Title :

A tool to predict progression of non‐alcoholic fatty liver disease in severely obese patients

Author(s) :

Bauvin, Pierre [Auteur]
Delacôte, Claire [Auteur]
Lassailly, Guillaume [Auteur]
Ntandja Wandji, Line Carolle [Auteur]
Gnemmi, Viviane [Auteur]
Dautrecque, Flavien [Auteur]
Louvet, Alexandre [Auteur]
Caiazzo, Robert [Auteur]
Raverdy, Violeta [Auteur]
Leteurtre, Emmanuelle [Auteur]
Hétérogénéité, Plasticité et Résistance aux Thérapies des Cancers = Cancer Heterogeneity, Plasticity and Resistance to Therapies - UMR 9020 - U 1277 [CANTHER]
Pattou, François [Auteur]
Deuffic-Burban, Sylvie [Auteur]
Mathurin, Philippe [Auteur]

Journal title :

Liver International

Pages :

91-100

Publisher :

Wiley-Blackwell

Publication date :

2020-12-29

ISSN :

1478-3223

HAL domain(s) :

Sciences du Vivant [q-bio]

English abstract : [en]

Abstract Background & Aims Severely obese patients are a growing population at risk of non‐alcoholic fatty liver disease (NAFLD). Considering the increasing burden, a predictive tool of NAFLD progression would be of interest. ...
Show more >Abstract Background & Aims Severely obese patients are a growing population at risk of non‐alcoholic fatty liver disease (NAFLD). Considering the increasing burden, a predictive tool of NAFLD progression would be of interest. Our objective was to provide a tool allowing general practitioners to identify and refer the patients most at risk, and specialists to estimate disease progression and adapt the therapeutic strategy. Methods This predictive tool is based on a Markov model simulating steatosis, fibrosis and non‐alcoholic steatohepatitis (NASH) evolution. This model was developped from data of 1801 severely obese, bariatric surgery candidates, with histological assessment, integrating duration of exposure to risk factors. It is then able to predict current disease severity in the absence of assessment, and future cirrhosis risk based on current stage. Results The model quantifies the impact of sex, body‐mass index at 20, diabetes, age of overweight onset, on progression. For example, for 40‐year‐old severely obese patients seen by the general practitioners: (a) non‐diabetic woman overweight at 20, and (b) diabetic man overweight at 10, without disease assessment, the model predicts their current risk to have NASH or F3‐F4: for (a) 5.7% and 0.6%, for (b) 16.1% and 10.0% respectively. If those patients have been diagnosed F2 by the specialist, the model predicts the 5‐year cirrhosis risk: 1.8% in the absence of NASH and 6.0% in its presence for (a), 10.3% and 26.7% respectively, for (b). Conclusions This model provides a decision‐making tool to predict the risk of liver disease that could help manage severely obese patients.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Cancer Heterogeneity, Plasticity and Resistance to Therapies (CANTHER) - UMR 9020 - UMR 1277

Source :

Harvested from HAL