Screening mammography is recommended for women 50 to 69 years of age because of its proven efficacy and reasonable cost-effectiveness. Extending screening recommendations to include women 40 to 49 years of age remains controversial.
To compare the cost-effectiveness of screening mammography in women of different age groups.
Cost-effectiveness analysis done using Markov and Monte Carlo models.
General population of women 40 years of age and older.
Biennial screening from 50 to 69 years of age was compared with no screening. Screening done every 18 months from ages 40 to 49 years, followed by biennial screening from ages 50 to 69 years, was compared with biennial screening from ages 50 to 69 years.
Life-expectancy, costs, and incremental cost-effectiveness.
Screening women from 50 to 69 years of age improved life expectancy by 12 days at a cost of $704 per woman, resulting in a cost-effectiveness ratio of $21,400 per year of life saved. Extending screening to include women 40 to 49 years of age improved life expectancy by 2.5 days at a cost of $676 per woman. The incremental cost-effectiveness of screening women 40 to 49 years of age was $105,000 per year of life saved. On the basis of a multiway sensitivity analysis, there is a 75% chance that screening mammography in women 50 to 69 years of age costs less than $50,000 per year of life saved, compared with a 7% chance in women 40 to 49 years of age.
The cost-effectiveness of screening mammography in women 40 to 49 years of age is almost five times that in older women. When breast cancer screening policies are being set, the incremental cost-effectiveness of extending mammographic screening to younger women should be considered.
"To date there is little research evaluating the cost-effectiveness of breast cancer screening programs combining MM and CBE while incorporating costs other than screening examinations, including costs of diagnostic follow-up due to abnormal examinations, treatment, and post-treatment costs after diagnosis. While some studies have included treatment costs subsequent to diagnosis      , they have often been limited to specific age cohorts or subgroups (e.g. women older than 65). "
[Show abstract][Hide abstract] ABSTRACT: Breast cancer screening by mammography and clinical breast exam are commonly used for early tumor detection. Previous cost-effectiveness studies considered mammography alone or did not account for all relevant costs. In this study, we assessed the cost-effectiveness of screening schedules recommended by three major cancer organizations and compared them with alternative strategies. We considered costs of screening examinations, subsequent work-up, biopsy, and treatment interventions after diagnosis.
We used a microsimulation model to generate women's life histories, and assessed screening and treatment effects on survival. Using statistical models, we accounted for age-specific incidence, preclinical disease duration, and age-specific sensitivity and specificity for each screening modality. The outcomes of interest were quality-adjusted life years (QALY) saved and total costs with a 3% annual discount rate. Incremental cost-effectiveness ratios were used to compare strategies. Sensitivity analyses were done by varying some of the assumptions.
Compared with guidelines from the National Cancer Institute and the U.S. Preventive Services Task Force, alternative strategies were more efficient. Mammography and clinical breast exam in alternating years from ages 40 to 79 years was a cost-effective alternative compared with the guidelines, costing $35,500 per QALY saved compared with no screening. The American Cancer Society guideline was the most effective and the most expensive, costing over $680,000 for an added QALY compared with the above alternative.
Screening strategies with lower costs and benefits comparable with those currently recommended should be considered for implementation in practice and for future guidelines.
"The estimated difference is $1,682 $US 1995 or converted and inflated to 1999 dollars $2,522 $Can less for the screened group. It is assumed that the incidence of breast cancer in women 50 to 69 is 3.165 per thousand . "
[Show abstract][Hide abstract] ABSTRACT: Outreach facilitation has been proven successful in improving the adoption of clinical preventive care guidelines in primary care practice. The net costs and savings of delivering such an intensive intervention need to be understood. We wanted to estimate the proportion of a facilitation intervention cost that is offset and the potential for savings by reducing inappropriate screening tests and increasing appropriate screening tests in 22 intervention primary care practices affecting a population of 90,283 patients.
A cost-consequences analysis of one successful outreach facilitation intervention was done, taking into account the estimated cost savings to the health system of reducing five inappropriate tests and increasing seven appropriate tests. Multiple data sources were used to calculate costs and cost savings to the government. The cost of the intervention and costs of performing appropriate testing were calculated. Costs averted were calculated by multiplying the number of tests not performed as a result of the intervention. Further downstream cost savings were determined by calculating the direct costs associated with the number of false positive test follow-ups avoided. Treatment costs averted as a result of increasing appropriate testing were similarly calculated.
The total cost of the intervention over 12 months was $238,388 and the cost of increasing the delivery of appropriate care was $192,912 for a total cost of $431,300. The savings from reduction in inappropriate testing were $148,568 and from avoiding treatment costs as a result of appropriate testing were $455,464 for a total savings of $604,032. On a yearly basis the net cost saving to the government is $191,733 per year (2003 Can dollars) equating to $3,687 per physician or $63,911 per facilitator, an estimated return on intervention investment and delivery of appropriate preventive care of 40%.
Outreach facilitation is more expensive but more effective than other attempts to modify primary care practice and all of its costs can be offset through the reduction of inappropriate testing and increasing appropriate testing. Our calculations are based on conservative assumptions. The potential for savings is likely considerably higher.
BMC Health Services Research 04/2005; 5(1):20. DOI:10.1186/1472-6963-5-20 · 1.71 Impact Factor
"Laupacis et al (1992) suggested that a treatment costing less than $20,000/QALY could be considered very cost-effective, a treatment costing between $20,000/QALY and $100,000/QALY was judged acceptable, while a treatment costing more than $100,000/QALY was deemed not likely to be cost-effective . Other studies have suggested that $50,000/QALY provides a threshold for judging cost effectiveness [36,37]. Although arbitrary criteria, the application of any of the cited guidelines to the CUAs illustrated in the present study convey that the choice of algorithm can dictate whether the intervention is considered cost-effective or unacceptable. "
[Show abstract][Hide abstract] ABSTRACT: Cost utility analysis (CUA) using SF-36/SF-12 data has been facilitated by the development of several preference-based algorithms. The purpose of this study was to illustrate how decision-making could be affected by the choice of preference-based algorithms for the SF-36 and SF-12, and provide some guidance on selecting an appropriate algorithm.
Two sets of data were used: (1) a clinical trial of adult asthma patients; and (2) a longitudinal study of post-stroke patients. Incremental costs were assumed to be 2000 dollars per year over standard treatment, and QALY gains realized over a 1-year period. Ten published algorithms were identified, denoted by first author: Brazier (SF-36), Brazier (SF-12), Shmueli, Fryback, Lundberg, Nichol, Franks (3 algorithms), and Lawrence. Incremental cost-utility ratios (ICURs) for each algorithm, stated in dollars per quality-adjusted life year (dollars/QALY), were ranked and compared between datasets.
In the asthma patients, estimated ICURs ranged from Lawrence's SF-12 algorithm at 30,769 dollars/QALY (95% CI: 26,316 to 36,697) to Brazier's SF-36 algorithm at 63,492 dollars/QALY (95% CI: 48,780 to 83,333). ICURs for the stroke cohort varied slightly more dramatically. The MEPS-based algorithm by Franks et al. provided the lowest ICUR at 27,972 dollars/QALY (95% CI: 20,942 to 41,667). The Fryback and Shmueli algorithms provided ICURs that were greater than 50,000 dollars/QALY and did not have confidence intervals that overlapped with most of the other algorithms. The ICUR-based ranking of algorithms was strongly correlated between the asthma and stroke datasets (r = 0.60).
SF-36/SF-12 preference-based algorithms produced a wide range of ICURs that could potentially lead to different reimbursement decisions. Brazier's SF-36 and SF-12 algorithms have a strong methodological and theoretical basis and tended to generate relatively higher ICUR estimates, considerations that support a preference for these algorithms over the alternatives. The "second-generation" algorithms developed from scores mapped from other indirect preference-based measures tended to generate lower ICURs that would promote greater adoption of new technology. There remains a need for an SF-36/SF-12 preference-based algorithm based on the US general population that has strong theoretical and methodological foundations.
Health and Quality of Life Outcomes 02/2005; 3(1):11. DOI:10.1186/1477-7525-3-11 · 2.12 Impact Factor
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