Contrary to the previously reported positive association between urban residence, SEP, and overall breast cancer occurrence (16
), this study found that living in a high poverty county (≥ 20%), a county with a high percentage of less than high school graduates, and residing in a low SEP county as defined by the poverty-high school index were significantly associated with IBC, even after adjustment for age at diagnosis and race/ethnicity.
Prior studies examining overall breast cancer occurrence have found it to be associated with urban residence and higher SEP (16
). However, the majority of breast cancers are non-IBC, and thus determining IBC’s association with SEP based on studies of all breast cancer types is difficult. This study used an inclusive definition to separately characterize IBC from all other breast cancer types, and then directly compared IBC to non-IBC through use of HLMs adjusting for age and race/ethnicity, in order to specifically examine SEP and its association with IBC as a distinct breast cancer entity.
Residing in a county with a large percent of persons below the poverty level, less than high school graduates, and in the low SEP group of the poverty-high school index were all associated with IBC in this analysis, suggesting that poverty and education are capturing similar aspects of SEP that affect IBC incidence. As SEP measures, poverty and education both act as a summary measure of a county’s SEP and can be compared over time and across US geographic areas (50
). While poverty and education are correlated, as each has been shown to be related to overall breast cancer incidence, they were included as separate SEP measures as well as in a combined index in this analysis (16
). Metro vs. non-metro area of residence at diagnosis captures various characteristics that can be directly and/or indirectly related to an individual’s health, such as population density, geographic isolation, exposure to agriculture, industrial or commercial complexes, and proximity and access to health care services (68
). Furthermore, there are many ways to classify counties based on characteristics such as administrative units, land-use, and economic concepts (68
). It is possible the definition of metro vs. non-metro used in this analysis does not capture specific factors that may be related to IBC, and thus explain the lack of association seen.
Although risk factors for IBC remain largely unknown, some studies have shown different risk factor profiles for IBC patients as compared to non-IBC patients. Chang et al. found that high BMI was significantly associated with increased risk of IBC, regardless of menopausal status (12
). This is in contrast to overall breast cancer, where higher premenopausal weight has been shown to reduce risk (70
). Chang et al. also found IBC patients were more likely to be premenopausal and have younger age at menarche and first birth as compared to non-IBC and non-breast cancer patients (12
A study conducted in France by Le et al. found that IBC patients had a lower educational level, a higher BMI, a longer cumulative duration of breastfeeding, and included a greater proportion of non-European women as compared to non-IBC patients (13
). A recent study of Egyptian breast cancer cases found IBC patients had significantly lower parity than non-IBC patients (14
). Furthermore, a 2010 study based in Tunisia reported a rural predominance of IBC among the cases studied, and hypothesized the reduction in IBC seen in that country was due in part to increasing SEP (71
In this analysis, IBC was associated with younger age and Black race/ethnicity, while API race/ethnicity was associated with lower odds of IBC, as found in previous studies (1
). White Hispanic and AI/AN race/ethnicity were also found to be significantly associated with IBC. A previous study showed no difference in the age-adjusted IBC IR between Hispanic and non-Hispanic women for cases diagnosed from 1994–1998 reported to the North American Association of Central Cancer Registries (64
). However, this study did not classify Hispanic origin as mutually exclusive from other race/ethnicities, and used the more restrictive ICD-O-3 8530 code to define IBC (64
). Younger age at IBC diagnosis has been reported for AI/AN women as compared to White women (6
), although no studies which directly compared the IRs or proportion of IBC between AI/AN women and other race/ethnicities were located.
The strengths of this study include the use of the US SEER database, 5 mutually exclusive race/ethnicity categories, a comprehensive definition of IBC, and a hierarchical modeling structure. The SEER program is considered the standard for cancer registry data quality worldwide (72
). Quality control studies, including case-finding, recoding, and reliability studies are continually conducted by the SEER program to ensure data included in the registries are accurate and collected and recorded in a uniform and timely manner across all registries (72
). As IBC is a relatively rare diagnosis, the US SEER database, which covers 26% of the US population residing in varying regions and geographic areas with over-representation of minority groups, allows for the stratification of IBC incidence by SEP and race/ethnicity categories (32
Previous studies have been limited to reporting IBC rates and proportions for a limited number of race/ethnicity categories, usually for White, Black, & Other, due to small numbers of cases as well as the manner in which this data was recorded by SEER (1
). Beginning with the November 2005 SEER data submission, the algorithms for creating the race recode variables within the SEER database were revised, allowing for the examination of incidence for four race categories: White, Black, AI/AN, and API, as well as Hispanic ethnicity (73
). The race and Hispanic ethnicity data can also now be merged in order to create mutually exclusive race/ethnicity categories (73
). This allowed for the current analysis to report results for 5 mutually exclusive race/ethnicity categories, as opposed to the more limited race/ethnicity analyses in previous IBC studies.
IBC studies have been hampered by lack of a standard case definition (6
). Previous studies have used the ICD-O 8530 designation to define IBC (7
). ICD-O code 8530 is a pathologic designation requiring plugging of the dermal lymphatics with tumor emboli and does not consider clinical skin changes (6
). However, this conservative IBC definition is not consistent with the current AJCC staging manual guidelines, and may underestimate the true incidence of IBC (6
). SEER EOD codes are based on a combined clinical and operative/pathologic assessment abstracted from the pathology report, and allow for identification of IBC cases that do not have ICD-O 8530 as the pathologic diagnosis for years prior to 2004 (7
). From 2004 forward, SEER includes a variable with derived AJCC staging, which allows for the identification of IBC cases defined as the primary tumor designation of “T4d” (35
). The comprehensive IBC definition used in this paper is similar to that used in recent IBC studies (6
). Using this definition should help ensure less misclassification of IBC cases to the non-IBC group. Finally, use of a hierarchical modeling structure allows for the calculation of more accurate standard errors, thus adding confidence to any significant results found (61
A few limitations should be noted when interpreting the results of this analysis. Though SEER data are broadly representative of the US population, cases recorded in the SEER database are more likely to be foreign born and urban as compared to the US population as measured in the 2000 census (78
). There are also a relatively small number of AI/AN IBC cases available for this analysis (n=39), which is reflected in the wide 95% CIs around the IR and OR estimates for this race/ethnicity category. However, due to the US SEER’s large size and over 30 years of follow-up, it is generally considered to accurately represent the overall US cancer population (78
Another limitation is the lack of individual-level SEP information in the US SEER database and the inherent ecologic bias in interpreting the results of this analysis at the individual-level. Any associations seen between county-level SEP and IBC occurrence may not necessarily hold were individual-level SEP available and used in the analysis (79
). Therefore, the results of this analysis are better interpreted at the contextual level, i.e., the effect being measured is that of residing in a county with a particular SEP characteristic, not that of the breast cancer cases’ individual SEP. However, a study comparing census-level SEP measures to individual-level measures found they were similarly associated with individual-level health outcomes (52
). Furthermore, the US SEER database linked to US census data provides a unique opportunity to conduct analyses stratified by race/ethnicity and county-level SEP measures on a relatively large number of IBC and non-IBC cases.
Overall breast cancer has been found to be positively associated with SEP, whereas in this analysis IBC was associated with decreasing SEP. One explanation for these results is that women of lower SEP have less access to health care that would lead to early detection and the resultant neglected breast cancer develops into IBC. Some earlier IBC work suggested that it may be a subtype of locally advanced breast cancer rather than a distinct entity (80
). However, the majority of recent studies on the epidemiology, clinical and prognostic characteristics, biology, and molecular genetics of IBC suggest is it likely a distinct biologic entity from other breast cancer (10
). Another explanation is that breast cancers occurring in women of lower SEP presenting with skin involvement are misdiagnosed as IBC (85
). However, there is little literature, especially in the US, suggesting women of lower SEP are at higher risk for IBC, so it is unlikely clinicians would be more likely to look for and diagnose (or misdiagnose) IBC disproportionately in women of lower SEP.
These results are in keeping with a growing amount of evidence showing IBC likely has a different risk factor profile than other breast cancers and is a distinct biologic entity (10
). Few studies have examined the epidemiology of rarer forms of breast cancer such as IBC, though studies that have suggest the general breast cancer risk profile may not hold for rarer breast cancer subtypes (1
). Further investigation into the etiology of IBC is needed in order to elucidate risk factors for the disease that would help guide prevention and screening programs, especially studies which examine individual and community-level associations between multiple SEP measures and IBC incidence. However, these results also indicate studies designed to investigate why the disparity of higher incidence of IBC in lower SEP groups and racial/ethnic minorities is observed, as well as potential interventions to eliminate these differences, are called for. Furthermore, because treatment is especially urgent in IBC, design and implementation of strategies that would promote earlier IBC diagnosis among lower SEP groups and racial/ethnic minorities, which traditionally experience less access to early detection programs, would likely have a direct and favorable impact on their prognosis.