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Evaluating Organized Breast Cancer Screening Implementation

The Prevention of Late-Stage Disease?

¹ Center for Health Studies, Group Health Cooperative, Seattle, Washington; ² Department of Epidemiology, University of Washington, Seattle, Washington; and ³ Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
The objective of our study was to evaluate organized breast cancer screening implementation by measuring the association between screening program enrollment and late-stage disease. Our setting was a health plan using mailed mammography reminders to women ages 40. We conducted yearly cross-sectional summaries of mammography experience and late-stage (regional or distant Surveillance Epidemiology and End Results Reporting (SEER) stage) breast cancer occurrence for all of the health-plan women ages 40 (1986–1998). We estimated the odds of late-stage breast cancer among health-plan and surrounding community women because it was too early to compare changes in mortality. We also estimated the odds of late-stage disease (1995–1998) associated with program enrollment and mammography screening among health-plan women. We found that mammography-within-two-years increased within the health plan from 25.9% to 51.2% among women ages 40–49 and from 32.9% to 74.7% among women ages 50. Health-plan late-stage rates were lower than those in the surrounding community [ages 40–49: odds ratio (OR), 0.87; 95% confidence interval (CI), 0.77–0.99; ages 50–79: OR, 0.86; 95% CI, 0.80–0.92] and declined parallel to the community. Among health-plan cancer cases, women ages 43 who were enrolled in the screening program and who had at least one program mammogram were less likely to have late-stage disease compared with the women not enrolled in the program (OR, 0.31; 95% CI, 0.16–0.61) but the odds of late-stage was also reduced among program-enrolled women not receiving program mammograms (OR, 0.45; 95% CI, 0.21–0.95). We concluded that enrollment in organized screening is associated with increased likelihood of mammography and reduced odds of late-stage breast cancer. Addressing the concerns of un-enrolled women and those without mammograms offers an opportunity for further late-stage disease reduction.

	Introduction

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Women, physicians, healthcare organizations, and governments seek evidence that breast cancer screening with mammography is contributing to progress toward breast cancer mortality reductions (1, 2, 3, 4) . Women have heard the controversy about the quality of breast cancer screening trials and wonder whether they should bother getting a mammogram (5 , 6) . Primary care physicians face multiple competing demands and must consciously choose to make breast cancer screening referrals (7 , 8) . Health plans and governments face constrained healthcare resources and must make decisions about continuing organized breast cancer screening programs or investing in screening for other conditions (1, 2, 3, 4 , 9, 10, 11, 12) . We undertook this study to evaluate whether offering organized breast cancer screening is associated with indicators of program implementation success, including program enrollment, increased mammography, reduction in late-stage breast cancer, and a reduced odds of late-stage disease among program-enrolled women. The results have relevance to anyone seeking evidence regarding the effectiveness of mammography screening.

Implementation of screening mammography occurs through referral to a radiology facility (opportunistic screening) or through organized programs (organized screening) (13) . Opportunistic screening usually occurs at the time of a clinical encounter with a primary care provider for a complete physical examination or women’s health visit for cervical cancer screening, but women’s self-referral for mammograms also occurs (14 , 15) . Most organized programs include a centralized administrative structure, screening centers that serve a specific population, direct-mail reminders to women, quality control efforts, and an evaluation component (13) . Organized screening exists in some not-for-profit managed care plans in the United States, several European countries, and Canada (16 , 17) . The proportion of women screened varies from 50 to 89% in countries with organized plans (13 , 16) . In the United States, where opportunistic screening is the norm, 64.4% of women ages 40–49 and 75.3% of women ages 50–64 had a mammogram within the prior 2 years by 1998 (16 , 18) . Whether to offer organized screening programs is of interest because relying on the patient-physician interaction may be inadequate, but organizing programs takes resources (13 , 19, 20, 21) .

Health-plan administrators and policymakers need early markers of progress to demonstrate effective screening implementation and to justify continued investment in the face of competing demands. Successful implementation of breast cancer screening programs should result in a high level of program enrollment among the population to whom it is offered and, therefore, a high proportion of women should have regular screening. If both occur, then we expect to see a decreasing rate of late-stage breast cancer, a reduced risk of late-stage disease among those who are program enrolled and screened, and a reduced risk of mortality. Although reduced mortality is the desired program effect, achieving that effect takes years so we used late-stage breast cancer as a proxy for mortality. We chose late-stage breast cancer as our outcome measure based on three assumptions: (a) mortality reductions are possible through mammography (1 , 2 , 22 , 23) ; (b) late-stage disease rates will fall before mortality reductions occur; and (c) late-stage disease is strongly correlated with mortality (24, 25, 26) . Declining rates of late-stage disease provide evidence of successful screening mammography implementation because cancer stage is established at diagnosis (24, 25, 26) . Declining rates of late-stage disease also reflect program effects that are independent of treatment and, in this respect, have an advantage over mortality end points for monitoring screening program progress.

This evaluation has three components that capture the expected changes in a population offered a screening program: (a) an evaluation of mammography diffusion among health-plan women (component 1, mammography diffusion); (b) an evaluation of the rate of late-stage disease (component 2, late-stage rates) among health-plan and community women; and (c) an evaluation of the odds of late-stage disease among health-plan women as a function of program enrollment and screening exposure (component 3, modeling the odds of late-stage disease). We had three major hypotheses: (a) that mammography use would increase over time among health-plan women and be higher among women ages 50 compared with those ages 40–49; (b) that late-stage rates would decrease with time; and (c) that the risk of late-stage disease would be reduced with program enrollment and the receipt of program mammograms.

	Subjects and Methods

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Setting.
We conducted this study at Group Health Cooperative (GHC), a not-for-profit health plan with salaried primary care and specialty providers that served more than 350,000 average annual health-plan enrollees during the study period and delivered most services through the health plan facilities. This analysis focused on the 94.5% of the enrollees in the staff model Puget Sound plan who were offered an organized breast cancer screening program (27, 28, 29, 30) . We excluded the 5.5% of women served through contract-care because of differences in when and how the health plan implemented the screening program for these women. We also evaluated cancer rates in the surrounding community for comparison. However, there is no automated record of mammography exposure in the community; therefore, that comparison was not made.

Group Health Cooperative’s Breast Cancer Screening Program (BCSP) began in 1986 to track screening mammography, to mail reminders to women ages 40, to provide reports of screening status to primary care physicians, and to oversee implementation in six screening centers (17 , 27, 28, 29, 30) . The program uses a centralized database to manage a risk factor survey and to serve an average annual population of 80,000 women over the age of 40 years in the health plan. Eighty-five % of women ages 40 complete the survey, and there is no upper age-limit for reminder letters. Classic risk factors (e.g., onset of menses, age when menses end, first- and second-degree family history of breast cancer, previous breast biopsy, atypical hyperplasia on a previous biopsy) are used with age (i.e., 50) to identify a high-risk population and to send reminders at 1- or 2-year intervals (27, 28, 29, 30) . The proportion of the population that is eligible for mammography reminders differs by age categories and includes 65% of women ages 40–49 and all women ages 50 and above. Women ages 40–49 without classic risk factors (35% of women ages 40–49) are not offered reminders until age 50 but may seek screening through their usual care provider. Any woman may be screened at any interval of 1 or more years through their primary care provider.

The program staff monitors monthly automated mailings that include information about the program, the invitation to complete the risk-factor survey and to join the program, and/or reminders to women due for a screening center appointment. During the study period, a screening center appointment included a breast physical examination by a nurse practitioner, instruction in breast self-examination, and a screening mammogram. If a woman had a screening mammogram through her provider during the recommended interval, then she did not get a reminder from the program, and the provider was responsible for any clinical breast examination. Women continued to get reminders until they or their provider requested exclusion. Screening program mammograms and physician-referred mammograms occurred in the same facilities and used the same equipment. Nurses coordinated follow-up of all screened women, regardless of whether the screening occurred within the program or on primary-care referral.

Surveillance Epidemiology and End Results Reporting (SEER) Registry.
The Washington State SEER registry includes five counties (King, Snohomish, Thurston, Kitsap, Pierce) that account for most health-plan enrollees. Women from these counties were included in this evaluation. The SEER registry uses national standards to record stage-at-diagnosis and date of diagnosis and provides a report to the health plan of the cancers diagnosed at health-plan facilities. Internal audits at the health plan show that the SEER registry captures 98% of breast cancer cases among health-plan enrollees in the five counties. The other 2% are women who receive diagnoses of breast cancers at contracted facilities but who are not identified as members of the health plan.

Component Definitions, Sample, Measures, and Analysis.
Below, we define relevant variables and describe the sample, measures, and analysis for each study component summarized in Table 1 . Variables that were used in more than one component are defined where they are first used.

View this table: [in this window] [in a new window]   Table 1 Design summary of the three-component evaluation of the effect of offering organized mammography screening 1986–1998 to an annual average of 80,799 female health-plan enrollees ages 40 years

Definitions.
"Health-plan women" included the total population of women ages 40 who were enrolled in the health plan in December of each year between 1986 and 1998. "Mammography use" occurred when a health-plan woman received a bilateral (screening or diagnostic) two-view mammogram. We used the date of documented or self-reported mammography occurrence recorded in automated files to establish whether a mammogram occurred in each calendar year.

Measure.
"Ever-use of mammography" included all self-reported or automated evidence of having had a mammogram before, and including, the year of interest (1986–1998)."Mammography-within-2-years" measured the proportion of health-plan women who had one mammogram in the previous 2 years from 1986 to 1998.

We began the evaluation of mammography diffusion in 1986 (30) . From that time forward, mammogram use was available in automated radiology records and could be supplemented by self-reported mammography use when women completed the program survey. We graphed the proportion of women, ages 40–49 and 50 years, with mammograms and assumed that women without data in a given year had not had a mammogram during that year.

Analysis.
For component 1 of this study, we showed the diffusion of mammography over time but did not conduct any statistical tests. On average, there were 33,483 women ages 40–49, and 51,951 women ages 50 in each year, but the population size ranged from 18,794 in 1983 to 39,695 in 1998 for women ages 40–49, and from 38,447 to 66,581 for women ages >50.

Component 2: Late-Stage Disease Rates
In component 2, we evaluated whether there was a declining rate of late-stage disease in health plan and surrounding-community women between 1983 and 1998. We started this analysis in 1983 to include comparison late-stage rates from a time-period before the screening program was available within the health plan.

Definitions.
We defined "late-stage disease" using the SEER categories of "regional" or "distant" disease because it was consistently available over time. "Regional disease" included invasive breast cancer that extended beyond the limits of the breast directly into surrounding organs or tissues, into regional lymph nodes, or both. "Distant disease" included invasive breast cancer that spread to parts of the body remote from the primary tumor by direct extension or by metastasis (31) . Other measures of late-stage disease, such as staging by tumor, node, and metastases (TNM stage), could not be used because they were not available over the entire evaluation time period (1983–1998).

Population.
We estimated the total population of community women for each year using the county estimates in 5-year age categories provided by the Washington State Office of Financial Management and subtracting the female age-specific health-plan population (32) . The community population included an annual average of 483,101 women (range, 395,068 in 1986 to 610,645 in 1998).

We identified all health-plan women ages 40 with invasive breast cancers diagnosed at a late-stage in a health-plan facility between January 1, 1983, and December 31, 1998, regardless of their breast cancer screening program enrollment status.

Measure.
We calculated the age-adjusted late-stage disease rate separately for health-plan and community women using the yearly population estimates. We age-adjusted the health-plan and community women rates to the 1970 SEER cancer population to be consistent with SEER policy for cancers diagnosed before 1999.

Analysis.
For component 2, we used unconditional logistic regression to examine the association between the occurrence of late-stage disease (yes/no) and time-period.

We grouped data from 1983–1998 into 2-year intervals and modeled time as a group linear variable for each age group (40–49, 50+) while adjusting for age within age group. We used four separate models, one for each population: health-plan women ages 40–49, health-plan women ages 50+, community women ages 40–49, and community women ages 50+. In two additional models, we included all women (health-plan and community) ages 40–49, or all women ages 50, and tested for differences in the occurrence of late-stage disease between health plan and the surrounding community by evaluating the main effect of population (health plan versus community). We tested whether the rate of decline differed between the health plan and the community by testing for an interaction between the main effects of the population (health plan or community) and time.

Component 3: Modeling the Odds of Late-Stage Disease
In component 3, we evaluated the odds ratio (OR) for late-stage disease in the health-plan population as a function of BCSP program enrollment and screening exposure. This component tested the ecological assumptions underlying any apparent association between the diffusion of mammography and trends in late-stage disease demonstrated in components 1 and 2. Women with late-stage disease should be less likely to have been enrolled in the program and to have received repeated mammography if the screening program enrollment and the use of mammography lead to reduced rates of late-stage disease. If screening takes place independent of the program (e.g., through primary-care referral), then we would not expect BCSP enrollment or BCSP mammograms to be associated with a reduced odds of late-stage disease, even if late-stage disease rates were falling in the population, because the falling rates could be attributed to screening outside the program.

Definitions.
"BCSP enrollment" occurred when health-plan women completed and returned the breast cancer risk-factor questionnaire. A "breast cancer screening program mammogram" was one conducted by radiologists in association with a BCSP Center visit. A "screening mammogram" was any bilateral mammogram designated as "screening" by the radiology facility. These included BCSP mammograms and those referred to radiology by a primary care physician. "Repeated screening mammography" occurred when women received two or more screening mammograms within 5 years. "Index year" was the year of breast cancer diagnosis for each case. "Early-stage breast cancer" included all invasive breast cancers recorded as local stage by SEER.

Population.
In component 3, we identified all health-plan women ages 43–79 at the time of diagnosis of an invasive breast cancer between January 1, 1995, and December 31, 1998, who had at least 5 years of enrollment before their date of diagnosis of breast cancer. We excluded women less than 43 because they did not have an opportunity to receive two or more mammograms. We also identified a random sample from the "general health-plan population" of women ages 43–79 who did not have late-stage breast cancer, and we frequency-matched them on age and length of health-plan enrollment to the late-stage cases in a ratio of 4:1. These general health-plan controls were selected irrespective of BCSP enrollment, and three had early-stage breast cancer before the index date of their matched case.

Measure.
Because a BCSP mammogram rather than program enrollment was what would avoid late-stage disease, we evaluated the two in association. We tested three key measures for their association with late-stage breast cancer: BCSP enrollment and BCSP mammography experience (no, yes+no BCSP mammogram; and yes +1 or more BCSP mammograms); total number of screening mammograms used during the 5 years before diagnosis (0–1, 2+ mammograms); and BCSP screening mammography use (0–1, 2+ BCSP mammograms). We used automated data for all variables for all cases and controls and considered the following variables in addition to mammography use: age, race, family history of breast cancer in a first- or second-degree relative, and length of health-plan enrollment. Mammography use was restricted to examinations documented in the health-plan radiology files during the 5 years before the date of diagnosis.

Analysis.
We estimated the OR for late-stage disease as a function of program enrollment, number of mammograms, and screening program mammograms by comparing the experience among women with late-stage disease and that of two separate controls: (a) all women with early-stage invasive disease; and (b) the age and length-of-enrollment-matched general health-plan population controls.

For the component 3 analysis, we compared the health-plan late-stage breast cancer cases with the two control groups on demographics, breast cancer risk factors, and mammography experience. We used descriptive statistics to compare cases with each set of controls with respect to the variables of interest (age, race, family history, length of health-plan enrollment, BCSP enrollment, and number of screens). We then used unconditional logistic regression to examine separately the effects of program enrollment and its associated BCSP screen, and number of screens in the last 5 years (0–1, 2+). All models adjusted for age at diagnosis in 5-year age categories, index year, and length of enrollment (5–9, 10–14, 15–19, 20+ years). We also tested the above models among women ages 53–79 because all women in this latter age group were eligible for reminders to schedule screening mammograms.

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Component 1: Mammography Diffusion.
By the end of 1986, 66.4% of all women ages 40 who were enrolled in the health plan had self-reported or radiology-based documentation regarding mammograms and the proportion of women with documentation grew to 89% by the end of 1998. On the basis of this documentation among all women ages 40–49, "ever-use" of mammography increased from 36.1% in 1986 to 66.6% in 1998, whereas "use-within-2-years" increased from 25.9% to 51.2% over the same time period (Fig. 1) . Among all women ages 50, ever-use went from 45.9% in 1986 to 89.1% in 1998, whereas use-within-2-years increased from 32.9% to 74.7% over the same time period.

View larger version (23K): [in this window] [in a new window]   Fig. 1. Mammograph use among health-plan women ages 40–49 and 50+ years.

View larger version (24K): [in this window] [in a new window]   Fig. 2. Rates of late-stage breast cancer among community and health-plan women ages 40–49 and 50+ years.

Component 3: Modeling the Odds of Late-stage Disease.
Table 2 shows that late-stage cases were similar to the general health-plan population controls. Of note was the slightly younger age of late-stage compared with early-stage cancers (58.4 years versus 61.8 years; P = 0.0005), and the slightly shorter length of health-plan enrollment.

Late-Stage Cases versus Early-Stage Cancer Controls.
The odds of late-stage disease was significantly reduced among BCSP enrollees compared with those who were not enrolled and was reduced more among women who had at least one BCSP screen (Table 4) . Among the cancer cases, women with two or more BCSP screens were less likely to be late-stage cancers compared with those who had less than two BCSP screens.

Models Restricted to Women Ages 53–79.
Results of the separate set of models making the same comparisons as above but restricted to women ages 53–79 are also shown in Table 4 . The results did not change our findings, although the protective effect of BCSP enrollment and screening appeared stronger.

Screening Correspondence and Exposure.
The BCSP mailed one or more reminders to schedule an examination to 64, 89, and 64%, respectively, of the late-stage, early-stage, and general health-plan population controls who had never had a mammogram but were enrolled in the program (data not in tables). Health-plan women enrolled in the BCSP were more likely to have had a mammogram [84% (957/1134)] compared with women not enrolled in the BCSP [22% (17/78)]. Women enrolled in the BCSP who did not have BCSP mammograms sometimes received them outside the program, but this occurred less frequently among women with late-stage [26% (9/34)] compared with early-stage [48% (35/73)] breast cancer, and similar to the general population controls [28% (44/158); late-stage versus early-stage, P = 0.04].

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Our findings demonstrate the challenge of evaluating the implementation of organized screening. We are evaluating progress toward the desired end point of reduced late-stage disease and evaluating whether any progress can be attributed to screening program exposure. We assume a benefit of mammography but recognize it may be small and delayed, relative to program implementation at the population level (1 , 22) . As expected, we show rising proportions of ever-screened and recently screened women among the health-plan population and a corresponding decrease in late-stage breast cancer, among women ages 50 and above. We do not see a change in the late-stage rate among women ages 40–49. The rate of late-stage cancer is significantly lower at the health plan for both age groups compared with the surrounding community, and the rates of decline do not differ from each other.

A unique strength of this evaluation is that we test the ecological assumption underlying the association between mammography diffusion and decreasing late-stage disease. We use individual-level data and two separate control groups to estimate the OR for late-stage disease among health-plan women. By doing so we demonstrate that enrolling women in organized screening and getting a BCSP mammogram is associated with a 69% reduction in the risk of late-stage disease among the cancer cases. Even more important is a 61% reduction in the OR for late-stage disease with BCSP enrollment and use of BCSP screens when estimated using the general health-plan population controls. The demonstration of reduced risk compared with disease-free controls provides the least biased estimate of the advantage of breast cancer screening program enrollment.

However, the picture is not so simple, because there is also a reduction in the odds of late-stage disease among women enrolled in the program who never receive a BCSP screening mammogram. These findings are consistent with a conclusion that program enrollment is associated with a reduced risk of late-stage disease, but it may not be because of program mammograms. It may reflect the selection bias that women who enroll in the program are most interested in screening. The data show that women enrolled in the program are getting screened, even if some are getting their mammograms outside the screening program. The data also show a point estimate consistent with reduced risk of late-stage disease among women with two or more BCSP mammograms, although the CIs around the estimate are wide (Table 4) . Although the point estimate is consistent with results from randomized trials using mortality end points, it would be a simpler story if we that knew the estimate was significantly reduced (22) .

Another ambiguity is that the declining rate of late-stage breast cancer among health-plan women ages 50 has not yet attained statistical significance. Although the target population for mammography screening is more than 80,000 women, cancers are diagnosed infrequently, and cancers are diagnosed at a late stage even more infrequently. Consequently, it is difficult to attain numbers of cases that allow tests of significance with adequate precision. However, despite the lack of significance, the odds of late-stage disease is reduced over time, similarly to the reduction of odds in the surrounding community for women ages 50, and the cancer rate is lower than in the surrounding community. Both facts suggest that the risk-based approach at the health plan is doing no harm compared with the approach taken in the community, and that both populations are showing expected progress toward a mortality reduction by achieving low rates of late-stage disease.

Although the rate of late-stage disease is falling in the surrounding community, data regarding the screening experience of individuals are not available. Without individual level data regarding screening exposure, we cannot evaluate the amount of mammography the community was using to achieve their significant decline in late-stage disease. However, community level estimates from the Behavioral Risk Factor Surveillance Survey for 1998 show that a higher proportion of community women ages 40–49 were screened within the prior 2 years (68.8%) compared with the health-plan population (51.2%) and a lower proportion (66%) of community women ages 50 have had a mammogram within 2 years compared with health-plan women (74.7%; Ref. 33 ). Self-reported mammography somewhat overestimates the proportion of those who receive a mammogram within a given time frame, but it would appear that the health plan screened a smaller proportion of younger women and reached a higher proportion of women ages 50. Although reaching a wider population is one important measure of implementation, it is also important to know how frequently women are screened. Because the community may be more likely than the BCSP to be screening annually, there could be substantial differences in the resources used to achieve the late-stage rates reported here. More should be done to link the data from tumor registries with data on population-based mammography to further evaluate the impact of mammography screening in the general United States population.

The association between BCSP enrollment and the reduced odds of late-stage disease seems like a convincing argument for encouraging program enrollment. Program enrollment leads to reminders that do not depend on a visit to a health center. The higher proportion of general-population women with a mammogram among those enrolled in the BCSP suggests that the reminders lead to mammograms, but it may also reflect the selection bias that women who are interested in mammograms are the ones who enroll in the program.

What may be more important is that this organized screening effort creates the opportunity to identify women at increased risk of late-stage disease, including those who are not enrolled in the program, and those who are enrolled but not getting mammograms. As many as 10% of the women ages 50 in the entire population had never had a mammogram and 25% had not had one within the previous 2 years. The process of enrollment in the program affords an opportunity to identify women who do not complete the process and, therefore, are at increased risk of late-stage disease as shown in this analysis. Women who do not enroll in the screening program could be approached to solicit and address their concerns.

But some women in the program are also not getting mammograms. Our results show that women without mammograms had documentation of mailed recommendations reminding them to schedule screening mammograms. However, reminders alone may not be adequate because 12% (107/903) of health-plan women ages 50 who were enrolled in BCSP had not had a mammogram in the last 5 years. Of these women, 73% (78/107) had been sent two or more reminders. Randomized trial results in this population suggest that telephone contact is a more effective approach to women who do not schedule appointments after mailed reminders (34) . However, these telephone reminders require personnel and an investment that may not be justified (35) . It seems prudent to encourage further program enrollment so that reminders are sent. Whether to invest in further recruitment efforts raises the question of who is responsible for achieving screening, women who receive reminders or the health plan that sends them?

Our finding of reductions in late-stage disease with rising mammography use are consistent with findings from the United Kingdom and Sweden who have organized programs and also use screening intervals of 2 or more years for women ages 50 (1 , 36) . These programs report reductions in late-stage disease (37) and reductions in mortality (1) ; therefore, it is reasonable to expect mortality reduction in our population as well, given adequate time. Aside from mortality, however, there is evidence that surgical morbidity is reduced when late-stage is avoided (38) . Our program results in the United States should provide reassurance that we can see progress toward a benefit when screening is implemented and reaches the population.

This study has several strengths. To our knowledge, it is the first report of population-based mammography screening and outcomes to evaluate the impact of screening during the active period of mammography diffusion in the United States. As such, it provides comprehensive population and individual-based information on mammography use and late-stage breast cancer. The recorded findings reflect the experience of an entire population and are not subject to sampling error. Furthermore, all of the cancers have been staged using SEER methodology and, as such, represent a uniform standard in breast cancer staging. We also have comprehensive mammography exposure data including self-report and actual use in our facilities. Together, these factors make this a unique opportunity to look at the impact of screening at the population level (components 1 and 2) and test whether what we see for the population makes sense at the individual level (component 3). Mammography does diffuse during the observation period, and the rate of late stage-disease drops. Component 3 suggests that the drop in late-stage disease would be explained by mammography exposure. Women enrolled in the program are more likely to have mammograms, although not necessarily in the BCSP.

Another strength is access to an entire population of cancers, careful selection of the study populations for each component, and the use of two controls when we estimated the odds of late-stage disease for individuals (component 3). We excluded women under age 43 from component 3 to allow adequate time to have two previous mammograms before the diagnosis of the cancer, but, otherwise, all women enrollees are included. We chose 1995 as the first year for inclusion of individual cases in component 3 because it is the first year that repeated screening occurred at 2-year intervals (27, 28, 29, 30) . We frequency-matched late-stage breast cancer cases and the general health-plan population on age and length of health-plan enrollment because both factors could influence the likelihood of getting mammograms.

The different controls provide different insights into the program and mammography screening effect but each has its limitation. The limitation of using the general population as a comparison group is that the risk of breast cancer is higher among women who get screened compared with those who do not, and, therefore, the incidence of breast cancer will be expected to be higher among screened women (39) . This higher breast cancer incidence (of all stages) would mask some of the effect of screening on reducing the odds of late-stage disease. Alternatively, use of the early-stage breast cancer cases as the comparison group resolves this problem, because all of those women have cancer, but the ORs for estimating the association with screening exposure could be biased toward showing a stronger than true effect if mammography leads to over-diagnosis of early-stage invasive breast cancer instead of, or as well as, a decrease in late-stage diagnosis.

Some may say that a limitation is that these results come from a managed care plan, but it is likely that similar levels of implementation would achieve similar outcomes in other populations. There is no reason to believe that breast cancer operates differently among these managed care enrollees. However, the rate of late-stage disease in the surrounding community may be higher because some members of the community do not have access to care (40) . The question these findings raise is whether an organized screening approach has advantages. One answer is yes, because it identifies women at increased risk of poor outcomes because they either do not enroll in the program, or they do not get mammograms when reminded. The question that needs to be raised is whether pursuing these women would further reduce late-stage disease. Organized screening offers that opportunity.

	Footnotes

 
Grant support: National Cancer Institute Grant CA63731.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Notes: Dr. Taplin is presently at National Cancer Institute, NIH, Division of Cancer Control and Population Sciences, Bethesda, Maryland.

Requests for reprints: Stephen H. Taplin, National Cancer Institute, 6130 Executive Boulevard, MSC 7344, EPN 4005, Bethesda, MD 20892-7344. Phone: (301) 496-8500; Fax: (301) 435-3710.

Received 7/ 8/03; revised 10/ 3/03; accepted 10/ 8/03.

	References

Top Abstract Introduction Subjects and Methods Results Discussion References

 

1. Blanks R. G., Moss S. M., McGahan C. E., Quinn M. J., Babb P. J. Effect of NHS breast screening programme on mortality from breast cancer in England and Wales, 1990–8: comparison of observed with predicted mortality. Br. Med. J., 321: 665-669, 2000.[Abstract/Free Full Text]
2. DeKoning H. J., Fracheboud J., Boer R., Verbeek A. L. M., Collette H. J. A., Hendriks J. H. C. L., Van Ineveld B. M., DeBruyn A. E., VanDer Maas P. J. Nationwide breast cancer screening in the Netherlands: support for breast cancer mortality reduction. Int. J. Cancer, 60: 777-780, 1995.[Medline]
3. Blanks R. G., Moss S. M., Wallis M. G. Monitoring and evaluating the UK national health service breast screening programme: evaluating the variation in radiological performance between individual programmes using PPV-referral diagrams. J. Med. Screen, 8: 24-28, 2001.[Abstract/Free Full Text]
4. Edwards B. K., Howe H. L., Ries L. A., Thun M. Y., Rosenberg H. M., Yanckik R., Wingo P. A., Jamal A., Feigal E. G. Annual report to the nation on the status of cancer, 1973–1999, featuring implications of age and aging on U. S. cancer burden. Cancer (Phila.), 94: 2766-2792, 2002.
5. Niederhuber J. E. Seeking calmer waters in a sea of controversy. Oncologist, 7: 172-173, 2002.[Free Full Text]
6. Begg C. B. The mammography controversy. Oncologist, 7: 174-176, 2002.[Free Full Text]
7. Mandelblatt J. S., Yabroff K. R. Effectiveness of interventions designed to increase mammography use: a meta-analysis of provider-targeted strategies. Cancer Epidemiol. Biomark. Prev., 8: 759-767, 1999.[Abstract/Free Full Text]
8. Hawley S. T., Earp J. A., O’Malley M., Ricketts T. C. The role of physician recommendation in women’s mammography use: is it a 2-stage process?. Med. Care, 38: 392-403, 2000.[CrossRef][Medline]
9. Salzmann P., Kerlikowske K., Phillips K. Cost-effectiveness of extending screening mammography guidelines to include women 40 to 49 years of age. Ann. Intern. Med., 127: 955-965, 1997.[Abstract/Free Full Text]
10. Rimer B. K. Mammography use in the U. S.: trends and the impact of intervention. Ann. Behav. Med., 16: 317-326, 1994.
11. Pignone M., Somnath S., Hoerger T., Mandelblatt J. Cost-effectiveness analyses of colorectal cancer screening: a systematic review for the U. S. preventive services task force. Ann. Intern. Med., 137: 96-104, 2002.[Abstract/Free Full Text]
12. US Preventive Services Task Force. Screening for cervical cancer DiGuiseppi C. Atkins D. Woolf S. eds. . Guide to Clinical Preventive Services: Report of the US Preventive Services Task Force, Ed. 2 105-117, Williams and Wilkins Baltimore, MD 1996.
13. Ballard-Barbash R., Klabunde C., Paci E., Broeders M., Coleman E. A., Fracheboud J., Bouchard F., Rennert G., Linos A., Shapiro S. International Breast Cancer Screening Network (IBSN). Breast cancer screening in 21 countries: delivery of services, notification of results, and outcomes ascertainment. Eur. J. Cancer Prev., 8: 417-426, 1999.[Medline]
14. Suter L. G., Nakano C. J., Elmore J. G. The personal costs and convenience of screening mammography. J. Womens Health Gend. Based Med., 11: 667-672, 2002.[Medline]
15. Pearlman D. N., Rakowski W., Ehrich B. Mammography, clinical breast exam, and Pap testing: correlates of combined screening. Am. J. Prev. Med., 12: 57-64, 1996.
16. Taplin S. H., Robles S., Kricker A., Sancho-Garnier H., Pisani P., Miller A. B. Use of breast cancer screening Vainio H. Bianchini F. eds. . Breast Cancer Screening, Volume 7: 47-86, IARC Press Lyon, France 2002.
17. Thompson R. S., Taplin S. H., McAfee T. A., Mandelson M. T., Smith A. E. Primary and secondary prevention services in clinical practice: twenty years’ experience in development, implementation, and evaluation. J. Am. Med. Assoc., 273: 1130-1135, 1995.[Abstract]
18. Breen N., Wagener D. K., Brown M. L., Davis W. W., Ballard-Barbash R. Progress in cancer screening over a decade: results of cancer screening from the 1987, 1992, and 1998 National Health Interview Surveys. J. Natl. Cancer Inst., 93: 1704-1713, 2001.[Abstract/Free Full Text]
19. Burack R. C., Gimotty P. A., George J., Stengle W., Warbasse L., Moncrease A. Promoting screening mammography in inner-city settings: a randomized controlled trial of computerized reminders as a component of a program to facilitate mammography. Med. Care, 32: 609-624, 1994.[CrossRef][Medline]
20. Solberg L. I., Kottke T. E., Conn S. A., Brekke M. L., Calomeni C. A., Conboy K. S. Delivering clinical preventive services is a systems problem. Ann. Behav. Med., 19: 271-278, 1997.[Medline]
21. Klabunde C., Bouchard F., Taplin S., Scharpantgen A., Ballard-Barbash R. Quality assurance for screening mammography: an international comparison. J. Epidemiol. Community Health, 55: 204-212, 2001.[Abstract/Free Full Text]
22. Nystrom L., Andersson I., Bjurstam N., Frisell J., Nordenskjold B., Rutqvist L. E. Long-term effects of mammography screening: updated overview of the Swedish randomised trials. Lancet, 359: 909-919, 2002.[CrossRef][Medline]
23. Blanks R. G., Moss S. M., Patrick J. Results from the UK NHS breast screening programme, 1994–1999. J. Med. Screen, 7: 195-198, 2000.[Abstract/Free Full Text]
24. Day N. E. Quantitative approaches to the evaluation of screening programs. World J. Surg., 13: 3-8, 1989.[CrossRef][Medline]
25. Day N. E. The epidemiological basis for evaluating different screening policies. IARC Sci. Publ., 76: 199-212, 1986.
26. Prorok P. C. Evaluation of screening programs for the early detection of cancer Cornell R. G. eds. . Statistical Methods for Cancer Studies, 267-328, Marcel Dekker New York 1984.
27. Taplin S. H., Thompson R. S., Schnitzer F., Anderman C., Immanuel V. Revisions in the risk-based Breast Cancer Screening Program at Group Health Cooperative. Cancer (Phila.), 66: 812-818, 1990.
28. Carter A. P., Thompson R. S., Bourdeau R. V., Andenes J., Mustin H., Straley H. A clinically effective breast cancer screening program can be cost-effective, too. Prev. Med., 16: 19-34, 1987.[CrossRef][Medline]
29. Thompson R. S., Taplin S. H., Carter A. P., Schnitzer F. Cost effectiveness in program delivery. Cancer (Phila.), 64: 2682-2689, 1989.
30. Taplin S. H., Mandelson M. T., Anderman C., White E., Thompson R. S., Timlin D., Wagner E. H. Mammography diffusion and trends in late-stage breast cancer: evaluating outcomes in a population. Cancer Epidemiol. Biomark. Prev., 6: 625-631, 1997.[Abstract]
31. Ries L. A. G., Kosary C. L., Hankey B. F., Miller B. A., Harras A., Edwards B. K. . SEER Cancer Statistics Review, 1973–1994, NIH Pub. No. 97-2789, 12 National Cancer Institute Bethesda. MD 1997.
32. Washington State Office of Financial Management. Intercensal and postcensal estimates of county population by age and sex: 1980–2002, November 2002. URL http://www.ofm.wa.gov/pop/coagemf/index.htm (Accessed June 23, 2003).
33. Washington State Department of Health. Center for Health Statistics Behavioral Risk Factor Surveillance Survey. URL http://www.doh.wa.gov/EHSPHL/CHS/CHS-Data/brfss/brfss_homepage.htm (Accessed November 20, 2002).^.
34. Taplin S. H., Barlow W., Ludman E., MacLehose R., Meyer D., Seger D., Herta D., Chin R., Curry S. Testing reminder and motivational telephone calls to increase screening mammography. J. Natl. Cancer Inst. (Bethesda), 92: 233-242, 2000.[Abstract/Free Full Text]
35. Fishman P., Taplin S., Meyer D., Barlow W. Cost-effectiveness of strategies to enhance mammography use. Eff. Clin. Pract., 5: 213-220, 2000.
36. Duffy S. W., Tabar L., Chen H. H., Holmqvist M., Yen M. F., Abdsalah S., Epstein B., Frodis E., Ljungberg E., Melander C. H., Sundbom A., Tholin M., Wiege M., Akerlund A., Wu H. M., Tung T. S., Chiu Y. H., Chiu C. P., Huang C. C., Smith R. A., Rosen M., Stenbeck M., Holmberg L. The impact of organized mammography service screening on breast carcinoma mortality in seven Swedish counties. Cancer (Phila.), 95: 458-469, 2002.
37. McCann J., Duffy S., Day N. East Anglian breast screening programme. Predicted long-term mortality reduction associated with the second round of breast screening in East Anglia. Br. J. Cancer, 84: 423-428, 2000.
38. Freedman G. M., Anderson P. R., Goldstein L. J., Hanlon A. L., Cianfrocca M. E., Millenson M. M., von Mehren M., Torosian M. H., Boraas M. C., Nicolaou N., Patchefsky A. S., Evers K. Routine mammography is associated with earlier stage disease and greater eligibility for breast conservation in breast carcinoma patients age 40 years and older. Cancer (Phila.), 98: 918-925, 2003.
39. Taplin S. H., Anderman C., Grothaus L. Breast cancer risk and participation in mammographic screening. Am. J. Public Health, 79: 1494-1498, 1989.[Abstract/Free Full Text]
40. Lawson H. W., Henson R., Bobo J. K., Kaeser M. K. Implementing recommendations for the early detection of breast and cervical cancer among low-income women. Morb. Mortal. Wkly. Rep., 49: 35-55, 2000.[Medline]

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