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A Comparison of Markov and Discrete-Time Microsimulation Approaches: Simulating the Avoidance of Alcohol-Attributable Harmful Events from Reduction of Alcohol Consumption Through Treatment of Alcohol Dependence

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Abstract

Background and Objective

When modelling the pathophysiology of a disease, it is important to select a modelling approach that can adequately replicate its course. The objective of this paper was to compare the outcomes obtained by the Markov and discrete-time microsimulation modelling approaches using nalmefene clinical trial data.

Methods

Markov and microsimulation modelling approaches assessing alcohol dependence treatment with psychosocial support with or without nalmefene were compared in terms of the modelled evolution of patients’ alcohol consumption and the resulting occurrence of alcohol-attributable harmful events over 1 year.

Results

Comparison of the proportion of the modelled population at different levels of alcohol consumption over time revealed systematic differences arising from the different modelling techniques: a lower number of patients reaching abstinence, a higher number of patients at higher drinking levels, and, overall, a smoother evolution of alcohol consumption in the microsimulation. Reasons are discussed in the paper. While the models produced similar occurrences of alcohol-attributable harmful events as a whole, distinct results for the individual events were observed, explained by the specific pathophysiology of occurrence of these events and how their implementation was adapted to fit the limitations of the compared modelling approaches; however, these differences were only statistically significant for one of the eight events.

Conclusions

For a general public health or health economic assessment of alcohol use disorders, it is possible to achieve similar results with the compared approaches. To assess a patients’ disease course, taking into consideration alcohol-attributable harmful events, the microsimulation approach may provide more precise results. However, further external validation of the models is needed and this additional precision may be outweighed by the greater computational burden of a microsimulation approach.

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Acknowledgments

Editorial and medical writing support was provided by Saoirse Leonard from Costello Medical Consulting Ltd, Cambridge, UK. This support was funded by Lundbeck SAS.

Author Contributions

All authors were involved in the conception and design of all or some component(s) of the research. Acquisition of data was carried out by Philippe Laramée, Aurélie Millier, Nora Rahhali, Olivier Cristeau, Samuel Aballéa, Thor-Henrik Brodtkorb and Jürgen Rehm. Modelling and statistical analysis was performed by Philippe Laramée, Aurélie Millier, Nora Rahhali, Olivier Cristeau, Samuel Aballéa, Thor-Henrik Brodtkorb and Jürgen Rehm. All authors participated at all or some step(s) of the review, analysis and interpretation of the outcomes. Philippe Laramée was responsible for development of the manuscript. All authors reviewed and commented on the draft manuscript, reviewed its intellectual content, and approved the final version. Philippe Laramée will act as the overall guarantor.

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Authors and Affiliations

  1. Social and Epidemiological Research Department, Centre for Addiction and Mental Health, Toronto, ON, M5S 2S1, Canada

    Philippe Laramée & Jürgen Rehm

  2. Health Economics and Outcomes Research, Creativ-Ceutical, 75008, Paris, France

    Aurélie Millier, Olivier Cristeau & Samuel Aballéa

  3. Health Economics, RTI Health Solutions, 45930, Ljungskile, Sweden

    Thor-Henrik Brodtkorb

  4. Global Analytics, Lundbeck SAS, 92445, Issy-les-Moulineaux CEDEX, France

    Nora Rahhali

  5. Costello Medical Consulting Ltd, Cambridge, CB2 1RE, UK

    Stephen Montgomery & Sara Steeves

  6. Laboratoire de Santé Publique, Faculté de Médecine, Université de la Méditerranée, 13385, Marseille, France

    Mondher Toumi

  7. Dalla Lana School of Public Health, University of Toronto, Toronto, ON, M5T 3M7, Canada

    Jürgen Rehm

  8. Klinische Psychologie und Psychotherapie, TU Dresden, 01187, Dresden, Germany

    Jürgen Rehm

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  1. Philippe Laramée
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  2. Aurélie Millier
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  8. Sara Steeves
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  10. Jürgen Rehm
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Corresponding author

Correspondence to Philippe Laramée.

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Conflict of interest

Philippe Laramée was an employee of Lundbeck SAS at the time the main body of this work was undertaken and Nora Rahhali is an employee of Lundbeck SAS, who funded this work. Aurélie Millier, Olivier Cristeau and Samuel Aballéa are employees of Creativ-Ceutical, who were contracted by Lundbeck SAS to undertake some of the work described in this manuscript. Thor-Henrik Brodtkorb is an employee of RTI Health Solutions, who were contracted by Lundbeck SAS to undertake some of the work described in this manuscript. Stephen Montgomery and Sara Steeves are employees of Costello Medical Consulting Ltd, who were contracted by Lundbeck SAS to undertake some of the work described in this manuscript. Jürgen Rehm has received grants, consulting fees/honoraria, travel support and payment for lectures from Lundbeck, outside the work presented in this manuscript. Mondher Toumi declares no conflicts of interest.

Funding

This work was funded by Lundbeck SAS. The views presented in this paper are those of the authors and do not necessarily reflect those of the study funders.

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Laramée, P., Millier, A., Brodtkorb, TH. et al. A Comparison of Markov and Discrete-Time Microsimulation Approaches: Simulating the Avoidance of Alcohol-Attributable Harmful Events from Reduction of Alcohol Consumption Through Treatment of Alcohol Dependence. Clin Drug Investig 36, 945–956 (2016). https://doi.org/10.1007/s40261-016-0442-7

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  • DOI: https://doi.org/10.1007/s40261-016-0442-7

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