Cost-effectiveness of smoking cessation to prevent age-related macular degeneration.

BACKGROUND: Tobacco smoking is a risk factor for age-related macular degeneration, but studies of ex-smokers suggest quitting can reduce the risk. METHODS: We fitted a function predicting the decline in risk of macular degeneration after quitting to data from 7 studies involving 1,488 patients. We assessed the cost-effectiveness of smoking cessation in terms of its impact on macular degeneration-related outcomes for 1,000 randomly selected U.S. smokers. We used a computer simulation model to predict the incidence of macular degeneration and blindness, the number of quality-adjusted life-years (QALYs), and direct costs (in 2004 U.S. dollars) until age 85 years. Cost-effectiveness ratios were based on the cost of the Massachusetts Tobacco Control Program. Costs and QALYs were discounted at 3% per year. RESULTS: If 1,000 smokers quit, our model predicted 48 fewer cases of macular degeneration, 12 fewer cases of blindness, and a gain of 1,600 QALYs. Macular degeneration-related costs would decrease by $2.5 million if the costs of caregivers for people with vision loss were included, or by $1.1 million if caregiver costs were excluded. At a cost of $1,400 per quitter, smoking cessation was cost-saving when caregiver costs were included, and cost about $200 per QALY gained when caregiver costs were excluded. Sensitivity analyses had a negligible impact. The cost per quitter would have to exceed $77,000 for the cost per QALY for smoking cessation to reach $50,000, a threshold above which interventions are sometimes viewed as not cost-effective. CONCLUSION: Smoking cessation is unequivocally cost-effective in terms of its impact on age-related macular degeneration outcomes alone.

Cost-effectiveness of ranibizumab for neovascular age-related macular degeneration.

BACKGROUND: Intravitreal ranibizumab prevents vision loss and improves visual acuity in patients with neovascular age-related macular degeneration, but it is expensive, and efficacy beyond 2 years is uncertain. METHODS: We assessed the cost-effectiveness of ranibizumab compared with no ranibizumab over 10 years, using randomized trial efficacy data for the first 2 years, post-trial efficacy assumptions, and ranibizumab acquisition costs ranging from the wholesale price ($1,950 per dose) to the price of bevazicumab ($50), a similar molecule which may be equally efficacious. We used a computer simulation model to estimate the probability of blindness, the number of quality-adjusted life-years (QALYs), direct costs (in 2004 U.S. dollars), and cost-effectiveness ratios for a 67-year old woman. Costs and QALYs were discounted at 3% per year. RESULTS: The probability of blindness over 10 years was reduced from 56% to 34% if ranibizumab was efficacious for only 2 years, 27% if efficacy was maintained for a further 2 years only (base-case scenario), and 17% if visual acuity at 4 years was then sustained. It was cost-saving under all price assumptions, when caregiver costs were included. When caregiver costs were excluded, the cost per QALY for the base-case ranged from $5,600, assuming the bevazicumab price, to $91,900 assuming the wholesale ranibizumab price. The cost per QALY was < $50,000 when the cost of ranibizumab was less than $1000. CONCLUSION: From a societal perspective, ranibizumab was cost-saving. From a health care funder's perspective, ranibizumab was an efficient treatment when it cost less than $1000 per dose.

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

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.

Short-term impact of smoking cessation on myocardial infarction and stroke hospitalisations and costs in Australia.

OBJECTIVE: To estimate the short-term benefits of a reduction in smoking on acute myocardial infarction (AMI) and stroke hospitalisations and costs. DESIGN AND SETTING: Epidemiological study which applied functions describing reductions over time in risk of AMI and stroke in people quitting smoking to hospitalisation rates and costs for Australia. MAIN OUTCOME MEASURES: The numbers of AMI and stroke hospitalisations in 35-64-year-olds and the associated costs that could have been avoided over a 7-year period from 2001-02 if smoking prevalence had decreased by 1% in the first year (Scenario 1) or by 1% per annum for 5 consecutive years (Scenario 2). RESULTS: Under Scenario 1, almost 1000 hospitalisations for AMI and about 350 hospitalisations for stroke would have been avoided over 7 years, saving about $20.4 million in health care costs. Under Scenario 2, over 3000 AMI hospitalisations and over 1000 stroke hospitalisations would be avoided, and health care costs could be reduced by $61.6 million (2.75% of costs for AMI and stroke over the period). CONCLUSIONS: This study provides further support for the proposition that modest and achievable reductions in smoking rates can substantially improve health outcomes and reduce health care costs, even in the short term.

The potential for tobacco control to reduce PBS costs for smoking-related cardiovascular disease.

OBJECTIVE: To estimate Pharmaceutical Benefits Scheme (PBS) subsidies for drugs to treat smoking-related cardiovascular disease (CVD) in 2001-02, and over the period of the government's Intergenerational Report (IGR), assuming current smoking prevalence rates and a 5% absolute reduction. DESIGN AND SETTING: An Australian epidemiological study, using prescribing data, aetiological fraction methodology, and IGR trends. MAIN OUTCOME MEASURES: Estimated smoking-related PBS subsidy costs in 2001-02 and predicted cumulative subsidies until 2041-42, under current and reduced smoking prevalence assumptions. RESULTS: The PBS costs of smoking-related CVD in 2001-02 were $126 million, 9.77% of the cost of drugs for CVD and 2.96% of total PBS subsidies. The cumulative difference in these costs over the 40-year period with a 5% drop in smoking prevalence was predicted to be $4.5 billion, a 17% reduction. The saving would be $1.14 billion discounting future costs at 5% per year. CONCLUSIONS: Further investment in tobacco control interventions could curb the increasing cost of the PBS and contribute to government efforts to ensure the viability of Australia's healthcare-financing programs. The net present value of a campaign to reduce smoking prevalence was estimated at $1 billion, with an internal rate of return of 33%.