The Impact of Breast Cancer Screening on Population Health

Breast cancer is an important public health problem with an estimated number of 1.38 million breast cancer cases and 458,000 deaths from the disease yearly worldwide. Randomized trials have shown that mammography screening significantly reduces breast cancer mortality. Besides the benefits in terms of lives saved, mammography screening is, however, also associated with harms, such as false-positive test results and overdiagnosis. This thesis describes the impact of breast cancer screening in the population and compares the effects to the effects of other interventions. We found that mammography screening has had a substantial impact on breast cancer mortality in the U.S. and is projected to continue to do so in the future. Screening women biennially from age 50 to 74 years leads to a favorable balance between benefits and harms. More intensive screening (either extending the age ranges or increasing the screenin

Health-related Quality of Life using the EQ-5D-5L:normative utility scores in a Dutch female population

PURPOSE: Normative utility scores represent the health related quality of life of the general population, are of utmost importance in cost-effectiveness studies and should reflect relevant sexes and age groups. The aim of this study was to estimate EQ-5D-5L normative utility scores in a population of Dutch females, stratified by age, and to compare these scores to those of female populations of three other countries. METHODS: Dutch women completed the EQ-5D-5L online between January and July 2020. Mean normative utilities were computed using the Dutch EQ-5D-5L value set, stratified by age, tested for differences using the Kruskall–Wallis test, and compared to normative utility scores of female populations elsewhere. Additionally, to support the use of the Dutch EQ-5D-5L data in other settings, normative utility scores were also calculated by applying the value sets of Germany, United Kingdom and USA. RESULTS: Data of 9037 women were analyzed and the weighted mean utility score was 0.911 (SD 0.155, 95% CI 0.908–0.914). The mean normative utility scores differed between age groups, showing lower scores in older females. Compared to other normative utility scores of female populations, Dutch mean utilities were consistently higher except for age groups 18–24 and 25–34. With the three country-specific value sets, new age-specific mean normative utility scores were provided. CONCLUSION: This study provides mean normative utility scores of a large cohort of Dutch females per age group, which were found to be lower in older age groups. Utility scores calculated with three other value sets were made available. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11136-022-03271-3

Finding the optimal mammography screening strategy:A cost-effectiveness analysis of 920 modelled strategies

Breast cancer screening policies have been designed decades ago, but current screening strategies may not be optimal anymore. Next to that, screening capacity issues may restrict feasibility. This cost‐effectiveness study evaluates an extensive set of breast cancer screening strategies in the Netherlands. Using the Microsimulation Screening Analysis‐Breast (MISCAN‐Breast) model, the cost‐effectiveness of 920 breast cancer screening strategies with varying starting ages (40‐60), stopping ages (64‐84) and intervals (1‐4 years) were simulated. The number of quality adjusted life years (QALYs) gained and additional net costs (in €) per 1000 women were predicted (3.5% discounted) and incremental cost‐effectiveness ratios (ICERs) were calculated to compare screening scenarios. Sensitivity analyses were performed using different assumptions. In total, 26 strategies covering all four intervals were on the efficiency frontier. Using a willingness‐to‐pay threshold of €20 000/QALY gained, the biennial 40 to 76 screening strategy was optimal. However, this strategy resulted in more overdiagnoses and false positives, and required a high screening capacity. The current strategy in the Netherlands, biennial 50 to 74 years, was dominated. Triennial screening in the age range 44 to 71 (ICER 9364) or 44 to 74 (ICER 11144) resulted in slightly more QALYs gained and lower costs than the current Dutch strategy. Furthermore, these strategies were estimated to require a lower screening capacity. Findings were robust when varying attendance and effectiveness of treatment. In conclusion, switching from biennial to triennial screening while simultaneously lowering the starting age to 44 can increase benefits at lower costs and with a minor increase in harms compared to the current strategy

Extrapolation of pre-screening trends: Impact of assumptions on overdiagnosis estimates by mammographic screening

Background: Overdiagnosis by mammographic screening is defined as the excess in breast cancer incidence in the presence of screening compared to the incidence in the absence of screening. The latter is often estimated by extrapolating the pre-screening incidence trend. The aim of this theoretical study is to investigate the impact of assumptions in extrapolating the pre-screening incidence trend of invasive breast cancer on the estimated percentage of overdiagnosis. Methods: We extracted data on invasive breast cancer incidence and person-years by calendar year (1975-2009) and 5-year age groups (0-85 years) from Dutch databases. Different combinations of assumptions for extrapolating the pre-screening period were investigated, such as variations in the type of regre

Breast Cancer Screening in Georgia:Choosing the Most Optimal and Cost-Effective Strategy

Objectives: To define the optimal and cost-effective breast cancer screening strategy for Georgia. Methods: We used the Microsimulation Screening Analysis-Breast (MISCAN-Breast) model that has been adapted to the Georgian situation to evaluate 736 mammography screening strategies varied by interval (biennial and triennial), starting ages (40-60 years), stopping ages (64-84 years), and screening modality (with and without clinical breast examination [CBE]). Quality-adjusted life-years (QALYs) and additional cost (healthcare perspective) compared with no screening per 1000 women were calculated with 3% discount. Major uncertainties (eg, costs) are addressed as sensitivity analyses. Results: Strategies using a combination of mammography and CBE yielded in substantially higher costs with minimal differences in outcomes compared with mammography-only strategies. The current screening strategy, biennial mammography screening from the age of 40 until 70 years with CBE, is close to the frontier line but requires high additional cost given the QALY gains (€16 218/QALY), well above the willingness-to-pay threshold of €12 720. The optimal strategy in Georgia would be triennial mammography-only screening from age 45 to 66 years with an incremental cost-effectiveness ratio of €12 507. Conclusions: Biennial screening strategies are resource-intensive strategies and may not be feasible for Georgia. By switching to triennial mammography-only strategy from the age of 45 until 66 years, it is possible to offer screening to more eligible women while still gaining substantial screening benefits. This is to address capacity issues which is a common barrier for many Eastern European countries.</p

Health utility values of breast cancer treatments and the impact of varying quality of life assumptions on cost-effectiveness

In breast cancer research, utility assumptions are outdated and inconsistent which may affect the results of quality adjusted life year (QALY) calculations and thereby cost-effectiveness analyses (CEAs). Four hundred sixty four female patients with breast cancer treated at Erasmus MC, the Netherlands, completed EQ-5D-5L questionnaires from diagnosis throughout their treatment. Average utilities were calculated stratified by age and treatment. These utilities were applied in CEAs analysing 920 breast cancer screening policies differing in eligible ages and screening interval simulated by the MISCAN-Breast microsimulation model, using a willingness-to-pay threshold of €20,000. The CEAs included varying sets on normative, breast cancer treatment and screening and follow-up utilities. Efficiency frontiers were compared to assess the impact of the utility sets. The calculated average patient utilities were reduced at breast cancer diagnosis and 6 months after surgery and increased toward normative utilities 12 months after surgery. When using normative utility values of 1 in CEAs, QALYs were overestimated compared to using average gender and age-specific values. Only small differences in QALYs gained were seen when varying treatment utilities in CEAs. The CEAs varying screening and follow-up utilities showed only small changes in QALYs gained and the efficiency frontier. Throughout all variations in utility sets, the optimal strategy remained robust; biennial for ages 40-76 years and occasionally biennial 40-74 years. In sum, we recommend to use gender and age stratified normative utilities in CEAs, and patient-based breast cancer utilities stratified by age and treatment or disease stage. Furthermore, despite varying utilities, the optimal screening scenario seems very robust.</p