Our analyses show that breast cancer survival varied not only across the 5 SEER programs but also within 2 of the 5 SEER programs, namely, in Detroit and Atlanta. In both areas, separate clusters of shorter-than-expected survival and longer-than-expected survival were identified. In each of these 2 SEER programs, census-tract poverty rate and stage at diagnosis played a major role in explaining the presence of these clusters. Race also played a mediating role in Atlanta. In relation to these factors, other patient characteristics (age, marital status, and comorbidity), treatment factors, other tumor factors (grade, histology, estrogen receptor status, and metastases), utilization of medical care, and mammography use explained very little of the variance in survival.
Because of the importance of stage at diagnosis in explaining the geographic variation in breast cancer survival, increasing screening mammography use and appropriate diagnostic follow-up will likely improve survival in the clusters of shorter-than-expected survival. Identification of areas of shorter-than-expected survival allows for geographically targeted efforts to increase mammography use and to improve delays in diagnostic follow-up.
Much has been written about the racial disparity in breast cancer survival that exists and which has been increasing since the 1980s (43
). Although differences in treatment variation have been reported to account for racial disparities (45
), treatment variation did not play a role in survival among African-American women who lived in the Atlanta cluster of shorter-than-expected survival. Additionally, insurance status as an explanation for racial disparities (45
) is unlikely to have played a role in our study because all women had Medicare insurance. The literature suggests that racial disparities could be reduced by patient-, provider-, and health system-level interventions (44
). Without additional studies, it is unclear which interventions should be implemented among African Americans in the Atlanta cluster of shorter-than-expected survival.
There are several mechanisms by which the poverty rate could explain the geographic variation in breast cancer survival. Improving the type of recommended treatment in areas of higher poverty would not be expected to negate the differences between areas of shorter versus average length of survival. However, our data did not capture the extent of the treatment received. Although the SEER–Medicare data did not contain adjuvant endocrine treatment data, it is unlikely that endocrine treatment would mediate the observed association because other types of treatment were not mediators. Additionally, utilization of medical care or surveillance mammography use after diagnosis in areas of higher poverty would not be expected to negate the differences between areas of shorter versus average length of survival. Neither would patient and tumor characteristics beyond stage at diagnosis account for the differences in length of survival between these areas.
Persons who lived in areas with increased poverty rates may have reduced access to local resources, such as grocery stores selling fresh fruits and vegetables (46
), which may lead to increased consumption of dietary fat intake, which, in turn, is associated with reduced survival (47
). Residents of these areas also may experience increased psychosocial stress, which is associated with reduced survival (48
). Persons who live in high poverty areas also may be more likely to seek treatment for their breast cancer at hospitals with fewer annual numbers of breast cancer surgeries, which lower numbers have been associated with adverse breast cancer outcomes (50
). Additional studies are needed to determine why breast cancer survivors living in high-poverty census tracts in the clusters of shorter-than-expected survival have reduced survival.
Our study was limited to women participating in the Medicare program from 5 SEER-program registries. Our findings cannot be generalized to women aged 65 years or younger, who resided elsewhere, who were enrolled in a health maintenance organization, and who had only Medicare Part A coverage. About 14% of subjects participated in a health maintenance organization, which varied geographically (51
). Although SEER data are considered to be the “gold standard” of cancer surveillance systems, some variables may have been misclassified. This may have biased the findings toward the null. The SEER–Medicare data did not contain information about the women's socioeconomic status. Income and educational attainment are unlikely to have explained our findings, because the effect of individual-level socioeconomic status on breast cancer survival is mixed and often attenuated after correction for stronger prognosticators, such as type of treatment and other factors included in our models (52
). Although some breast cancer survivors may receive services from complementary and alternative providers after breast cancer diagnosis, we did not have any information about these providers and were therefore unable to include them in our analysis. Additionally, in the San Francisco-Oakland and Seattle-Puget Sound SEER areas, there is a slightly higher percentage of Asians than African Americans. However, African Americans are typically more segregated than Asians (53
). Finally, because of the use of the marginal probability in the SatScan analysis, the presence of one or more census tracts without any women with breast cancer does not affect the results. In fact, there were several census tracts without any breast cancer patients included in the clusters of shorter- or longer-than-expected breast cancer survival for both Detroit and Atlanta.
In conclusion, interventions to reduce late-stage breast cancer, focusing on areas of high poverty and targeting African Americans, may reduce disparities in subsequent clusters of shorter-than-expected breast cancer survival.