| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
Erasmus Medical Center, Institute for Medical Technology Assessment, Rotterdam, The Netherlands; and Hines Veterans Affairs Hospital and Northwestern University, Chicago, Illinois
Correspondence and requests for reprints should be addressed to Dr. Maureen Rutten-van Mölken, Institute for Medical Technology Assessment, Erasmus MC, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands. E-mail: m.rutten-vanmolken{at}erasmusmc.nl
ABSTRACT
Calculating the cost-effectiveness of interventions is an important step in accurately assessing the health and financial burdens of a disease. Although clinical trials that include cost data can be used to compare the cost-effectiveness of specific interventions, they only deal with outcomes within the time frame of the trial. Health economic models can synthesize epidemiologic, clinical, economic, and quality-of-life data from many different sources and extrapolate results to a point many years in the future. The models generally compare interventions with respect to the costs per life-year gained or per quality-adjusted life-year gained. The use of health economic models to assess the economic burden of chronic obstructive pulmonary disease (COPD) and the value of interventions is growing, and will continue to do so as the burden of the disease is better appreciated. Several COPD disease-state models have been described; each uses a consistent definition of COPD severity that is based on FEV1% predicted, but the models differ in the allowed transitions, disease progression estimates, utility weights, and costs. This article reviews COPD health economic models and discusses the importance of survival benefits and utilities (health state valuations) for COPD in economic models.
Key Words: chronic obstructive pulmonary disease • health economic model • cost-effectiveness
Chronic obstructive pulmonary disease (COPD) is a major cause of chronic morbidity and mortality. Its high prevalence and related mortality are increasing at a time when death from cardiovascular events is decreasing, giving a clear signal that improved intervention strategies through early diagnosis and treatment are required to reduce the economic and social costs of this disease. Data from the United States and Europe offer insights into the enormous economic and social burden of COPD for societies and insurance payers. When considering the economics of COPD, the arguments must stretch beyond simply the efficacy, safety, and cost of an intervention to include broader aspects of improved health, such as survival and impact on quality of life, within a standardized framework. In general, economic evaluations, or cost-effectiveness analyses, are employed because they allow valued judgments on the efficiency of treatments within the context of survival and quality of life. Parameters such as cost per life-year gained (LYG) and per quality-adjusted life year (QALY) combine costs with measures of quality of life and survival time to help policy makers determine priorities and strategies for health care. This framework allows comparison of the value of healthcare interventions both within and across different diseases and an assessment of the impact of investment now on future expenditure and health outcomes. Thus, understanding the health economics of interventions for COPD will be an important component in caring for patients with COPD.
A clearer quantitative economic assessment of COPD and its interventions is required to more effectively inform health care decision making. Although clinical trial data are frequently used to compare the cost-effectiveness of specific interventions, they have limitations. These include the choice of outcome and when the outcome is measured. Frequently, surrogate endpoints (e.g., lung function) are measured as opposed to measuring final outcomes, such as quality of life and death. The endpoints are usually recorded at a discreet time point, and don't go beyond the end of the trial, so no ongoing effect over a subject's lifetime is measured. Survival data often tend to relate only to the follow-up period of the trial, and are not usually extended long-term, which offers insufficient information to accurately estimate any potential gain in life expectancy. Given these limitations, increasingly more sophisticated approaches to economic assessment, which incorporate disease modeling, are employed to provide survival and cost per LYG estimates beyond the clinical trial and to explore uncertainties and drivers of cost-effectiveness.
In an economic assessment of a chronic disease such as COPD, decision analytical modeling, such as Markov modeling, is now the favored approach. In a Markov model, the progress of a notional group of patients through a finite number of health states is modeled over time, with patients initially placed in one health state; the probability of transition to another state in the model is defined within a given time period, known as a Markov cycle. Models are created through incorporation of clinical data, especially from epidemiologic and population databases that map the natural history of the disease in terms of survival, allowing extrapolation to a point in the future for cost-effectiveness assessment. A limitation of Markov modeling is that previous disease events experienced by a patient do not influence the probability of a transition from one state to another (known as the Markovian assumption) (1).
In this review, we offer a brief overview of published Markov models developed to assess the cost-effectiveness of COPD interventions, highlighting some of the differences between these models and reviewing ongoing research to improve utility estimates for COPD severity stages and exacerbation status. Utility is a measure of the preference for or desirability of a specific level of health status or specific health outcome, and is used to weigh improvements in life expectancy according to the quality of life experienced within the calculation of QALYs.
CURRENT COPD-RELATED ECONOMIC MODELS
Five COPD progression models, all of which are Markov models (2–6), and which have evaluated different interventions (summarized in Table 1) are described below. The most recent model published, developed by the Institute for Medical Technology Assessment in Rotterdam and the National Institute of Public Health and the Environment in Bilthoren, NL (6), is a uniquely dynamic population model. A model in development as part of the Burden of Obstructive Lung Disease (BOLD) initiative is also described (7).
|
A different model (3), based on the Global Initiative for Chronic Lung Disease (GOLD) recommendations, was unique in that it included separate Markov chains for COPD severity and for COPD-related exacerbations. In the exacerbation component of the model, patients could be exacerbation free or have mild, moderate, or severe exacerbations. The type of exacerbation influenced the probability of moving to either milder or worse disease, and of death. Patients can improve to the next milder COPD state, after which disease progression continues. The model used data from a variety of sources on disease progression, expected exacerbation frequency/duration, mortality, costs, burden of illness, and the relationships between variables. The cost-effectiveness of two hypothetical interventions, one that would halve lung function decline, and one that reduced exacerbations by 25%, was calculated. The findings were important, as they showed that an intervention that slows disease progression as assessed by lung function decline only becomes cost-effective after many years (about 30 years) when compared with an intervention that reduces exacerbation rates.
In 2005, a further Markov model (4) was described using the same four mutually exclusive disease states (mild, moderate, and severe disease, and death) as those of a previous study (2) to model costs, exacerbations, survival, QALYs, and cost effectiveness (Figure 1). Spencer and colleagues compared a long-acting ß2-agonist/inhaled corticosteroid combination (salmeterol/fluticasone propionate) to usual care over a 25-yr time horizon (4). The transition probabilities of disease progression (for smokers and ex-smokers), death, and the exacerbation probabilities were taken from the published medical literature. Efficacy data for the combination therapy were obtained from the TRISTAN (Trial of Inhaled Steroids and Long-Acting ß-Agonists) study (8) that involved patients with a documented history of frequent COPD exacerbations. The model demonstrated that, when combination therapy impacted exacerbation rates only, the cost per QALY was Can $74,887 (95% confidence interval = 21,985–128,671), but if the therapy impacted mortality, the survival effect resulted in a huge reduction; the incremental cost per QALY was Can $11,125 (95% confidence interval = 8,710, dominated) compared with usual care. Sensitivity analyses showed that the cost per QALY was insensitive to the size of the mortality benefit, which supports the importance of this endpoint in determining the cost-effectiveness.
|
10 per exacerbation avoided in Canada and above 0 per exacerbation avoided in The Netherlands. In The Netherlands, the ceiling ratios for cost-effectiveness were better because of the higher treatment costs and increased length of hospital stay in case of an exacerbation compared with Canada. A DYNAMIC, POPULATION-BASED MODEL
Recently, a Dutch model (6) was used to determine the future burden of COPD in The Netherlands and to assess two smoking cessation interventions. The model is both population-based and dynamic (Figure 2). It starts from the age-, sex-, and smoking-class distribution in the entire Dutch population and models the incidence of COPD depending on this distribution. The model follows patients with COPD over their course of disease, distinguishing four COPD severity stages according to GOLD, and never, current, and former smokers. Progression of COPD is defined as the annual decline in FEV1% predicted, and depends on age, sex, smoking, and FEV1% predicted. Estimates of progression were based on data from the Lung Health Study (9). Changes in demography and smoking influence the incidence, prevalence, progression, mortality, and costs of COPD. As a result, the model can estimate the impact of intervening at any stage in the course of COPD, from primary prevention to end-stage COPD. This cannot be done with the COPD models described previously because they all follow a cohort of patients with COPD over time, mostly until they have all reached the death state. New cases of COPD do not enter these models. Hence, they are not able to estimate how COPD epidemiology and costs change at a country level. Over the 25-yr time frame, the model predicted an increase of 6, 3, 0.9, and 0.8 patients with mild, moderate, severe, and very severe COPD, respectively, per 1,000 inhabitants. When costs per patient were kept constant, Dutch COPD-related healthcare expenditures were predicted to increase from 280 million in 2000 to 495 million in 2025.
|
14,000 per QALY. This Dutch COPD model is part of a large dynamic multistate life table model, the Chronic Disease Model, developed by the National Institute for Public Health and the Environment, which models the prevalence, incidence, and mortality of a large number of different diseases in the Dutch population (10, 11). Because of this, the COPD model accounts for competing death risks. A disadvantage of the model is that it does not include COPD exacerbations.
AN ECONOMIC MODEL BASED ON THE BOLD INITIATIVE
The objective of the BOLD economic model, as part of the BOLD initiative (7), is to develop a health policy tool that can be used to calculate site-specific estimates of the current and future economic impact of COPD. It is an interactive, web-based model using information from the BOLD prevalence survey, local cost and population estimates, and disease progression estimates from the Framingham Heart Study. At present, 11 countries (China, Turkey, Austria, Poland, South Africa, Iceland, Norway, Germany, The United States, Canada, and The Philippines) have completed the prevalence portion of the BOLD project or are in the process of completing the prevalence survey. In addition, BOLD is associated with a similar project, PLATINO (Latin American Project for the Investigation of Obstructive Lung Disease), which was conducted in countries in Central and South America (12, 13).
The structure of the BOLD model is similar to that of the COPD models described here, and includes 10 health states (Figure 3). The model does not allow transitions to less severe GOLD stages in patients with COPD. Both cohort and offspring data from the Framingham Heart Study are used to follow patients with COPD over a nearly 20-yr period to determine the rates of disease progression in males and females by smoking status.
|
The results suggest that ICS treatment is a cost-effective alternative in patients with stages II and III COPD. In the first scenario, cost-effectiveness per LYG was $29,064 at 5 yr and $13,043 at 20 yr. In the second scenario, these figures were $27,321 and $12,758, respectively. When ICS reduced the risk of mortality and the rate of exacerbations, as in the third scenario, the results were $1,581 per LYG at 5 yr and ICS was dominant (cheaper and more effective) at 20 yr. Some limitations of the analysis include a lack of quality-of-life data in the simulations, only a deterministic analysis was performed, and an inability to populate the model with estimates for each of the subpopulations modeled.
UTILITY AND LIFE EXPECTANCY IN ESTIMATING QALYS IN COPD ECONOMIC MODELS
With new treatment approaches suggesting opportunities to improve COPD management, one of the challenges that remains is improving COPD economic models to provide better QALY estimates. Currently, the COPD models lack good data on both the quality (defined by utility) and quantity (life expectancy) elements of QALYs. A limitation of current models lies in the accuracy of the projections of the impact of COPD interventions on life expectancy. Improved modeling of life expectancy will be particularly important when assessing new life-saving interventions. In addition, more sensitivity analyses around this parameter and validation of estimates against epidemiology evidence is required. However, at present, utility is the main driver in the calculation of QALYs in COPD economic models because interventions generally do not affect survival.
Despite the importance of utility estimates for these models, robust estimates according to the severity of COPD remain undefined. In particular, reliable estimates for utility scores for exacerbations, which are especially important when assessing the effect of an intervention, are not available. This reflects the fact that, in clinical trials of COPD, assessments of disease status are usually made at scheduled clinic visits and, therefore, do not accurately capture the precise impact of exacerbations. Furthermore, the instruments that are currently employed to calculate utility (e.g., EQ-5D) are largely too insensitive.
The lack of accepted utility values is reflected in the COPD models currently described. In the models, utility score for severity stages and exacerbation status vary. Three of the models (3, 5, 6) used an identical utility score for severity stages, but with respect to exacerbations, utility weights differed across the models with either a unique weight given for exacerbations, or a disutility factor associated with an exacerbation. The disutility value (the negative impact on quality of life associated with the exacerbation) was either a constant (2) or a function of the baseline utility weight for the patients (3, 5). Thus, a key area of ongoing research remains defining the extent and length of utility decrement during the disease course of COPD.
CONCLUSIONS
The number of COPD health economic models is growing. Comparing the five current models, all are Markov models that are generally similar with regard to the health states included. Disease progression, defined as decline in lung function, is the predominant movement through health states, although several models allow movement to less severe health states. Importantly, disease progression estimates used in each of the models are derived from various sources, with different populations and estimates of progression, which may subsequently impact the estimates of future costs associated with the disease. In addition, the model structures differ with respect to many elements, including the ability to model COPD incidence, the impact of smoking on disease progression, and the impact of exacerbation rates on disease progression.
Ongoing research efforts in COPD economic models are directed toward constructing a model that is widely accepted and allows comparison of cost-effectiveness between treatments. The best available process to obtain crucial model parameters, such as disease progression and the impact of smoking, must be identified to provide some consensus on model structure and datasets. Because COPD is a systemic, multicomponent disease, future economic models will require incorporation of disease progression dependent upon more than just lung function. Value-of-information analysis of existing models, which involves estimating the value of collecting additional information on one or more crucial drivers of the cost-effectiveness in order to reduce or eliminate uncertainty, will also allow prioritization of future COPD research. Key priorities in future model development include better utility information and better definition of outcome measures. Questions that require better answers include: are exacerbations a good outcome measure in long-term analyses? Because interventions that increase survival will also accumulate more exacerbations, potentially offsetting reductions in the annual rate of exacerbation that the treatment may produce, are exacerbation-free months a relevant outcome parameter? In addition, when transition probabilities between COPD severity stages differ (even if only during the first year) and mortality rates depend on severity stage, can an effect on survival be modeled without any robust clinical evidence of a survival effect? Finally, should costs other than those that are COPD-related during the extended life be included, because QALYs are included?
Through the BOLD initiative, the availability of site-specific epidemiologic and cost data will allow evaluation of the cost-effectiveness for COPD interventions in a number of country-specific settings. Ultimately, global epidemiologic and economic studies will allow for more uniform guidelines for the prevention and cost-effective treatment of patients with COPD (15).
FOOTNOTES
Conflict of Interest Statement: M.R.v.M. has received two research grants for modeling cost-effectiveness of COPD interventions from Boehringer Ingelheim. She has received a speakers fee from GlaxoSmithKline (UK £1,500) for presenting the current review during a COPD meeting in Rome on November 3 and 4, 2005. During 2005, the Institute for Medical Technology Assessment had a consultancy agreement with Boehringer Ingelheim and Altana Pharma (both for 50,000). T.A.L. participated as a speaker in the COPD meeting mentioned above, which was sponsored by GlaxoSmithKline, and received a US $116,646 grant for the BOLD project in 2005, which was sponsored by a consortium of pharmaceutical manufacturers.
(Received in original form March 27, 2006; accepted in final form April 18, 2006)
REFERENCES
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
