.01522" to predict the probability of hepatic decompensation. Risk score model had an area under the curve of 0.89 (95% CI = 0.92, 0.86) and it performed well in both the validation (0.91, 0.87-0.94) and the overall cohort (0.89, 0.87-0.91).
CONCLUSIONS: A significant proportion of patients with NAFLD developed hepatic decompensation. We have provided a simple, objective model to help identify "at-risk" patients.

Entities:  

Keywords:  cirrhosis; fatty liver; liver disease; metabolic syndrome; prevention

Mesh:

Year:  2020        PMID: 32157645      PMCID: PMC7210346          DOI: 10.1007/s11606-020-05725-1

Source DB:  PubMed          Journal:  J Gen Intern Med        ISSN: 0884-8734            Impact factor:   5.128


  27 in total

1.  Competing risks and prognostic stages of cirrhosis: a 25-year inception cohort study of 494 patients.

Authors:  G D'Amico; L Pasta; A Morabito; M D'Amico; M Caltagirone; G Malizia; F Tinè; G Giannuoli; M Traina; G Vizzini; F Politi; A Luca; R Virdone; A Licata; L Pagliaro
Journal:  Aliment Pharmacol Ther       Date:  2014-03-24       Impact factor: 8.171

Review 2.  Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.

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Journal:  Stat Med       Date:  1996-02-28       Impact factor: 2.373

Review 3.  Comparison of laboratory tests, ultrasound, or magnetic resonance elastography to detect fibrosis in patients with nonalcoholic fatty liver disease: A meta-analysis.

Authors:  Guangqin Xiao; Sixian Zhu; Xiao Xiao; Lunan Yan; Jiayin Yang; Gang Wu
Journal:  Hepatology       Date:  2017-09-26       Impact factor: 17.425

4.  Prevalence of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis among a largely middle-aged population utilizing ultrasound and liver biopsy: a prospective study.

Authors:  Christopher D Williams; Joel Stengel; Michael I Asike; Dawn M Torres; Janet Shaw; Maricela Contreras; Cristy L Landt; Stephen A Harrison
Journal:  Gastroenterology       Date:  2010-09-19       Impact factor: 22.682

5.  Prevalence of hepatic steatosis in an urban population in the United States: impact of ethnicity.

Authors:  Jeffrey D Browning; Lidia S Szczepaniak; Robert Dobbins; Pamela Nuremberg; Jay D Horton; Jonathan C Cohen; Scott M Grundy; Helen H Hobbs
Journal:  Hepatology       Date:  2004-12       Impact factor: 17.425

6.  Simple non-invasive fibrosis scoring systems can reliably exclude advanced fibrosis in patients with non-alcoholic fatty liver disease.

Authors:  Stuart McPherson; Stephen F Stewart; Elsbeth Henderson; Alastair D Burt; Christopher P Day
Journal:  Gut       Date:  2010-09       Impact factor: 23.059

7.  Neutrophil to lymphocyte ratio: a new marker for predicting steatohepatitis and fibrosis in patients with nonalcoholic fatty liver disease.

Authors:  Naim Alkhouri; Gareth Morris-Stiff; Carla Campbell; Rocio Lopez; Tarek Abu-Rajab Tamimi; Lisa Yerian; Nizar N Zein; Ariel E Feldstein
Journal:  Liver Int       Date:  2011-09-08       Impact factor: 5.828

8.  Regression modelling strategies for improved prognostic prediction.

Authors:  F E Harrell; K L Lee; R M Califf; D B Pryor; R A Rosati
Journal:  Stat Med       Date:  1984 Apr-Jun       Impact factor: 2.373

Review 9.  Percutaneous liver biopsy in clinical practice.

Authors:  Bandar Al Knawy; Mitchell Shiffman
Journal:  Liver Int       Date:  2007-11       Impact factor: 5.828

10.  Development and validation of a simple NAFLD clinical scoring system for identifying patients without advanced disease.

Authors:  S A Harrison; D Oliver; H L Arnold; S Gogia; B A Neuschwander-Tetri
Journal:  Gut       Date:  2008-04-04       Impact factor: 23.059

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