Philippe Laramée1, Aurélie Millier2, Nora Rahhali3, Olivier Cristeau2, Samuel Aballéa2, Clément François4, Ylana Chalem4, Mondher Toumi5, Jürgen Rehm6,7,8. 1. Social and Epidemiological Research Department, Centre for Addiction and Mental Health, Toronto, M5S 2S1, Canada. plaramee@outlook.com. 2. Health Economics and Outcomes Research, Creativ-Ceutical, 75008, Paris, France. 3. Global Analytics, Lundbeck SAS, 92445, Issy-les-Moulineaux Cedex, France. 4. Global Outcomes Research, Lundbeck SAS, 92445, Issy-les-Moulineaux Cedex, France. 5. Laboratoire de Santé Publique, Faculté de Médecine, Université de la Méditerranée, 13385, Marseille, France. 6. Social and Epidemiological Research Department, Centre for Addiction and Mental Health, Toronto, M5S 2S1, Canada. 7. Dalla Lana School of Public Health, University of Toronto, Toronto, M5T 3M7, Canada. 8. Klinische Psychologie und Psychotherapie, TU Dresden, 01187, Dresden, Germany.
Abstract
BACKGROUND: Alcohol dependence causes considerable harm to patients. Treatment with nalmefene, aiming to reduce consumption rather than maintain complete abstinence, has been licensed based on trials demonstrating a reduction in total alcohol consumption and heavy drinking days. Relating these trial outcomes to harmful events avoided is important to demonstrate the clinical relevance of nalmefene treatment. METHODS: A predictive microsimulation model was developed to compare nalmefene plus brief psychosocial intervention (BRENDA) versus placebo plus BRENDA for the treatment of patients with alcohol dependence and a high or very high drinking risk level based on three pooled clinical trials. The model simulated patterns and level of alcohol consumption, day-by-day, for 12 months, to estimate the occurrence of alcohol-attributable diseases, injuries and deaths; assessing the clinical relevance of reducing alcohol consumption with treatment. RESULTS: The microsimulation model predicted that, in a cohort of 100,000 patients, 971 (95 % confidence interval [CI] 904-1038) alcohol-attributable diseases and injuries and 133 (95 % CI 117-150) deaths would be avoided with nalmefene versus placebo. This level of benefit has been considered clinically relevant by the European Medicines Agency. CONCLUSIONS: This microsimulation model supports the clinical relevance of the reduction in alcohol consumption, and has estimated the extent of the public health benefit of treatment with nalmefene in patients with alcohol dependence and a high or very high drinking risk level.
BACKGROUND:Alcohol dependence causes considerable harm to patients. Treatment with nalmefene, aiming to reduce consumption rather than maintain complete abstinence, has been licensed based on trials demonstrating a reduction in total alcohol consumption and heavy drinking days. Relating these trial outcomes to harmful events avoided is important to demonstrate the clinical relevance of nalmefene treatment. METHODS: A predictive microsimulation model was developed to compare nalmefene plus brief psychosocial intervention (BRENDA) versus placebo plus BRENDA for the treatment of patients with alcohol dependence and a high or very high drinking risk level based on three pooled clinical trials. The model simulated patterns and level of alcohol consumption, day-by-day, for 12 months, to estimate the occurrence of alcohol-attributable diseases, injuries and deaths; assessing the clinical relevance of reducing alcohol consumption with treatment. RESULTS: The microsimulation model predicted that, in a cohort of 100,000 patients, 971 (95 % confidence interval [CI] 904-1038) alcohol-attributable diseases and injuries and 133 (95 % CI 117-150) deaths would be avoided with nalmefene versus placebo. This level of benefit has been considered clinically relevant by the European Medicines Agency. CONCLUSIONS: This microsimulation model supports the clinical relevance of the reduction in alcohol consumption, and has estimated the extent of the public health benefit of treatment with nalmefene in patients with alcohol dependence and a high or very high drinking risk level.
Authors: Katie Witkiewitz; Henry R Kranzler; Kevin A Hallgren; Stephanie S O'Malley; Daniel E Falk; Raye Z Litten; Deborah S Hasin; Karl F Mann; Raymond F Anton Journal: Alcohol Clin Exp Res Date: 2018-11-05 Impact factor: 3.455
Authors: Philippe Laramée; Aurélie Millier; Thor-Henrik Brodtkorb; Nora Rahhali; Olivier Cristeau; Samuel Aballéa; Stephen Montgomery; Sara Steeves; Mondher Toumi; Jürgen Rehm Journal: Clin Drug Investig Date: 2016-11 Impact factor: 2.859