A model to identify heavy drinkers at high ...
Document type :
Article dans une revue scientifique: Article original
PMID :
Permalink :
Title :
A model to identify heavy drinkers at high risk for liver disease progression
Author(s) :
Delacote, Claire [Auteur]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Bauvin, Pierre [Auteur]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Louvet, Alexandre [Auteur]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Dautrecque, Flavien [Auteur]
Service des Maladies de l'Appareil Digestif et de la Nutrition [CHRU Lille]
Ntandja Wandji, Line [Auteur]
Service des Maladies de l'Appareil Digestif et de la Nutrition [CHRU Lille]
Lassailly, Guillaume [Auteur]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Voican, Cosmin [Auteur]
Université Paris-Saclay
AP-HP - Hôpital Antoine Béclère [Clamart]
Laboratoire d'Excellence en Recherche sur le Médicament et l'Innovation Thérapeutique [Châtenay-Malabry] [LabEx LERMIT]
Perlemuter, Gabriel [Auteur]
Université Paris-Saclay
AP-HP - Hôpital Antoine Béclère [Clamart]
Laboratoire d'Excellence en Recherche sur le Médicament et l'Innovation Thérapeutique [Châtenay-Malabry] [LabEx LERMIT]
Naveau, Sylvie [Auteur]
Université Paris-Saclay
AP-HP - Hôpital Antoine Béclère [Clamart]
Laboratoire d'Excellence en Recherche sur le Médicament et l'Innovation Thérapeutique [Châtenay-Malabry] [LabEx LERMIT]
Mathurin, Philippe [Auteur]
Service des Maladies de l'Appareil Digestif et de la Nutrition [CHRU Lille]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Deuffic-Burban, Sylvie [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Bauvin, Pierre [Auteur]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Louvet, Alexandre [Auteur]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Dautrecque, Flavien [Auteur]
Service des Maladies de l'Appareil Digestif et de la Nutrition [CHRU Lille]
Ntandja Wandji, Line [Auteur]
Service des Maladies de l'Appareil Digestif et de la Nutrition [CHRU Lille]
Lassailly, Guillaume [Auteur]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Voican, Cosmin [Auteur]
Université Paris-Saclay
AP-HP - Hôpital Antoine Béclère [Clamart]
Laboratoire d'Excellence en Recherche sur le Médicament et l'Innovation Thérapeutique [Châtenay-Malabry] [LabEx LERMIT]
Perlemuter, Gabriel [Auteur]
Université Paris-Saclay
AP-HP - Hôpital Antoine Béclère [Clamart]
Laboratoire d'Excellence en Recherche sur le Médicament et l'Innovation Thérapeutique [Châtenay-Malabry] [LabEx LERMIT]
Naveau, Sylvie [Auteur]
Université Paris-Saclay
AP-HP - Hôpital Antoine Béclère [Clamart]
Laboratoire d'Excellence en Recherche sur le Médicament et l'Innovation Thérapeutique [Châtenay-Malabry] [LabEx LERMIT]
Mathurin, Philippe [Auteur]
Service des Maladies de l'Appareil Digestif et de la Nutrition [CHRU Lille]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Deuffic-Burban, Sylvie [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
Journal title :
Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
Abbreviated title :
Clin. Gastroenterol. Hepatol.
Publication date :
2020-01-10
ISSN :
1542-7714
Keyword(s) :
ASH
Prognostic Factor
Alcohol-Associated Liver Disease
Intermediate-Term Outcome
Prognostic Factor
Alcohol-Associated Liver Disease
Intermediate-Term Outcome
HAL domain(s) :
Sciences du Vivant [q-bio]
English abstract : [en]
Alcohol-related liver disease (ALD) causes chronic liver disease. We investigated how information on patients' drinking history and amount, stage of liver disease, and demographic feature can be used to determine risk of ...
Show more >Alcohol-related liver disease (ALD) causes chronic liver disease. We investigated how information on patients' drinking history and amount, stage of liver disease, and demographic feature can be used to determine risk of disease progression. We collected data from 2334 heavy drinkers (50 g/day or more) with persistently abnormal results from liver tests who had been admitted to a hepato-gastroenterology unit in France from January 1982 through December 1997; patients with a recorded duration of alcohol abuse were assigned to the development cohort (n=1599; 75% men) or the validation cohort (n=735; 75% men), based on presence of a liver biopsy. We collected data from both cohorts on patient history and disease stage at the time of hospitalization. For the development cohort, severity of the disease was scored by the METAVIR (due to the availability of liver histology reports); in the validation cohort only the presence of liver complications was assessed. We developed a model of ALD progression and occurrence of liver complications (hepatocellular carcinoma and/or liver decompensation) in association with exposure to alcohol, age at the onset of heavy drinking, amount of alcohol intake, sex and body mass index. The model was fitted to the development cohort and then evaluated in the validation cohort. We then tested the ability of the model to predict disease progression for any patient profile (baseline evaluation). Patients with a 5-y weighted risk of liver complications greater than 5% were considered at high risk for disease progression. Model results are given for the following patient profiles: men and women, 40 y old, who started drinking at an age of 25 y, drank 150 g/day, and had a body mass index of 22 kg/m2 We developed a Markov model that integrates data on level and duration of alcohol use to identify patients at high risk of liver disease progression. This model might be used to adapt patient care pathways.Show less >
Show more >Alcohol-related liver disease (ALD) causes chronic liver disease. We investigated how information on patients' drinking history and amount, stage of liver disease, and demographic feature can be used to determine risk of disease progression. We collected data from 2334 heavy drinkers (50 g/day or more) with persistently abnormal results from liver tests who had been admitted to a hepato-gastroenterology unit in France from January 1982 through December 1997; patients with a recorded duration of alcohol abuse were assigned to the development cohort (n=1599; 75% men) or the validation cohort (n=735; 75% men), based on presence of a liver biopsy. We collected data from both cohorts on patient history and disease stage at the time of hospitalization. For the development cohort, severity of the disease was scored by the METAVIR (due to the availability of liver histology reports); in the validation cohort only the presence of liver complications was assessed. We developed a model of ALD progression and occurrence of liver complications (hepatocellular carcinoma and/or liver decompensation) in association with exposure to alcohol, age at the onset of heavy drinking, amount of alcohol intake, sex and body mass index. The model was fitted to the development cohort and then evaluated in the validation cohort. We then tested the ability of the model to predict disease progression for any patient profile (baseline evaluation). Patients with a 5-y weighted risk of liver complications greater than 5% were considered at high risk for disease progression. Model results are given for the following patient profiles: men and women, 40 y old, who started drinking at an age of 25 y, drank 150 g/day, and had a body mass index of 22 kg/m2 We developed a Markov model that integrates data on level and duration of alcohol use to identify patients at high risk of liver disease progression. This model might be used to adapt patient care pathways.Show less >
Language :
Anglais
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
CHU Lille
Inserm
Université de Lille
Inserm
Université de Lille
Submission date :
2021-07-06T12:47:54Z
2024-01-26T13:31:40Z
2024-01-26T13:31:40Z