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Cost-Effectiveness Analysis of Genotype-Guided Treatment Allocation in Patients with Alcohol Use Disorders Using Naltrexone or Acamprosate, Using a Modeling Approach.

ABSTRACT: Alcohol use disorders (AUD) are a major contributor to the global burden of disease, and have huge societal impact. Some studies show that AUD patients carrying the G-allele of the OPRM1 variant c.118A>G respond better to naltrexone, resulting in reduced relapse rates compared to carriers of the AA genotype. Genotype-guided treatment allocation of these patients carrying a G-allele to naltrexone could potentially improve the treatment outcome. However, cost-effectiveness of this strategy should be investigated before considering clinical implementation. We, therefore, evaluated costs and Quality-Adjusted Life-Years (QALYs), using a modelling approach, from an European perspective, of genotype-guided treatment allocation (G-allele carriers receiving naltrexone; AA homozygotes acamprosate or naltrexone) compared to standard care (random treatment allocation to acamprosate or naltrexone), by using a Markov model. Genotype-guided treatment allocation resulted in incremental costs of EUR 66 (95% CI -28 to 149) and incremental effects of 0.005 QALYs (95% CI 0.000-0.011) per patient (incremental cost-effectiveness ratio of EUR 13,350 per QALY). Sensitivity analyses showed that the risk ratio to relapse after treatment allocation had the largest impact on the cost-effectiveness. Depending on the willingness to pay for a gain of one QALY, probabilities that the intervention is cost-effective varies between 6 and 79%. In conclusion, pharmacogenetic treatment allocation of AUD patients to naltrexone, based on OPRM1 genotype, can be a cost-effective strategy, and could have potential individual and societal benefits. However, more evidence on the impact of genotype-guided treatment allocation on relapse is needed to substantiate these conclusions, as there is contradictory evidence about the effectiveness of OPRM1 genotyping.

SUBMITTER: Sluiter RL

PROVIDER: S-EPMC6492516 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Cost-Effectiveness Analysis of Genotype-Guided Treatment Allocation in Patients with Alcohol Use Disorders Using Naltrexone or Acamprosate, Using a Modeling Approach.

Sluiter Reinier L RL Kievit Wietske W van der Wilt Gert Jan GJ Schene Aart H AH Teichert Martina M Coenen Marieke J H MJH Schellekens Arnt A

European addiction research 20181101 5

Alcohol use disorders (AUD) are a major contributor to the global burden of disease, and have huge societal impact. Some studies show that AUD patients carrying the G-allele of the OPRM1 variant c.118A>G respond better to naltrexone, resulting in reduced relapse rates compared to carriers of the AA genotype. Genotype-guided treatment allocation of these patients carrying a G-allele to naltrexone could potentially improve the treatment outcome. However, cost-effectiveness of this strategy should ...[more]

PMID: 30384381

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Project description:BackgroundThe placebo effect often undermines efforts to determine treatment effectiveness in clinical trials. A significant placebo response occurs in alcohol trials, but it is not well understood. The purpose of this study was to characterize the placebo response across multiple naltrexone and acamprosate studies.MethodsFifty-one trials, 3 with a naltrexone and an acamprosate arm, 31 with at least 1 naltrexone arm, and 17 with at least 1 acamprosate arm, were identified from Cochrane reviews and PubMed search. To be included in this study, patients had to be at least 18 years old, abstinent from alcohol before randomization, and meet a diagnosis of alcohol dependence. Pearson correlation coefficients (rp ) and simple linear regression were used to describe the strength of linear relationships between placebo response and treatment effect size. Spearman's rank correlation coefficients (rs ) were used to examine the strength of associations between study characteristics and placebo response.ResultsFor the end point measures of percent days abstinent and total abstinence, a negative relationship was evident between placebo response and treatment effect size in the naltrexone trials (rp = -0.55, p < 0.01 and rp = -0.20, p = 0.35, respectively) as well as in the acamprosate trials (rp = -0.45, p = 0.09 and rp = -0.56, p = 0.01, respectively). The placebo response for percent days abstinent was negatively correlated with mean age of participants (rs = -0.42, p = 0.05) across naltrexone trials and positively correlated with publication year (rs = 0.57, p = 0.03) across acamprosate trials. However, these 2 study characteristics were not significantly correlated with treatment effect size.ConclusionsThe placebo response varied considerably across trials and was negatively correlated with the treatment effect size. Additional studies are required to fully understand the complex nature of the placebo response and to evaluate approaches to minimize its effects.

Dataset Information

Cost-Effectiveness Analysis of Genotype-Guided Treatment Allocation in Patients with Alcohol Use Disorders Using Naltrexone or Acamprosate, Using a Modeling Approach.

Publications

Cost-Effectiveness Analysis of Genotype-Guided Treatment Allocation in Patients with Alcohol Use Disorders Using Naltrexone or Acamprosate, Using a Modeling Approach.

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