This study performed an economic evaluation of different BC mammography screening strategies in Catalonia (Spain), using mathematical models. We assumed the perspective of the national health system and considered the direct healthcare costs over time of screening, diagnosis, initial treatment, follow-up and advanced care.
Our results show that, based on the incremental cost-effectiveness ratio (ICER), a reduced number of strategies can be selected for consideration from a set of 20 screening scenarios. Strategies that start at age 50 and end at age 74 predominate among those selected when the effectiveness of screening is measured in terms of the number of lives extended, and strategies that start at the ages 40 or 45 and end at age 69 predominate when the effect is measured as YL or QALYs. Independently of how the effect is measured, the ICER increases considerably when moving from biennial to annual scenarios.
An interesting result is that, assuming 100% participation in the studied screening strategies, the background is always the reference scenario because it has the lowest cost. But the effectiveness of the background is the lowest, for all the effect measures. In addition, once the non dominated scenarios are ordered according the ICER, always the next alternative is B50-69 that corresponds to the current public screening program in Catalonia. However, in some cases, other alternatives are more effective at a cost that could be considered implementable, given the generally accepted reference values. When the effect is measured as YL or QALY, these alternatives start the screening at ages younger than 50 years whereas only a few suggest to finish after the age 69.
Sensitivity analysis showed that the results were robust to moderate changes in costs of treatment or length of follow-up after initial treatment. Only dramatic increases of advanced cancer care modified the scenarios selected in the cost-effectiveness analysis in favor of annual screening scenarios. We did not perform a sensitivity analysis of changes in the survival functions as a result of improvements in mortality and prognosis after a BC diagnosis. The CISNET groups verified that there was a negative interaction between screening and adjuvant treatments. That means that the benefits of screening are smaller if treatments are more effective. As Cronin et al. pointed out, taken to the extreme, if treatment were completely curative there would be no additional mortality benefit associated with early detection .
Costs of diagnosing and treating breast cancer
Many authors have studied the costs of diagnosing and/or treating BC [3, 4, 28–31]. There is high variability in the methodology, patient characteristics, perspective and time horizon used. Some authors calculate the net costs by subtracting the costs of care of age-matched controls [28, 30]. Other authors identify the cancer-associated costs, which requires someone to decide which costs should be included. Some studies restrict the analysis to pre- or post-menopausal status  or to screened or non-screened groups. The objectives of studying costs also can be very different, from performing a descriptive study of costs from diagnosis to death  to building a simulation model . Nevertheless some characteristics are common to most of the studies, for instance, the acceptance of increasing costs over time of advanced cancer care, and the substantial weight of hospitalization costs [28, 29, 31].
A major challenge is to estimate the costs of advanced disease. Even though clinical practice guidelines provide standard treatment for advanced disease, very often treatments are customized according to the tumor or the patient's characteristics and the response to each treatment line. De Koning et al.  and Richards et al.  pioneered the economic evaluation of advanced cancer care in the early 1990s when screening programs were spreading and information about their impact was needed. Recently, Guest et al. estimated the costs of palliative care for BC as £2,482 (at 2000/2001 prices) per patient . Berkowitz et al.  assessed the lifetime direct costs of treating metastatic disease using the Statistics Canada's Population Health Model. On average, women with metastatic disease were expected to live three years and to incur direct treatment costs of approximately $60,000 per case, in 1998 US dollars. In comparison, patients treated for metastatic BC in our study had, on average, lower costs, 28,413 €. These differences may be explained, in part, by financial and organizational differences in health systems. In 2005, health care expenditure measured in PPP (Purchasing Power Parity) per capita was $2,225 in Spain, $3,326 in Canada and $6,401 in the USA .
Campbell et al. reviewed 29 cost-of-illness studies for BC in the US . Of these, 22 measured only direct medical costs and took the health payer perspective. The estimated lifetime per-patient costs ranged from $US 20,000 to $US 100,000. The costs of initial and terminal treatments were greater than follow-up care on a per-unit-time basis, but follow-up care accounted for the largest part of lifetime cost due to the relatively long survival of BC patients. In our study, the estimated cost over time per patient fluctuated between 26,000 and 35,000 € depending on the intensity of early detection exams (no screening or annual screening in the 40-79 years of age interval, respectively). When a 3% discount was applied, cost over time per patient oscillated between 25,600 and 37,000 € (Table A.1 in Additional file 1).
The distribution of costs by phase in our study is consistent with the results found in the literature. When averaging the cost by phase over the different scenarios, for a cohort of 100,000 women at birth, the highest cost corresponded to initial treatment (63,083,670 €), followed by detection cost (55,353,560 €), advanced cancer care (33,011,915 €) and the costs of follow-up (3,031,631 €).
Cost-effectiveness of mammography screening
Several authors have studied the cost-effectiveness of mammography screening using mathematical models [23, 38–41]. Generally, these studies assess the effect of different screening strategies in relation to no screening. Some of them include the current guidelines or the actual screening scenarios among the compared screening strategies.
Wong et al. studied the cost-effectiveness of mammography screening in Chinese women in Hong Kong, adopting a societal perspective . They compared biennial alternatives beginning at ages 40 or 50 and ending at ages 69 or 79, with the results from no screening. The least costly, non-dominated strategy was screening from ages 40 to 69 years, with an ICER of $61,600 per QALY saved or $64,400 per life year saved compared with no screening. These values were much higher than ours or other found in the literature. A difference with our study is that Wong et al. included ductal carcinoma in situ (DCIS) cases. Lee et al.  studied the cost-effectiveness of mammography screening in Korea using the model proposed by Lee and Zelen . The effectiveness of mammography screening was defined as the probability of detecting BC in the preclinical state and the cost was based on the direct cost of mammography screening and confirmative tests. They concluded that biennial mammography screening for women aged at least 40 years was cost-effective. Ahern et al. assessed the cost-effectiveness of screening strategies recommended by the National Cancer Institute, the American Cancer Society (ACS), and the US Prevention Services Task Force in the USA and compared them with alternative strategies, using a microsimulation model. Mammography and clinical breast exams 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 ACS guideline was the most effective and the most expensive, costing over $680,000 for an added QALY compared with the above alternative. The authors concluded that strategies with lower costs and benefits comparable with those currently recommended should be considered for implementation in practice and future guidelines.
In Spain, Plans et al., in 1996, compared the direct health service costs of a round of screening for a program that screened women aged 50-64 years with the resulting estimated cancers detected . They estimated a cost per women screened of $350 and a cost-effectiveness ratio of $7,020 per year of life gained. Garuz et al., in 1997, performed a cost-effectiveness analysis of a BC mammography screening program that consisted of a biennial mammography in all women 50-64 years old . They used data from the Navarre Screening Program, the Guipuzcoa Cancer Registry and the literature. Costs were estimated using a Markov model and measured in 1993 ECUs (1 ECU = 1 €) and a discount of 6%. The cost-effectiveness ratio per avoided death was 115,500 ECUs and 7,300 ECUs per saved life year. Extending the program to women 45-49 years represented an incremental cost of 229,000 and 9,400 ECUs, respectively. We did not analyze the strategy for ages 50-64, but our biennial 50-69 strategy, compared with the background, resulted in around 28,500 € per avoided death and 3,500 € per year of life saved. Extending the program to the 45-49 age group would represent an incremental cost of 162,000 and 7,000 €, respectively. Our values are lower than those reported by Garuz et al. This may be explained by differences in cost assessment, in the discount rate and time value of money (6% and future value in Garuz et al. versus 3% and present value in ours) and in the age at the last exam, 64 versus 69 years. The non-discounted cost per life saved in the Garuz et al. study was 38,400 €, a value more similar to ours.
Beemsterboer et al.  using Catalan data on BC mortality, incidence and screening and Dutch data on costs, obtained cost-effectiveness ratios equivalent to 5,553, 4,387 and 4,321 € per YL (5% discounting) for scenarios that target women 50-64 years of age with screening intervals of one, two and three years, respectively. De Koning et al., in 2000, reported the cost per YL of screening with biennial mammograms as 2,650 € in Navarra (ages 45-65), 4,475 € in Catalonia and 7,125 € in Spain (both for ages 50-69) . Our result, for B50-69, was 3,555 € per YL, compatible with the Beemsterboer and de Koning results, even though the costs of treating BC have increased in the last decade.
We have used a very detailed model that allowed us to thoroughly assess the cost and effectiveness of different screening scenarios. However, our study has several limitations, among them are the following. Our model relies on data and assumptions that may be not correct. When available, we have used Catalan or Spanish data from population based registries or BC screening programs. If the input data was not available at the region or country level, we used data that the CISNET had prepared for BC mortality modeling research groups in the USA . Finally, there were some inputs that Lee and Zelen had obtained from published randomized clinical trials and observational studies. In a previous publication, we performed a sensitivity analysis to assess the effect of departures from the modeling assumptions on the effectiveness of early detection  and we concluded that the model was robust.
We have not obtained confidence intervals of the model outputs. Our model is probabilistic because it works with the probability density functions of the different inputs related to the natural history or detection of BC. It is also an analytic model that consists of a set of equations describing BC mortality over time. There is uncertainty associated with the model inputs and there is also uncertainty associated with the model structure. It is complex and computationally intensive to obtain the variance of the model estimates. Instead, we have carried out a sensitivity analysis to explore how changes in the input parameters affect the results.
With respect to the outcome measures, we have included LE as a measure of effect together with YLG and QALYs. We want to highlight that the standard and internationally recognized measure to compare different health interventions and measure their effectiveness is the QALY . Although it can be interesting to estimate the amount of LE, this measure is less robust as an outcome measure and cannot be recommended as the basis for population-based policy decisions.
With respect to costs, we have several considerations. a) Costs were obtained from a single public hospital in Barcelona, which may not be representative of the hospitals in the region. However, we believe that the costs of diagnosing and treating BC in the hospitals of the Catalan public health system are not remarkably different. b) Advanced care costs were obtained from a small sample of metastatic BC patients at diagnosis. About one third of them were still alive after five years. Including living patients in the calculations may have underestimated the average cost of treating advanced disease. Excluding living patients from the analysis would have produced a biased sample. More adequate methods, based on the Kaplan-Meier sample average estimate , would have produced a better estimate, but we did not have all the necessary information to apply them, such as the costs of treatment over time on a monthly basis. c) Innovative treatments for advanced BC that currently may represent an improvement in survival or quality of life as well as an increase in cost were not available in the 2000-2003 time period. Despite these issues, sensitivity analyses showed that the results only changed when costs varied dramatically. d) We restricted the study to direct healthcare costs and the perspective of the national health system because the sources of indirect costs and the methods used to estimate them are heterogeneous, thus the estimates have high variability depending on the approach adopted. Reviewing some works that analyze the differences in the total costs (direct and indirect) for cancer patients in Spain, we found that indirect costs can represent from 20% to 70% of the total costs [46, 47]. Obviously, the results that we present could have been very different if indirect costs had been considered.
The decision of implementing a specific alternative is influenced by the budget assigned to the screening program and also by the amount that society is willing to pay for each effectiveness unit. Since the number of LE or mortality reduction is not a standard effectiveness measure in economic assessments, is not easy to find reference values for comparison.
There is scarce information in the literature about rates of false positives for invasive and non-invasive tests to diagnose BC in a non-screened population. Again, the sensitivity analysis showed that the selected scenarios were robust to changes in the assumptions.
Our study did not take into account either overdiagnosis of BC as a consequence of screening or DCIS. The impact of overdiagnosis would be to increase costs and decrease quality of life. Strategies with a higher number of screening exams (annual) would have a higher incremental cost per additional effect unit and, therefore, would end up being dominated by less intensive screening strategies (biennial). We have not accounted for overdiagnosis because there is high variability in overdiagnosis estimates. When we studied overdiagnosis in our region, we obtained a high association between exposure to screening and an increase in incidence, beyond what was expected by the advance of diagnosis, but the precision of the overdiagnosis estimate was low . We would like to have a more precise estimate of overdiagnosis before including it in the model.
In our model, DCIS cases were not included. The researchers that developed the probabilistic model that we have used considered that available information on the natural history of in situ disease was insufficient to include in situ tumors in the model . When observing the results of the CISNET groups in the USA, there does not seem to be a pattern between the screening benefits (in terms of mortality reduction) produced by the models and whether or not they modeled in situ disease . Nevertheless, including DCIS would increase the costs of treatment and decrease quality of life for the DCIS tumors that would not progress, similarly to overdiagnosis. We plan to incorporate both, DCIS and overdiagnosis, in future models.