For example , mammography screening does not seem to create anxiety in women who are given a clear result after a mammogram .
The incidence of breast cancer and mortality increases with age , and the GDG extrapolated that the absolute health benefits are greater in women aged 45 to 49 than those aged 40 to 44 years .
However , for the 45- to 49-year age group , the higher breast cancer incidence and mortality compared with women between the ages of 40 and 44 , as well as observational evidence showing a greater benefit in this age group ( 33 ) , led the GDG to judge that the balance of health effects probably favors screening , although the required re sources for screening likely differ across setting s ( 34 , 35 ) .
Other EtD criteria also were generally in favor of implementing organized mammography screening in this age group .
Despite intensified efforts by the European Council since 2003 , the implementation of organized , population -based mammography screening is not uniform across Europe and depends greatly on the policies in place in different countries , the organization of health care , and available re sources ( 1 ) .
Since the last edition of the European Guidelines on Breast Cancer Screening and Diagnosis was published in 2006 ( 2 ) , new evidence regarding breast cancer and innovation in guideline methodology prompted the European Commission Initiative on Breast Cancer ( ECIBC ) to develop new evidence -based recommendations ( in short , the European Breast Guidelines ) .
These guidelines inform women , health professionals , and policymakers about important questions related to organized mammography screening and breast cancer diagnosis , but recommendations may apply in context s in which organized screening programs are not in place .
Women generally consider these undesirable effects acceptable ( low certainty of evidence ) , and a systematic review suggested that women place a relatively low value on the psychosocial and physical effects of false-positive results and overdiagnosis ; however , some studies raised concerns about whether women fully underst and the result ing implication s ( 15 ) .
How Often Should Women Attend an Organized Mammography Screening Program ?
Benefits, Harms, and Cost-Effectiveness of Supplemental Ultrasonography Screening for Women With Dense Breasts
Editors ' Notes Context Many states have enacted laws that require mammography facilities to advise women with dense breasts and a negative mammography to consider supplemental testing with their providers . Contribution Three vali date d microsimulation models compared breast cancer outcomes , quality -adjusted life-years gained , and costs for mammography alone versus supplemental ultrasonography after a negative mammography result for women with dense breasts aged 50 to 74 years . Caution Other imaging methods , such as digital breast tomo synthesis , were not assessed . Implication Supplemental ultrasonography screening for women with dense breasts would result in limited health gains and substantially increase costs . Mammographic breast density is a risk factor for breast cancer ( 1 , 2 ) . It also affects mammography performance ( 36 ) . The false-negative rate of screening mammography varies as much as 10-fold from the lowest to the highest categories of breast density ( 5 ) . Because breast density affects cancer risk and the false-negative rate of screening , at least 19 states have enacted legislation requiring that women with dense breasts be told about their breast density after screening mammography and that they should discuss supplemental screening tests , such as ultrasonography , with their providers ( 7 , 8) . Similar legislation is under consideration at the national level ( 9 ) . Breast density notification laws have an uncertain effect on health but could affect millions of women . More than 40 % of women aged 40 to 74 years have dense breasts ( 10 ) , defined in the laws as heterogeneously or extremely dense breast tissue by the American College of Radiology 's Breast Imaging Reporting and Data System ( BI-RADS ) ( 9 , 11 ) . However , the American College of Radiology and other organizations have caution ed legislators , health policymakers , and health care providers to carefully consider the unintended consequences of legislation about breast density notification , including the uncertain harms and benefits of supplemental screening ( 8 , 1215 ) . These concerns are amplified because of the subjective nature of the BI-RADS breast density assessment and the challenges that providers face in accurately assessing and communicating breast cancer risk to their patients . Ultrasonography is often suggested for supplemental screening of women with dense breasts because it is widely available and has relatively low direct medical costs ( 1618 ) . Shortly after Connecticut became the first state to enact a law about breast density notification , as many as 30 % of women with dense breasts at some practice s within the state were having supplemental ultrasonography screening ( 1921 ) . Limited data from clinical trials and observational studies suggest that the addition of h and held ultrasonography screening to mammography for women with dense breasts increases cancer detection rates at the expense of increased biopsies for women without cancer ( 16 , 1922 ) . Moreover , the effect of supplemental ultrasonography screening on long-term outcomes , such as breast cancer mortality and its cost-effectiveness at a population level , are unknown ( 8) . We assessed the potential benefits , harms , and cost-effectiveness of supplemental screening ultrasonography for women with dense breasts using 3 established Cancer Intervention and Surveillance Modeling Network breast cancer models ( 23 ) . The models incorporate evidence from clinical trials and observational studies to estimate the effect of various screening scenarios on breast cancer outcomes , including breast cancer mortality , quality -adjusted life-years ( QALYs ) , and costs ( 24 , 25 ) . The results provide evidence for policymakers considering legislation about breast density notification and for women and providers evaluating screening options for women with dense breasts . Methods We used 3 microsimulation models  developed independently within the National Cancer Institutefunded Cancer Intervention and Surveillance Modeling Network consortium ( www.cisnet.cancer.gov ) : Model E ( Erasmus University Medical Center , Rotterdam , the Netherl and s ) , model G-E ( Georgetown University Medical Center , Washington , DC , and Albert Einstein College of Medicine , Bronx , New York ) , and model W ( University of Wisconsin , Madison , Wisconsin , and Harvard Medical School , Boston , Massachusetts ) . These modeling groups collaborate in the program project grant that supported this study and are described at http://cisnet.cancer.gov/breast/profiles.html and elsewhere ( 2628 ) . Appendix Table 1 outlines the main model differences and assumptions . Our analyses used a lifetime horizon and federal payer perspective . In brief , the models simulated life histories of women who were at risk for breast cancer , had screening , were treated for breast cancer diagnosed by screening or clinical detection , and were at risk for dying of breast cancer and other causes . The models had independent approaches and modeling structures ( 23 ) but used common inputs , including incidence in the absence of screening , mammography performance , treatment effectiveness , and competing causes of death ( 29 ) . The models approximately replicated U.S. breast cancer incidence and mortality trends ( 2628 , 30 ) ( Appendix Figure ) . For this analysis , we used simulated cohorts of women born in 1960 , as described elsewhere ( 24 , 25 ) . Appendix Table 1 . Key Assumptions and Features in the 3 Simulation Models Appendix Figure . Model replication of U.S. incidence and mortality patterns for women aged 30 to 79 y during 19752000 . Model E = Erasmus University Medical Center , Rotterdam , the Netherl and s ; model G-E = Georgetown University Medical Center , Washington , DC , and Albert Einstein College of Medicine , Bronx , New York ; model W = University of Wisconsin , Madison , Wisconsin , and Harvard Medical School , Boston , Massachusetts ; SEER = Surveillance , Epidemiology , and End Results Program . Model Variables At age 40 years , women in the simulated model cohorts were assigned an initial breast density on the basis of the distribution of BI-RADS density categories for premenopausal women in the Breast Cancer Surveillance Consortium ( BCSC ) ( Table 1 ) ( 31 ) . At age 50 years , women were assigned to the same breast density category or the next lower category so the prevalence of breast density categories matched the BCSC observed prevalence for postmenopausal women ( 31 ) . Sensitivity analyses were conducted with model W to examine the effect of reassigning density at both ages 50 and 65 years , on the basis of the BCSC data on the prevalence of breast density for women aged 50 to 64 years ( 44 % with dense breasts ) and 65 years or older ( 33 % with dense breasts ) . In all scenarios , a woman 's modeled risk for breast cancer depended on her age and breast density , on the basis of BCSC data ( Table 1 ) . Table 1 . Key Common Input Used by the 3 Simulation Models : BI-RADS Breast Density Sensitivity and specificity of digital mammography  were determined as a function of age , breast density , and screening interval using BCSC data ( Appendix Table 2 ) ( 32 ) . To our knowledge , the American College of Radiology Imaging Network Protocol 6666 study , a r and omized trial of using h and held ultrasonography to screen women with at least 1 risk factor for breast cancer , was the only controlled study of ultrasonography test performance ( 33 ) . On the basis of this study , experts estimated  screening ultrasonography performance after a negative mammography result for average-risk women . We used a  screening ultrasonography sensitivity of 55 % for women with dense breasts after a negative mammography result . We used a specificity of 94 % , with positive examination results defined as those recommended for biopsy . Models were calibrated so 94 % of ultrasonography screendetected cancer cases were invasive and 6 % were in situ , as seen in published studies ( 16 , 22 ) . Sensitivity analyses evaluated a range of performance characteristics ( Table 2 ) . Appendix Table 2 .  Digital Mammography Sensitivity and Specificity , by Screening Interval , Age Group , and Breast Density Table 2 . Key Common Input Used by the 3 Simulation Models : Screening Ultrasonography Performance Health-related quality -of-life utilities were a function of age ( 34 ) and decremented for breast cancer diagnosis and stage-specific treatment ( 35 ) . Sensitivity analyses included short-term reductions in quality of life for a screening examination ( 0.6 % for 1 week per screening examination ) or a positive screening result ( 10.5 % for 5 weeks ) ( 36 ) . The cost of a digital mammography screen  was $ 138 based on the 2013 Medicare reimbursement rate . Screening ultrasonography does not currently have a specific reimbursement rate , so we used the reimbursement rate for diagnostic breast ultrasonography , which is $ 100 . Sensitivity analyses were also conducted using higher potential reimbursement rates for screening ultrasonography because of its increased work intensity compared with diagnostic ultrasonography .  Diagnostic costs for additional imaging and biopsy after a positive screening mammography result and costs for cancer treatment were based on Medicare reimbursement rates , utilization patterns seen in the BCSC , and estimates from the literature ( 32 , 37 ) . Diagnostic costs after a positive ultrasonography result were assumed to be equal to the biopsy-related costs of diagnostic work-up after a positive mammography result . All costs were in 2013 U.S. dollars . Screening Strategies Primary analysis compared 3 strategies for women aged 50 to 74 years receiving biennial mammography screening  : mammography alone , mammography plus screening ultrasonography after a negative mammography result for women with extremely dense breasts , and mammography plus h and held screening ultrasonography after a negative mammography result for women with heterogeneously or extremely dense breasts ( base case ) . Secondary analyses evaluated the 3 strategies as an annual screening regimen for women aged 40 to 74 years . All strategies were compared with no
For example , mammography screening does not seem to create anxiety in women who are given a clear result after a mammogram .
The incidence of breast cancer and mortality increases with age , and the GDG extrapolated that the absolute health benefits are greater in women aged 45 to 49 than those aged 40 to 44 years .
However , for the 45- to 49-year age group , the higher breast cancer incidence and mortality compared with women between the ages of 40 and 44 , as well as observational evidence showing a greater benefit in this age group ( 33 ) , led the GDG to judge that the balance of health effects probably favors screening , although the required re sources for screening likely differ across setting s ( 34 , 35 ) .
Other EtD criteria also were generally in favor of implementing organized mammography screening in this age group .
Despite intensified efforts by the European Council since 2003 , the implementation of organized , population -based mammography screening is not uniform across Europe and depends greatly on the policies in place in different countries , the organization of health care , and available re sources ( 1 ) .
Since the last edition of the European Guidelines on Breast Cancer Screening and Diagnosis was published in 2006 ( 2 ) , new evidence regarding breast cancer and innovation in guideline methodology prompted the European Commission Initiative on Breast Cancer ( ECIBC ) to develop new evidence -based recommendations ( in short , the European Breast Guidelines ) .
These guidelines inform women , health professionals , and policymakers about important questions related to organized mammography screening and breast cancer diagnosis , but recommendations may apply in context s in which organized screening programs are not in place .
Women generally consider these undesirable effects acceptable ( low certainty of evidence ) , and a systematic review suggested that women place a relatively low value on the psychosocial and physical effects of false-positive results and overdiagnosis ; however , some studies raised concerns about whether women fully underst and the result ing implication s ( 15 ) .
How Often Should Women Attend an Organized Mammography Screening Program ?