The potential of breast cancer screening in Europe.

Currently, all European countries offer some form of breast cancer screening. Nevertheless, disparities exist in the status of implementation, attendance and the extent of opportunistic screening. As a result, breast cancer screening has not yet reached its full potential. We examined how many breast cancer deaths could be prevented if all European countries would biennially screen all women aged 50 to 69 for breast cancer. We calculated the number of breast cancer deaths already prevented due to screening as well as the number of breast cancer deaths which could be additionally prevented if the total examination coverage (organised plus opportunistic) would reach 100%. The calculations are based on total examination coverage in women aged 50 to 69, the annual number of breast cancer deaths for women aged 50 to 74 and the maximal possible mortality reduction from breast cancer, assuming similar effectiveness of organised and opportunistic screening. The total examination coverage ranged from 49% (East), 62% (West), 64% (North) to 69% (South). Yearly 21 680 breast cancer deaths have already been prevented due to mammography screening. If all countries would reach 100% examination coverage, 12 434 additional breast cancer deaths could be prevented annually, with the biggest potential in Eastern Europe. With maximum coverage, 23% of their breast cancer deaths could be additionally prevented, while in Western Europe it could be 21%, in Southern Europe 15% and in Northern Europe 9%. Our study illustrates that by further optimising screening coverage, the number of breast cancer deaths in Europe can be lowered substantially

Empirical estimates of prostate cancer overdiagnosis by age and prostate-specific antigen

Background: Prostate cancer screening depends on a careful balance of benefits, in terms of reduced prostate cancer mortality, and harms, in terms of overdiagnosis and overtreatment. We aimed to estimate the effect on overdiagnosis of restricting prostate specific antigen (PSA) testing by age and baseline PSA.Methods: Estimates of the effects of age on overdiagnosis were based on population based incidence data from the US Surveillance, Epidemiology and End Results database. To investigate the relationship between PSA and overdiagnosis, we used two separate cohorts subject to PSA testing in clinical trials (n = 1,577 and n = 1,197) and a population-based cohort of Swedish men not subject to PSA-screening followed for 25 years (n = 1,162).Results: If PSA testing had been restricted to younger men, the number of excess cases associated with the introduction of PSA in the US would have been reduced by 85%, 68% and 42% for age cut-offs of 60, 65 and 70, respectively. The risk that a man with screen-detected cancer at age 60 would not subsequently lead to prostate cancer morbidity or mortality decreased exponentially as PSA approached conventional biopsy thresholds. For PSAs below 1 ng/ml, the risk of a positive biopsy is 65 (95% CI 18.2, 72.9) times greater than subsequent prostate cancer mortality.Conclusions: Prostate cancer overdiagnosis has a strong relationship to age and PSA level. Restricting screening in men over 60 to those with PSA above median (>1 ng/ml) and screening men over 70 only in selected circumstances would importantly reduce overdiagnosis and change the ratio of benefits to harms of PSA-screening

Cost-effectiveness of multiparametric magnetic resonance imaging and MRI-guided biopsy in a population-based prostate cancer screening setting using a micro-simulation model

Background: The introduction of multiparametric magnetic resonance imaging (mpMRI) and MRI-guided biopsy has improved the diagnosis of prostate cancer. However, it remains uncertain whether it is cost-effective, especially in a population-based screening strategy. Methods: We used a micro-simulation model to assess the cost-effectiveness of an MRI-based prostate cancer screening in comparison to the classical prostate-specific antigen (PSA) screening, at a population level. The test sensitivity parameters for the mpMRI and MRI-guided biopsy, grade misclassification rates, utility estimates, and the unit costs of different interventions were obtained from literature. We assumed the same screening attendance rate and biopsy compliance rate for both strategies. A probabilistic sensitivity analysis, consisting of 1000 model runs, was performed to estimate

Race-Specific Impact of Natural History, Mammography Screening, and Adjuvant Treatment on Breast Cancer Mortality Rates in the United States

Background: U.S. Black women have higher breast cancer mortality rates than White women despite lower incidence. The aim of this study is to investigate how much of the mortality disparity can be attributed to racial differences in natural history, uptake of mammography screening, and use of adjuvant therapy. Methods: Two simulation models use common national race, and age-specific data for incidence, screening and treatment dissemination, stage distributions, survival, and competing mortality from 1975 to 2010. Treatment effectiveness and mammography sensitivity are assumed to be the same for both races. We sequentially substituted Black parameters into the White model to identify parameters that drive the higher mortality for Black women in the current time period. Results: Both models accurately reproduced observed breast cancer incidence, stage and tumor size distributions, and breast cancer mortality for White women. The higher mortality for Black women could be attributed to differences in natural history parameters (26-44%), use of adjuvant therapy (11-19%), and uptake of mammography screening (7-8%), leaving 38% to 46% unexplained. Conclusion: Black women appear to have benefited less from cancer control advances than White women, with a greater race-related gap in the use of adjuvant therapy than screening. However, a greater portion of the disparity in mortality appears to be due to differences in natural history and undetermined factors. Impact: Breast cancer mortality may be reduced substantially by ensuring that Black women receive equal adjuvant treatment and screening as White women. More research on racial variation in breast cancer biology and treatment utilization is needed. Cancer Epidemiol Biomarkers Prev; 20(1); 112-22. (C) 2011 AACR

Collaborative modeling of the impact of obesity on race-specific breast cancer incidence and mortality

Obesity affects multiple points along the breast cancer control continuum from prevention to screening and treatment, often in opposing directions. Obesity is also more prevalent in Blacks than Whites at most ages so it might contribute to observed racial disparities in mortality. We use two established simulation models from the Cancer Intervention and Surveillance Modeling Network (CISNET) to evaluate the impact of obesity on race-specific breast cancer outcomes. The models use common national data to inform parameters for the multiple US birth cohorts of Black and White women, including age- and race-specific incidence, competing mortality, mammography characteristics, and treatment effectiveness. Parameters are modified by obesity (BMI of a parts per thousand yen30 kg/m(2)) in conjunction with its age-, race-, cohort- and time-period-specific prevalence. We measure age-standardized breast cancer incidence and mortality and cases and deaths attributable to obesity. Obesity is more prevalent among Blacks than Whites until age 74; after age 74 it is more prevalent in Whites. The models estimate that the fraction of the US breast cancer cases attributable to obesity is 3.9-4.5 % (range across models) for Whites and 2.5-3.6 % for Blacks. Given the protective effects of obesity on risk among women < 50 years, elimination of obesity in this age group could increase cases for both the races, but decrease cases for women a parts per thousand yen50 years. Overall, obesity accounts for 4.4-9.2 % and 3.1-8.4 % of the total number of breast cancer deaths in Whites and Blacks, respectively, across models. However, variations in obesity prevalence have no net effect on race disparities in breast cancer mortality because of the opposing effects of age on risk and patterns of age- and race-specific prevalence. Despite its modest impact on breast cancer control and race disparities, obesity remains one of the few known modifiable risks for cancer and other diseases, underlining its relevance as a public health target

Collaborative modeling of the impact of obesity on race-specific breast cancer incidence and mortality

Obesity affects multiple points along the breast cancer control continuum from prevention to screening and treatment, often in opposing directions. Obesity is also more prevalent in Blacks than Whites at most ages so it might contribute to observed racial disparities in mortality. We use two established simulation models from the Cancer Intervention and Surveillance Modeling Network (CISNET) to evaluate the impact of obesity on race-specific breast cancer outcomes. The models use common national data to inform parameters for the multiple US birth cohorts of Black and White women, including age- and race-specific incidence, competing mortality, mammography characteristics, and treatment effectiveness. Parameters are modified by obesity (BMI of ≥30 kg/m(2)) in conjunction with its age-, race-, cohort- and time-period-specific prevalence. We measure age-standardized breast cancer incidence and mortality and cases and deaths attributable to obesity. Obesity is more prevalent among Blacks than Whites until age 74; after age 74 it is more prevalent in Whites. The models estimate that the fraction of the US breast cancer cases attributable to obesity is 3.9–4.5 % (range across models) for Whites and 2.5–3.6 % for Blacks. Given the protective effects of obesity on risk among women <50 years, elimination of obesity in this age group could increase cases for both the races, but decrease cases for women ≥50 years. Overall, obesity accounts for 4.4–9.2 % and 3.1–8.4 % of the total number of breast cancer deaths in Whites and Blacks, respectively, across models. However, variations in obesity prevalence have no net effect on race disparities in breast cancer mortality because of the opposing effects of age on risk and patterns of age- and race-specific prevalence. Despite its modest impact on breast cancer control and race disparities, obesity remains one of the few known modifiable risks for cancer and other diseases, underlining its relevance as a public health target

Tipping the Balance of Benefits and Harms to Favor Screening Mammography Starting at Age 40 Years A Comparative Modeling Study of Risk

Background: Timing of initiation of screening for breast cancer is controversial in the United States. Objective: To determine the threshold relative risk (RR) at which the harm-benefit ratio of screening women aged 40 to 49 years equals that of biennial screening for women aged 50 to 74 years. Design: Comparative modeling study. Data Sources: Surveillance, Epidemiology, and End Results program, Breast Cancer Surveillance Consortium, and medical literature. Target Population: A contemporary cohort of women eligible for routine screening. Time Horizon: Lifetime. Perspective: Societal. Intervention: Mammography screening starting at age 40 versus 50 years with different screening methods (film, digital) and screening intervals (annual, biennial). Outcome Measures: Benefits: life-years gained, breast cancer deaths averted; harms: false-positive mammography findings; harm-benefit ratios: false-positive findings/life-years gained, false-positive findings/deaths averted. Results of Base-Case Analysis: Screening average-risk women aged 50 to 74 years biennially yields the same false-positive findings/life-years gained as biennial screening with digital mammography starting at age 40 years for women with a 2-fold increased risk above average (median threshold RR, 1.9 [range across models, 1.5 to 4.4]). The threshold RRs are higher for annual screening with digital mammography (median, 4.3 [range, 3.3 to 10]) and when false-positive findings/deaths averted is used Results of Sensitivity Analysis: The threshold RRs changed slightly when a more comprehensive measure of harm was used and were relatively insensitive to lower adherence assumptions. Limitation: Risk was assumed to influence onset of disease without influencing screening performance. Conclusion: Women aged 40 to 49 years with a 2-fold increased risk have similar harm-benefit ratios for biennial screening mammography as average-risk women aged 50 to 74 years. Threshold RRs required for favorable harm-benefit ratios vary by screening method, interval, and outcome measure