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A computer simulation model of the natural history and economic impact of chronic obstructive pulmonary disease

Borg, Sixten LU ; Ericsson, Asa; Wedzicha, Jadwiga; Gulsvik, Amund; Lundbäck, Bo; Donaldson, Gavin C and Sullivan, Sean D (2004) In Value in Health 7(2). p.67-153
Abstract

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a major health problem with high societal costs. The Global Initiative for Chronic Lung Disease (GOLD) has identified a need for health economics data for COPD. For chronic diseases, such as COPD, where the natural history of disease is lifetime, a modeling approach for economic evaluation may be more realistic than prospective, piggy-backed clinical trials or specific COPD cohort studies. Simulation models can be used to extrapolate clinical data beyond the limited time frame of clinical trials, to analyze subgroups of patients or to explore uncertainty regarding the results by using sensitivity analysis techniques. Our purpose has been to develop a flexible computer simulation... (More)

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a major health problem with high societal costs. The Global Initiative for Chronic Lung Disease (GOLD) has identified a need for health economics data for COPD. For chronic diseases, such as COPD, where the natural history of disease is lifetime, a modeling approach for economic evaluation may be more realistic than prospective, piggy-backed clinical trials or specific COPD cohort studies. Simulation models can be used to extrapolate clinical data beyond the limited time frame of clinical trials, to analyze subgroups of patients or to explore uncertainty regarding the results by using sensitivity analysis techniques. Our purpose has been to develop a flexible computer simulation model for COPD that will represent disease progression and GOLD recommendations, useful for economic evaluations of new medicines to meet the needs of various payer requirements for reimbursement and resource allocation.

METHODS: This article describes a two-dimensional Markov model, which uses data from multiple sources about disease progression, exacerbation frequency and duration, mortality, costs, burden of illness, and the relationships between those variables. The model is evaluated using stochastic uncertainty analysis, it allows comparison of treatments affecting different disease mechanisms, and it uses primary data validated against published sources.

RESULTS: We have evaluated two hypothetical interventions treating different features of the disease (lung function decline and acute exacerbations). These analyses show that reducing lung function decline must be a long-term strategy compared to reducing the number of exacerbations. It was necessary to have a long term like 30 years, with 10,000 patients and 20% increase in price, or 20 years with equal prices to show cost-effectiveness with statistical significance for a treatment that reduces lung function decline.

CONCLUSIONS: Our study shows the value of modeling as a tool for evaluating different scenarios and for combining several sources of data, to provide estimates that would otherwise be unavailable. Clinical trials of this size and duration would be unrealistic.

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author
publishing date
type
Contribution to journal
publication status
published
keywords
Computer Simulation, Cost of Illness, Disease Progression, Global Health, Health Care Costs, Health Services Research, Humans, Lung, Markov Chains, Practice Guidelines as Topic, Pulmonary Disease, Chronic Obstructive, Quality-Adjusted Life Years, Severity of Illness Index, Uncertainty, United States, Journal Article, Research Support, Non-U.S. Gov't
in
Value in Health
volume
7
issue
2
pages
67 - 153
publisher
Wiley-Blackwell
external identifiers
  • scopus:1842457093
ISSN
1098-3015
DOI
10.1111/j.1524-4733.2004.72318.x
language
English
LU publication?
no
id
c760835b-a36e-48f5-a1ee-81b8543e4e45
date added to LUP
2018-03-08 07:37:37
date last changed
2018-11-21 21:38:31
@article{c760835b-a36e-48f5-a1ee-81b8543e4e45,
  abstract     = {<p>OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a major health problem with high societal costs. The Global Initiative for Chronic Lung Disease (GOLD) has identified a need for health economics data for COPD. For chronic diseases, such as COPD, where the natural history of disease is lifetime, a modeling approach for economic evaluation may be more realistic than prospective, piggy-backed clinical trials or specific COPD cohort studies. Simulation models can be used to extrapolate clinical data beyond the limited time frame of clinical trials, to analyze subgroups of patients or to explore uncertainty regarding the results by using sensitivity analysis techniques. Our purpose has been to develop a flexible computer simulation model for COPD that will represent disease progression and GOLD recommendations, useful for economic evaluations of new medicines to meet the needs of various payer requirements for reimbursement and resource allocation.</p><p>METHODS: This article describes a two-dimensional Markov model, which uses data from multiple sources about disease progression, exacerbation frequency and duration, mortality, costs, burden of illness, and the relationships between those variables. The model is evaluated using stochastic uncertainty analysis, it allows comparison of treatments affecting different disease mechanisms, and it uses primary data validated against published sources.</p><p>RESULTS: We have evaluated two hypothetical interventions treating different features of the disease (lung function decline and acute exacerbations). These analyses show that reducing lung function decline must be a long-term strategy compared to reducing the number of exacerbations. It was necessary to have a long term like 30 years, with 10,000 patients and 20% increase in price, or 20 years with equal prices to show cost-effectiveness with statistical significance for a treatment that reduces lung function decline.</p><p>CONCLUSIONS: Our study shows the value of modeling as a tool for evaluating different scenarios and for combining several sources of data, to provide estimates that would otherwise be unavailable. Clinical trials of this size and duration would be unrealistic.</p>},
  author       = {Borg, Sixten and Ericsson, Asa and Wedzicha, Jadwiga and Gulsvik, Amund and Lundbäck, Bo and Donaldson, Gavin C and Sullivan, Sean D},
  issn         = {1098-3015},
  keyword      = {Computer Simulation,Cost of Illness,Disease Progression,Global Health,Health Care Costs,Health Services Research,Humans,Lung,Markov Chains,Practice Guidelines as Topic,Pulmonary Disease, Chronic Obstructive,Quality-Adjusted Life Years,Severity of Illness Index,Uncertainty,United States,Journal Article,Research Support, Non-U.S. Gov't},
  language     = {eng},
  number       = {2},
  pages        = {67--153},
  publisher    = {Wiley-Blackwell},
  series       = {Value in Health},
  title        = {A computer simulation model of the natural history and economic impact of chronic obstructive pulmonary disease},
  url          = {http://dx.doi.org/10.1111/j.1524-4733.2004.72318.x},
  volume       = {7},
  year         = {2004},
}