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      The Quit Benefits Model: a Markov model for assessing the health benefits and health care cost savings of quitting smoking

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      Cost Effectiveness and Resource Allocation
      BioMed Central

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          Abstract

          Background

          In response to the lack of comprehensive information about the health and economic benefits of quitting smoking for Australians, we developed the Quit Benefits Model (QBM).

          Methods

          The QBM is a Markov model, programmed in TreeAge, that assesses the consequences of quitting in terms of cases avoided of the four most common smoking-associated diseases, deaths avoided, and quality-adjusted life-years (QALYs) and health care costs saved (in Australian dollars, A$). Quitting outcomes can be assessed for males and females in 14 five year age-groups from 15–19 to 80–84 years.

          Exponential models, based on data from large case-control and cohort studies, were developed to estimate the decline over time after quitting in the risk of acute myocardial infarction (AMI), stroke, lung cancer, chronic obstructive pulmonary disease (COPD), and death. Australian data for the year 2001 were sourced for disease incidence and mortality and health care costs. Utility of life estimates were sourced from an international registry and a meta analysis.

          In this paper, outcomes are reported for simulated subjects followed up for ten years after quitting smoking. Life-years, QALYs and costs were estimated with 0%, 3% and 5% per annum discount rates. Summary results are presented for a group of 1,000 simulated quitters chosen at random from the Australian population of smokers aged between 15 and 74.

          Results

          For every 1,000 males chosen at random from the reference population who quit smoking, there is a an average saving in the first ten years following quitting of A$408,000 in health care costs associated with AMI, COPD, lung cancer and stroke, and a corresponding saving of A$328,000 for every 1,000 female quitters. The average saving per 1,000 random quitters is A$373,000. Overall 40 of these quitters will be spared a diagnosis of AMI, COPD, lung cancer and stroke in the first ten years following quitting, with an estimated saving of 47 life-years and 75 QALYs. Sensitivity analyses indicated that QBM predictions were robust to variations of ± 10% in parameter estimates.

          Conclusion

          The QBM can answer many of the questions posed by Australian policy-makers and health program funders about the benefits of quitting, and is a useful tool to evaluate tobacco control programs. It can easily be re-programmed with updated information or a set of epidemiologic data from another country.

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          Most cited references38

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          Smoking, smoking cessation, and lung cancer in the UK since 1950: combination of national statistics with two case-control studies.

          To relate UK national trends since 1950 in smoking, in smoking cessation, and in lung cancer to the contrasting results from two large case-control studies centred around 1950 and 1990. United Kingdom. Hospital patients under 75 years of age with and without lung cancer in 1950 and 1990, plus, in 1990, a matched sample of the local population: 1465 case-control pairs in the 1950 study, and 982 cases plus 3185 controls in the 1990 study. Smoking prevalence and lung cancer. For men in early middle age in the United Kingdom the prevalence of smoking halved between 1950 and 1990 but the death rate from lung cancer at ages 35-54 fell even more rapidly, indicating some reduction in the risk among continuing smokers. In contrast, women and older men who were still current smokers in 1990 were more likely than those in 1950 to have been persistent cigarette smokers throughout adult life and so had higher lung cancer rates than current smokers in 1950. The cumulative risk of death from lung cancer by age 75 (in the absence of other causes of death) rose from 6% at 1950 rates to 16% at 1990 rates in male cigarette smokers, and from 1% to 10% in female cigarette smokers. Among both men and women in 1990, however, the former smokers had only a fraction of the lung cancer rate of continuing smokers, and this fraction fell steeply with time since stopping. By 1990 cessation had almost halved the number of lung cancers that would have been expected if the former smokers had continued. For men who stopped at ages 60, 50, 40, and 30 the cumulative risks of lung cancer by age 75 were 10%, 6%, 3%, and 2%. People who stop smoking, even well into middle age, avoid most of their subsequent risk of lung cancer, and stopping before middle age avoids more than 90% of the risk attributable to tobacco. Mortality in the near future and throughout the first half of the 21st century could be substantially reduced by current smokers giving up the habit. In contrast, the extent to which young people henceforth become persistent smokers will affect mortality rates chiefly in the middle or second half of the 21st century.
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            A generic model for the assessment of disease epidemiology: the computational basis of DisMod II

            Epidemiology as an empirical science has developed sophisticated methods to measure the causes and patterns of disease in populations. Nevertheless, for many diseases in many countries only partial data are available. When the partial data are insufficient, but data collection is not an option, it is possible to supplement the data by exploiting the causal relations between the various variables that describe a disease process. We present a simple generic disease model with incidence, one prevalent state, and case fatality and remission. We derive a set of equations that describes this disease process and allows calculation of the complete epidemiology of a disease given a minimum of three input variables. We give the example of asthma with age-specific prevalence, remission, and mortality as inputs. Outputs are incidence and case fatality, among others. The set of equations is embedded in a software package called 'DisMod II', which is made available to the public domain by the World Health Organization.
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              Mortality from tobacco in developed countries: indirect estimation from national vital statistics.

              Prolonged cigarette smoking causes even more deaths from other diseases than from lung cancer. In developed countries, the absolute age-sex-specific lung cancer rates can be used to indicate the approximate proportions due to tobacco of deaths not only from lung cancer itself but also, indirectly, from vascular disease and from various other categories of disease. Even in the absence of direct information on smoking histories, therefore, national mortality from tobacco can be estimated approximately just from the disease mortality statistics that are available from all major developed countries for about 1985 (and for 1975 and so, by extrapolation, for 1995). The relation between the absolute excess of lung cancer and the proportional excess of other diseases can only be approximate, and so as not to overestimate the effects of tobacco it has been taken to be only half that suggested by a recent large prospective study of smoking and death among one million Americans. Application of such methods indicates that, in developed countries alone, annual deaths from smoking number about 0.9 million in 1965, 1.3 million in 1975, 1.7 million in 1985, and 2.1 million in 1995 (and hence about 21 million in the decade 1990-99: 5-6 million European Community, 5-6 million USA, 5 million former USSR, 3 million Eastern and other Europe, and 2 million elsewhere, [ie, Australia, Canada, Japan, and New Zealand]). More than half these deaths will be at 35-69 years of age: during the 1990s tobacco will in developed countries cause about 30% of all deaths at 35-69 (making it the largest single cause of premature death) plus about 14% of all at older ages. Those killed at older ages are on average already almost 80 years old, however, and might have died soon anyway, but those killed by tobacco at 35-69 lose an average of about 23 years of life. At present just under 20% of all deaths in developed countries are attributed to tobacco, but this percentage is still rising, suggesting that on current smoking patterns just over 20% of those now living in developed countries will eventually be killed by tobacco (ie, about a quarter of a billion, out of a current total population of just under one and a quarter billion).
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                Author and article information

                Journal
                Cost Eff Resour Alloc
                Cost Effectiveness and Resource Allocation
                BioMed Central (London )
                1478-7547
                2007
                23 January 2007
                : 5
                : 2
                Affiliations
                [1 ]Bainbridge Consultants, 532 Brunswick St, Fitzroy North, Victoria, 3068, Australia
                [2 ]School of Population Health, The University of Melbourne, Parkville, Victoria, 3052, Australia
                Article
                1478-7547-5-2
                10.1186/1478-7547-5-2
                1796848
                17241477
                b135cbdb-6010-4106-83b5-2d8695571646
                Copyright © 2007 Hurley and Matthews; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 August 2006
                : 23 January 2007
                Categories
                Methodology

                Public health
                Public health

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