ARTICLE

Reason for Late-Stage Breast Cancer: Absence of Screening or Detection, or Breakdown in Follow-up?

Stephen H. Taplin, Laura Ichikawa, Marianne Ulcickas Yood, M. Michele Manos, Ann M. Geiger, Sheila Weinmann, Joyce Gilbert, Judy Mouchawar, Wendy A. Leyden, Robin Altaras, Robert K. Beverly, Deborah Casso, Emily Oakes Westbrook, Kimberly Bischoff, Jane G. Zapka, William E. Barlow

Affiliations of authors: Group Health Cooperative, Seattle, WA (SHT, LI, RA, RKB, DC, EOW); Henry Ford Health System, Detroit, MI (MUY); Kaiser Permanente Northern California, Oakland (MMM, WAL); Kaiser Permanente Southern California, Pasadena (AMG); Kaiser Permanente Northwest, Portland, OR (SW); Kaiser Permanente Hawaii, Honolulu (JG); Kaiser Permanente Colorado, Denver (JM, KB); University of Massachusetts Medical School, Worcester (JGZ); Cancer Research and Biostatistics, Seattle, WA (WEB)

Correspondence to: Stephen H. Taplin MD, MPH, Applied Research Program, National Cancer Institute, 9000 Rockville Pike, MSC 7344, EPN 4005, Bethesda, MD 20892-7344 (e-mail: taplins{at}mail.nih.gov)


    ABSTRACT
 Top
 Notes
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Background: Mammography screening increases the detection of early-stage breast cancers. Therefore, implementing screening should reduce the percentage of women who are diagnosed with late-stage disease. However, despite high national mammography screening rates, late-stage breast cancers still occur, possibly because of failures in screening implementation. Methods: Using data from seven health care plans that included 1.5 million women aged 50 years or older, we conducted retrospective reviews of chart and automated data for 3 years before 1995–1999 diagnoses of late-stage (metastatic and/or tumor size ≥3 cm; case subjects, n = 1347) and early-stage breast cancers (control subjects, n = 1347). We categorized the earliest screening mammogram during the period 13–36 months before diagnosis as none (absence of screening), negative (absence of detection), or positive (potential breakdown in follow-up). We compared the proportion of case and control subjects in each category of screening implementation and estimated the likelihood (odds ratio [OR] with 95% confidence intervals [CIs]) of late-stage breast cancer. We also evaluated demographic characteristics associated with absence of screening in women with late-stage disease. All statistical tests were two-sided. Results: Absence of screening, absence of detection, and potential breakdown in follow-up were distributed differently among case (52.1%, 39.5%, and 8.4%, respectively) and control subjects (34.4%, 56.9%, and 8.8%, respectively) (P = .03). Among all women, the odds of having late-stage cancer were higher among women with an absence of screening (OR = 2.17, 95% CI = 1.84 to 2.56; P<.001). Among case patients, women were more likely to be in the absence-of-screening group if they were aged 75 years or older (OR = 2.77, 95% CI = 2.10 to 3.65), unmarried (OR = 1.78, 95% CI = 1.41 to 2.24), or without a family history of breast cancer (OR = 1.84, 95% CI = 1.45 to 2.34). A higher proportion of women from census blocks with less education (58.5% versus 49.4%; P = .003) or lower median annual income (54.4% versus 42.9%; P = .004) were in the absence-of-screening category compared with the proportion for the other two categories combined. Conclusions: To reduce late-stage breast cancer occurrence, reaching unscreened women, including elderly, unmarried, low-income, and less educated women, should be made a top priority for screening implementation.



    INTRODUCTION
 Top
 Notes
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Reducing breast cancer mortality has been a public health priority since the mid-1980s, but evidence of success in achieving this goal has appeared only recently (1,2). Despite controversy over the validity of some study findings, there is a consensus that results from randomized trials have demonstrated a 30%–40% reduction in breast cancer mortality when mammography screening occurs regularly among women aged 50–64 years (37). During the 1980s, a national goal was set that, by 2000, at least 60% of women aged 50 years or older should have had a mammogram within the past 2 years (8). Although the national goal for screening was met by 1993, breast cancer mortality began to show a statistically significant decline only in the late 1990s (9,10).

One reason for the delay in mortality reduction may be that increasing the proportion of women who obtain screening mammography is a necessary but not sufficient step toward full implementation of the screening process. Effective implementation of the screening process involves several critical components: screening (obtaining the mammogram), detection (finding a cancer when it is present), and follow-up (evaluating women with positive mammograms) (11). Improving use of screening mammography has different implications for people conducting research or allocating resources of a health care system than it does for those improving the quality of the test or those creating systems to help coordinate the health care process for women with abnormal results (1215). Setting priorities for screening improvements and research requires knowing where the screening implementation process fails.

Few women in a regularly screened population should be diagnosed with late-stage cancer because, in theory, screening should identify cancers before they progress to late stage. The occurrence of late-stage cancers represents an important marker for potential breakdown in the screening implementation process because late-stage cancers appear before changes in mortality would be evident in a population (7,1619). In this study, we used data from seven organized health care plans in which women have access to screening mammography. In 1999, at the start of this study, 71%–81% of women in these seven organized health care plans had a mammogram within the previous 2 years, but late-stage breast cancers were still diagnosed, and we wanted to understand why (20).

In this study, we sought to establish where implementation of the screening process breaks down and where changes in care would have the greatest impact in avoiding late-stage breast cancer and its associated morbidity and mortality. To achieve the study goal, we compared the proportions of women with late-stage and early-stage breast cancer in each of the three implementation steps (screening, detection, and follow-up). In addition, we evaluated whether age, race, Hispanic ethnicity, and health care experience were associated with failure at particular steps in the screening implementation process. We specifically chose comparisons between late-stage and early-stage cancers to evaluate all breakdowns in implementation between two sets of women with cancer because only these women traverse the entire screening and diagnostic process. This study is therefore a study of mammography implementation, not mammogram efficacy.


    METHODS
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 Notes
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Study Setting, Population, and Sample

We conducted this study among seven health care plans participating in the Cancer Research Network. The Cancer Research Network is working to create an infrastructure to study cancer by using clinical resources within 11 health care plans around the United States. Seven of the integrated health care plans were involved in this study: Kaiser Permanente at five sites (Hawaii, Northern California, Southern California, Colorado, and the Northwest [Oregon]), Henry Ford Health System (Michigan), and Group Health Cooperative (Washington State). These comprehensive plans serve approximately 8.2 million people nationwide, including 1.5 million women aged 50 years or older, and have a full complement of primary care and specialty providers that deliver most services through their own facilities. In addition, these seven plans have access to computerized tumor registries, automated health care encounter data, and comprehensive paper medical records, and they offer screening mammography at no or minimal additional cost to women. The study was reviewed and approved by the research committees and institutional review boards responsible for each institution.

From the tumor registries, we identified women aged 50 years or older who were diagnosed with invasive breast cancer from 1995 through 1999. For this study, we excluded women who had a previous breast cancer diagnosis or who had been enrolled in their health care plan for less than 33 of the 36 months before their diagnosis.

We assigned women to one of two groups based on the stage of their breast cancer at the time of diagnosis. Women with late-stage disease were considered potential case subjects, and women with early-stage disease were considered potential control subjects. We defined late-stage breast cancers as those 3 cm or greater in diameter and/or with evidence of metastases at the time of diagnosis (tumor–node–metastasis stage IV (21), Surveillance, Epidemiology, and End Results (SEER1) Program summary stage 7 [distant or systemic disease, (22)] and all other breast cancers as early-stage cancers. We chose our measures of late-stage disease on the basis of evidence that the incidence of large tumors declines as the proportion of women with a mammogram increases and that tumor size and metastases are associated with poor prognosis (18,19,23).

We included all women with late-stage breast cancer from five study sites and approximately a 50% random sample from two sites where there were more cases than needed. We matched case subjects to control subjects (1:1) by health care plan, age within 1 year, and date of diagnosis within 6 months. If no match existed using these criteria, we relaxed the age criterion to be within 5 years. If still no match was found using the relaxed age criterion, we relaxed the date of diagnosis criterion by 3-month intervals to up to 1 year.

From all seven sites, we identified 1503 eligible case subjects with late-stage breast cancer and their control subjects with early-stage breast cancer. Among all eligible case subjects (n = 1503), we excluded 156 for the following reasons: breast cancer could not be verified as the primary cancer (n = 4), late-stage disease could not be confirmed (n = 30), care was provided outside the health plan for the entire audit period (n = 2), chart was unavailable (n = 61), enrollment criteria were not met (n = 9), the woman had a prior breast cancer (n = 43), the matched control was found to be ineligible and replacement did not occur (n = 5), and other/unknown reasons (n = 2). Across all seven sites, these exclusions left 1347 case and control subjects. We matched all but 198 case and control subjects within our criteria. These 198 case and control subjects could not be matched by age (n = 44), enrollment (n = 68), or both age and enrollment (n = 86) matching criteria. Although these 198 pairs did not meet our matching criteria, after considering the effect of their exclusion, we retained them in the analysis and controlled for the matching characteristics in the regression, as noted below.

Data Collection

We collected data on the 3 years (audit period) preceding the date of breast cancer diagnosis (time zero). This time frame was divided into two periods: 1) a diagnostic period, defined as time zero through 12 months before diagnosis and 2) a prediagnostic period, defined as the time 13 through 36 months before diagnosis. These distinctions were made under the premise that the prediagnostic period is the time during which improvement in screening implementation processes could potentially change the clinical outcome. We collected data from two sources: 1) automated databases, including tumor registries, health care plan membership, census, and encounter data, and 2) paper medical records. We extracted information from automated databases to identify the following variables: age, ethnicity, race, length of enrollment in health care plan, date of breast cancer diagnosis, breast cancer histology, marital status, and geocode on census block group at the time of diagnosis.

We abstracted medical records by using standardized forms designed to collect information on all breast-related visits during the entire audit period. We defined a breast-related visit as one associated with a documented breast symptom such as a lump or pain, a breast evaluation, or a breast procedure, including clinical breast examination, mammogram, biopsy, or ultrasound. We abstracted information that summarized breast-related health care and history, reasons for health care visits, use of other preventive services, and specialty care. The standardized form and the associated data manual are available at http://crn.cancer.gov (last accessed: August 23, 2004).

Definitions

Mammograms. An index mammogram was the earliest screening mammogram in the prediagnostic period. A screening mammogram was one with an indication for screening that used bilateral routine views. A diagnostic mammogram was one performed in symptomatic women and/or with an indication of a diagnostic exam. For this study, we considered the interpretation of mammograms as positive or negative. A positive interpretation included the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) assessments 0, 3, 4, or 5 (24) or any of the following events consistent with the BI-RADS lexicon in use in 1998: 1) additional imaging recommended or done within 2 weeks of an index screen, 2) immediate evaluation recommended by the radiologist, or 3) short-term follow-up recommended by the radiologist. If no assessment or recommendation was recorded (n = 88 of 1529), any findings other than "normal/negative" were considered a positive interpretation. All other mammograms were classified as negative interpretations.

Clinical breast examination. A screening clinical breast examination (CBE) was one performed in an asymptomatic woman during a complete physical or woman’s health visit. We considered two types of nonscreening CBE: a symptomatic CBE was one performed in a woman with a breast symptom, and an opportunistic CBE was one performed in a woman without a breast symptom at the time of a visit for chronic care or some other concern. Interpretation of the CBE was classified according to the provider’s documented conclusion and recommendation, and if neither was recorded, we used evidence of a relevant clinical finding. A positive CBE was one in which the provider concluded it was suspicious or recommended or performed an additional procedure (e.g., immediate mammogram, fine-needle aspiration, ultrasound, or surgical referral). A negative CBE was one in which none of the above were true.

Other breast issues. A preexisting breast condition included any charted information recorded during the audit period that suggested there was a breast-related problem (e.g., persistent symptoms, abnormal mammogram) from before the audit period. Refusal of breast-related care included any chart notation made during the audit period indicating that the patient refused a breast-related procedure, such as a mammogram, biopsy, or CBE.

Classification of Breakdowns in the Screening Implementation Process

We categorized breakdowns in care during the prediagnostic period into one of three mutually exclusive categories: 1) absence of screening, if a woman had no screening mammogram; 2) absence of detection, if the interpretation of the earliest screening mammogram during prediagnostic period was negative; and 3) potential breakdown during follow-up, if the interpretation of the earliest screening mammogram during the prediagnostic period was positive but the diagnosis of breast cancer occurred more than 1 year later. We refer to the breakdown in follow-up as a "potential breakdown" because we did not evaluate the details of this care, and some may be entirely appropriate.

Classification of Method of Diagnosis

We classified the method of diagnosis by identifying the earliest positive CBE or mammogram that occurred within 90 days of a positive diagnostic workup or the cancer diagnosis. To ensure that it was the earliest test, no other positive test or evaluation could precede the CBE or mammogram within 90 days. For example, if a diagnostic mammogram occurred 90 days before the diagnosis but a positive screening CBE occurred less than 90 days before the mammogram, we classified the breast cancer as detected by screening CBE. If both the CBE and mammogram occurred on the same day, the diagnosis was attributed to the mammogram.

Data Quality

All abstractors (n = 16) received rigorous training by the same group of study personnel. In addition, we reaudited 5% of medical records (or a maximum of 35 medical records for larger sites), selected at random by a second abstractor at each site to ensure consistency and reproducibility. A set of 14 vignettes including 170 variables from medical records across the seven sites was also compiled for auditing by all the abstractors using the study data collection instrument. The agreement between the responses of medical records abstractors, the principal investigator, and the project coordinator was 94% for the variables required for categorization into one of the screening implementation breakdown groups.

Data Analysis

We used 1:1 matching to construct groups of women with late-stage and early-stage breast cancers. We made comparisons between the two groups by using conditional logistic regression for matched pairs. The models included age and year of diagnosis because we could not create perfect matches on these criteria for all case and control subjects. We also examined variables of interest across the three breakdown categories among case subjects only. For this analysis of case subjects, we used the Cochran–Mantel–Haenszel statistic to conduct a chi-square test, controlling for study site. We tested for a general association and did not assume any ordinal relationship for either covariates or the breakdown categories. Unconditional logistic regression was also used to examine the association between absence of screening and variables of interest among the case subjects, after controlling for study site. One study site applied the matching algorithm successfully to only 45% of its subjects and could not complete the audit for approximately 100 identified cases. Therefore, we repeated the analysis and excluded either the entire site or only the unmatched pairs from the site. Exclusion of this study site’s unmatched case and control subjects decreased the proportion of case and control subjects in the absence-of-screening category by 0.7% and 1.7%, respectively, and increased the proportion of case and control subjects in the absence-of-detection category by 0.7% and 1.7%, respectively. We present the analysis with all data included because the conclusions were unchanged by the exclusion of data from this single site. All analyses were conducted using the SAS/STAT user’s guide, version 8 (SAS Institute, Cary, NC). All statistical tests were two-sided.


    RESULTS
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 Notes
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
From four sites that recorded the total number of invasive cases (n = 8153), 17.6% (1431) met our criteria for being late stage. Among all sites after matching and exclusions, we had 1347 women with late-stage and 1347 women with early-stage breast cancers. Among the late-stage cases, the number per study site varied from 58 to 141 among those sites in which we included all cases, and 344 to 484 for the two sites in which we sampled cases.

The study population characteristics are shown in Table 1. As expected, matching case and control subjects resulted in similar ages and in median length of enrollment during (36 months) and before (156 months) the audit period. Among both case and control subjects, 52% were aged 50–64 years, 25% were aged 65–74 years, and 23% were aged 75 years or older. There were no statistically significant differences between case and control subjects in terms of Hispanic origin, race, marital status, family history of breast cancer, median household income, or probability of being from a census block with more than 50% of individuals with a college-level-or-higher education (Table 1).


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Table 1. Population characteristics

 
The proportion of women in each implementation breakdown category among women with late-stage and early-stage breast cancer differed among case and control subjects (Table 2). An analysis of the distribution of breakdown categories across the study sites showed that it differed statistically significantly from chance (P<.001). Among the sites, the proportion of all subjects in each breakdown category ranged from 30% to 52% in the absence-of-screening category, 37% to 59% in the absence-of-detection category, and 6% to 14% in the potential-breakdown-in-follow-up category. The absence-of-screening category included a higher proportion of case subjects than control subjects (52.1% versus 34.4%; P<.001). Potential breakdown during follow-up accounted for a small proportion of women with late-stage (8.4%) or early-stage (8.8%) disease. Compared with women with early-stage disease, a smaller proportion of women with late-stage disease had any screening CBE prior to or on the same day of a screening mammogram in the prediagnostic period (27.9% versus 40.9%; P<.001). A smaller proportion of women with late-stage disease than with early-stage disease were diagnosed by a screening mammogram (16.6% versus 42.7%; P = .001). Case and control subjects were similar with respect to frequency of breast biopsy and preexisting conditions but differed in two areas of care. First, women who were in the absence-of-screening category had higher odds of having late-stage disease than women who were in the other two categories (i.e., had a screening mammogram) (OR = 2.17, 95% CI = 1.84 to 2.56; P<.001) (Table 3). Second, women who refused breast cancer care prior to the prediagnostic period had higher odds of having late-stage disease (OR = 3.16, 95% CI = 2.11 to 4.73) than women who did not refuse care.


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Table 2. Breakdowns in screening implementation and other breast-related medical experience among women with late- and early-stage breast cancers

 

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Table 3. Odds of late-stage among women with early-stage and late-stage breast cancer*

 
We examined the association between demographic characteristics and the categories of breakdown in screening implementation among women with late-stage breast cancer (Table 4). Women aged 75 years or older were more likely to be in the absence-of-screening category than younger women (70.6% versus 46.5%; OR = 2.77, 95% CI = 2.10 to 3.65) (Table 5). Unmarried (single, separated, widowed, or divorced) women had higher odds of being in the absence-of-screening category than married women (60.3% versus 46.1%; OR = 1.78, 95% CI = 1.41 to 2.24). Women without a family history of breast cancer had higher odds of being in the absence-of-screening group (56.3% versus 42.4%; OR = 1.84, 95% CI = 1.45 to 2.34) than women with a family history of breast cancer. Comparing the proportion of women with late-stage disease in the absence-of-screening category with those in both other categories by education (living in census blocks with less than a 50% likelihood of college education versus a 50% or greater likelihood) or annual income (living in census blocks with median annual income of less than $75 000 versus $75 000 or greater), we found a higher proportion in the absence-of-screening group from census blocks with lower likelihood of college education (58.5% versus 49.4%; P = .003) or had a median annual income of less than $75 000 (54.4% versus 42.9%; P = .004). The distribution across all breakdown categories did not differ by racial categories or ethnicity when considered independently. All Hispanic women (n = 73) were identified by SEER as white. After we combined race and ethnicity into a single variable (white Hispanic; white, non-Hispanic; black; Asian/Pacific Islander; and other/unknown), the proportions of women in each breakdown category differed across the combined racial groups (P = .02), with 63% of white Hispanic women in the absence-of-screening group. Decreases in the proportion of women in the absence-of-screening category resulted in comparable increases in the proportion of each racial group in absence-of-detection category (data not shown).


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Table 4. Patient characteristics among late-stage case patients across breakdown categories

 

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Table 5. Odds of absence of screening among women with late-stage breast cancer*

 
We also evaluated the association between breast care history and screening implementation breakdown categories among women with late-stage breast cancer (Table 5). Women with a documented abnormal breast condition before the study period or those with a prior breast biopsy (OR = 0.76, 95% CI = 0.59 to 0.97; OR = 0.75, 95% CI = 0.56 to 1.01, respectively) had reduced odds of being in the absence-of-screening category compared with the respective groups of women without those characteristics. Women with a documented refusal of care before the study period had greatly increased odds of being in the absence-of-screening group (OR = 7.07, 95% CI = 3.95 to 12.66) than women who had not refused care.

Table 6 shows the method of diagnosis and American Joint Committee on Cancer (AJCC) stage of the cancers in each of the breakdown categories for women with late-stage disease. Some women (11%) in the absence-of-screening group were eventually diagnosed by screening mammogram. Women in the absence-of-screening group had higher odds of having later-stage disease (AJCC stage III or IV) than women in the other two breakdown categories (OR = 1.73, 95% CI = 1.36 to 2.19). Women without detection during the prediagnostic period had the lowest proportion of cases in the latest stages.


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Table 6. Method of diagnosis and stage distributions within breakdown categories among late-stage subjects

 

    DISCUSSION
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 Notes
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
This study is the first, to our knowledge, among women aged 50 years or older that describes the proportion of women with late-stage breast cancer associated with an absence of screening, an absence of detection, and potential breakdown in follow-up, and the first to compare the proportions with the distribution among women with early-stage disease. We found that women in the absence-of-screening category had higher odds of having late-stage disease, as did women who refused prior care or did not have a screening mammogram during the prediagnostic period. Approximately half the women with late-stage disease were unscreened during the prediagnostic period, and a large proportion of case subjects were undetected at their earliest mammography screen in that period. A higher proportion of older women and women from neighborhoods with lower income or less probability of college education were in the absence-of-screening category.

Because not being screened accounted for the highest proportion of late-stage cancers, reaching and screening women aged 50 years or older who have not had a mammogram within the last 2 years should be the top implementation priority among those seeking to reduce the impact of breast cancer. Although screening among women enrolled in these seven health care plans has exceeded the national screening goal, approximately 18% of all invasive breast cancers diagnosed are late-stage. The results show that even though some women were not screened in the prediagnostic period, some were eventually diagnosed by mammography screening; thus, these women were amenable to screening and might have been reached earlier.

Although chart, mail and telephone reminders, and other strategies to promote mammography screening among women are effective (14,15), the challenge is to implement these proven promotion strategies. Achieving implementation may mean justifying the resources required for implementation on a population scale and demonstrating that promotion strategies have an impact on screening rates and mortality reduction. We have shown that 18% of invasive cancers in our population were late stage. Changes in care that reduced that proportion among the more than 12 000 women with invasive breast cancer diagnosed every 5 years among just these health care plans could directly affect the lives of more than 2000 women. Women who have not been screened may differ from the general population, so the additional mortality reduction afforded by recruitment of these unscreened women cannot be simply extended from published results of the mammography screening trials. More work is needed to estimate the costs and additional mortality reduction afforded by screening promotion. Two other studies (25,26) have evaluated women with late-stage breast cancer and found proportions of late-stage cancers among unscreened women that were similar to ours. One 1993 study, in Pennsylvania, found that women aged 50 years or older who had been diagnosed with regional or distant disease or died from breast cancer were less likely to have been screened with mammography than all other women diagnosed with invasive breast cancer in that state (57.7% versus 42.1%; OR = 2.3; 95% CI = 1.3 to 4.3) (25). A second study, of women aged 42–49 years, showed that 52% of women diagnosed with AJCC stages II–IV breast cancer had not had a mammogram within 24 months (26). These proportions are remarkably similar to those reported in our study, although they include screening exposures within a year of diagnosis. The proportion of our population with late-stage disease without screening would have been reduced from 52% to 41% if we had included women screened during the diagnostic period. However, the screening mammogram that detects a late-stage breast cancer will not change its natural history. We need to identify an earlier point in the natural history of the disease to evaluate what might have happened to avoid becoming late stage. We believe our estimate more accurately reflects the proportion of women who could achieve better outcomes if changes in screening recruitment occurred. Women aged 75 years and older represent a large proportion of the women diagnosed with late-stage breast cancer in this study, and we found that they were more likely to be in the absence-of-screening category. Results from analyses of the increased risk of death among unscreened women aged 67–85 years suggest that mammography may well benefit women aged 75–85 years without competing morbidities (27). However, the implications of the absence of screening for mortality reduction are not clear because randomized trial data testing the benefit of screening among older women is limited to those aged 65–74 years (28,29). Of note is the finding that more women with early-stage breast cancer than women with late-stage disease had a screening CBE. The role of screening CBE in reducing breast cancer mortality is being questioned by clinicians and health care planners because it has not been demonstrated to reduce mortality (6,30,31). Our study does not include the appropriate general-population control group to evaluate CBE effectiveness, and there are many permutations of CBE and mammography in an observational study. Isolating the exact CBE exposure and estimating its effect on late-stage disease is beyond the scope of this analysis. More work is needed to understand the role of screening CBE as a direct means of screening or as a means to the referral for mammography.

Although the priority for health care change should be to reach unscreened women, research priorities for cancer screening should concentrate on improving breast cancer detection. Health care providers and health plans should also focus on detection, because problems in detection account for 40% of the late-stage cases. One possible way to improve breast cancer detection is to increase mammography sensitivity, which would involve examining and improving the screening interpretation process. Further evaluation is needed to determine whether the feedback to radiologists about their interpretive performance required by the Mammography Quality Standards Act or computer-assisted reading or digital mammography results in improved detection (3234). Other possible ways to improve detection that need further evaluation include biologic markers for screening and the use of new imaging technologies (3537).

Although we believe that priority should be given to reaching unscreened women and improving breast cancer detection, we note that there are also opportunities for improvement in the several steps of care that follow abnormal mammograms (Fig. 1). Follow-up of abnormal mammograms is a quality-of-care issue that appears to account for a small proportion of the late-stage cancers among women enrolled in these health plans (38). Follow-up may be a bigger problem in other populations, in which 25% of women with positive screening tests may not receive additional testing (39). Understanding the care provided to women in the potential-breakdown-in-follow-up category in this study may help identify opportunities for improvement, but specific problems in the follow-up process need to be clarified, including issues of communication that are critical to the transitions between implementation steps (40,41).



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Fig. 1. Classification of potential breakdowns in the screening implementation process.

 
Our study has several limitations. First, it used chart audit data and thus faces all the inherent limitations of observational research. It is possible that some of the women were screened outside of the integrated care plans, that our abstractions of the mammogram or CBE data did not capture the nuances of practice, or that our case selection was biased in some way. These challenges of retrospective data collection from charts could not be avoided, although we found high levels of auditor agreement. Second, we do not know the characteristics of the case subjects who were not included in the sample from two sites. Thus, we cannot verify that our sample is representative of all case subjects in those sites, although our conclusions were unaffected by excluding the sites for which we had concerns about biased sampling. Third, we estimated the overall proportion of women with invasive cancers in our entire target population by using data from just four of the seven sites. We have no reason to believe that the proportion is any lower across the other sites, but we cannot say that with certainty. Fourth, although we chose an appropriate control group for this study, the control group does limit our ability to estimate the risk of late-stage breast cancer overall, the frequency of some of the important exposures, and patient characteristics in the general population. This study did not include a general-population control group because our goal was to evaluate screening implementation, not mammography efficacy. Instead, we used women with early-stage disease as a comparison group. We chose this group because screening studies have shown that mortality reductions occur when mammography is offered at intervals of 1 to 3 years (42,43), and therefore, in our study in which both case and control subjects had cancer, both groups had the opportunity to experience breakdowns in the care process.

This study also raises questions that will need closer evaluation in other studies. These questions include clarifying the role of CBE in cancer detection, the influence of prior biopsies on later evaluations, and the proportion of visible cancers that were missed among women in the absence-of-detection category. The answers to these questions could improve screening implementation.

Our study has several strengths. First, we used data from a diverse set of integrated health care plans with multiple facilities serving 1.5 million women aged 50 years and older. Given the policies and practices of these health care plans, these findings represent what is true under the best of circumstances; i.e., policies are stated, in-reach and outreach reminders exist, follow-up care is available within the same set of providers, and there are no major cost disincentives to women seeking care (44). Second, given that our results are comparable to those in other studies (27,28), our findings highlight the importance of placing priority on reaching women without recent screening, regardless of the health care setting. Work to promote quality assurance practices that improve detection may also be important, but more research on how to do that is needed.

In summary, among a representative sample of women with late-stage breast cancer and access to health care, we identified the proportion of women who were without screening mammography (52.1%), who had screening but negative first examinations (39.5%), or who had potential breakdowns in the follow-up of a first positive examination (8.4%). This distribution provides a guide for setting priorities for implementation and research in breast cancer screening. Absence of screening was associated with a markedly increased risk of late-stage disease among women with invasive breast cancer. Although breakdowns during the follow-up of women with positive screening examinations are serious, this breakdown accounted for a small proportion of late-stage cancers. To further reduce late-stage cancers, priority should be given to promoting screening among those women without a mammogram within 2 years and improving breast cancer detection at the time of screening. Top priority, however, should be given to reaching unscreened women, especially those who are likely to be older, to have a low annual income, and to have less education, even in organized health plans.


    NOTES
 Top
 Notes
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
1 Editor’s note: SEER is a set of geographically defined, population-based, central cancer registries in the United States, operated by local nonprofit organizations under contract to the National Cancer Institute (NCI). Registry data are submitted electronically without personal identifiers to the NCI on a biannual basis, and the NCI makes the data available to the public for scientific research. Back

We thank the DETECT Study team, who worked through many years, phone calls, charts, and complexities of their systems to help us better understand screening implementation: Sarah Parkhurst (GHC); Noelle Blick, Rowena Allison, Reggie Jackson, Barbara Rowe (KPNC); Carmen N. West (KPSC); Weiming Hu, Deborah Reck, Jill Mesa (KPNW); Denise S. Williams, Mark M. Schmidt (KPH); Karen Wells, Susan McGuinness (deceased), Lisa May, Patricia Baker, Cheryl Spoutz (HFHS); Jennifer Ellis (KPCO). A special thanks to Susan Bennett for her work to track this publication and complete the manuscript preparation.

This work was done as part of the Cancer Research Network (CA79689) and Breast Cancer Surveillance Consortium (CA 63731). S. H. Taplin’s present affiliation is the National Cancer Institute.


    REFERENCES
 Top
 Notes
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 

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Manuscript received April 5, 2004; revised July 14, 2004; accepted August 18, 2004.


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