Sage Journals: Discover world-class research

Abstract

Ethnic differences in breast cancer survival have been a long-standing concern. The objective of this article is to present relevant studies for all major US racial/ethnic groups including African–Americans, Latinos, Native Americans, Japanese–Americans and Native Hawaiians, and to discuss underlying causes of disparity, In comparison to Caucasian women, African–American women continue to experience the poorest breast cancer–specific survival of all ethnic groups in the USA. The prognosis for Latinos, Native Hawaiians and Native Americans is intermediate, better than for African–Americans but not as good as for Caucasians, whereas Japanese–American women tend to have better outcomes. The following possible contributors to the observed differences are discussed in detail: unfavorable distribution of stage at diagnosis due to low screening rates, limited access to care and treatment, tumor type, comorbidities, socioeconomic status, obesity and physical activity.

Keywords

breast carcinoma ethnicity risk factors SEER registries survival trends

According to the 2010 Surveillance, Epidemiology and End Results (SEER) report [1], the 5-year breast cancer-specific survival rate in the USA was 89.2%. The strongest determinant of survival is stage at diagnosis: 98.6% for localized disease, 83.4% for regional disease and 23.4% for metastasized breast cancer [1]. During the last 20 years, improvements in breast cancer survival have been observed in all ethnic groups [2,3], but substantial differences across ethnic groups have been reported repeatedly with worse outcomes among ethnic groups of low socioeconomic status (SES) [4 –8]. Several of the predictors proposed as possible explanations for the ethnic-specific survival differences, for example, early detection, access to care, pre-existing chronic diseases, obesity, poverty and lifestyle factors, are related to SES [9 –11]. This raises the question whether ethnic disparities may be due to SES rather than biologic differences, such as tumor types or genetic susceptibility [12 –15]. The objectives of this article are to compare breast cancer survival rates for all major racial/ethnic groups in the USA (African–American, Hispanic/Latino, Asian–American, Native Hawaiian/Pacific Islander and Native American) to rates for Caucasian women and to examine underlying causes. Based on our own expertise, there is a special emphasis on Japanese–American and Native Hawaiian women. Genetic aspects of susceptibility are not presented as part of this article.

Methods

Relevant publications were identified in PubMed® and in the reference sections of published reports. From the large number of investigations that focused on African–American women, we selected the most recent ones and included a large meta-analysis to cover the earlier time period. For the other ethnic groups, we present all available studies even if they were small and published during earlier years. Due to the differences in methodology across studies and the large body of literature, we did not attempt our own meta-analysis or systematic review. Instead, we selected studies that compare breast cancer-specific and all-cause survival across ethnic groups and illustrate particular causes of disparity. The 24 reports summarized in Table 1 all computed hazard ratios (HR) and 95% CIs. Primarily, they utilized data from one or more cancer registries that participate in the SEER program [5 –8,16 –22] and sometimes overlap in study population and years of diagnosis. In a number of investigations, this information was enhanced with data from questionnaires, medical records or Medicare files [23 –27]. Also, a few analyses were conducted within a single hospital or institution [28 –31], network of healthcare institutions [32] or large clinical studies [33,34]. First, the results of the review are presented separately by ethnic group ( Figure 1 ); then individual factors that may contribute to ethnic survival differences are discussed in detail.

Table 1.

Selected studies comparing breast cancer-specific survival by ethnic group.

Author (year) Population source	n % early stage	Cases	Deaths	HR (95% CI)	Covariates	Ref.
Le Marchand et al. (1984) HTR (1960–1979)	2956 58% Loc	W: 1174 J: 973 H: 458 C: 225 F: 127	N/A	Reference group 1.0 (0.8–1.3) 1.6 (1.3–2.1) 1.0 (0.7–1.4) 1.6 (1.1–2.4)	Age, stage, SES	[5]
Sugarman et al. (1994) Seattle SEER, Portland IHS (1974–1989)	25,315 59% 0/Loc	W: 25,213 NA: 102	10,038 49	Reference group 1.4 (1.1–1.9)	Age, stage, urban residence, treatment	[7]
Meng et al. (1997) HTR (1980–1988)	3345 62% Loc Equal access	W: 1191 J: 1130 H: 549 C: 242 F: 233	172 132 122 34 46	1.2 (0.9–1.5) Reference group 1.7 (1.3–2.2) 1.3 (0.9–1.9) 1.6 (1.1–2.3)	Age, stage, census SES, menopausal status, marital status, geographical residence	[16]
Li et al. (2003) SEER (1992–1998)	124,934 48% I	W: 97,999 B: 10,560 J: 2420 F: 2125 C: 1852 H: 689 L: 7219 NA: 322	14,089 2393 187 227 177 88 1117 69	Reference group 1.5 (1.4–1.6) 0.6 (0.5–0.8) 0.9 (0.8–1.1) 0.8 (0.7–1.0) 1.3 (1.0–1.7) 1.1 (1.0–1.1) 1.7 (1.3–2.3)	Age, stage, ER/PR, surgery, radiation therapy	[8]
Wampler et al. (2005) 3 SEER programs (1973–1996)	2555 54% Loc	W:2044 NA/AN: 511	N/A	Reference group 1.6 (1.3–2.0)	Age, marital status, stage, tumor size, lymph nodes, therapy	[17]
Field et al. (2005) CRN (1993–1998)	21,155 67% Loc Equal access	W: 18,879 B: 2276	3474 596	Reference group 1.3 (1.2–1.5)	Age, histology, enrollment history, health plan	[32]
Chlebowski et al. (2005) WHI (1993–1998)	156,570 74% Loc	W: 3455 B: 242	191 21	Reference group 1.8 (1.1–3.1)	Age, BMI, tumor stage, study component	[33]
Tammemagi et al. (2005) Ford Health System (1985–1990)	906 35% 0/I	W: 642 B: 264	115 64	Reference group 1.5 (1.1–2.1)	Age, tumor stage, ER, therapy, comorbidity	[31]
Braun et al. (2005) HTR (1990–2002)	7722 54% I	W: 2363 J: 2666 H: 1330 F: 847 C: 516	239 175 173 110 55	Reference group 0.8 (0.6–0.9) 1.5 (1.2–1.9) 1.4 (1.1–1.7) 0.9 (0.7–1.2)	Age, stage, ER/PR	[18]
Newman et al. (2006) 20 studies (1958–2003)	90,124	W: 76,111 B: 14,013	N/A	Reference group 1.2 (1.1–1.3)	Age, stage, SES	[4]
Goggins et al. (2007) SEER (1991–2004)	348,358 47% I	W: 310,024 B: 34,293 H: 1873 NA: 1702 S: 187	N/A	Reference group 1.4 (1.4–1.5) 1.1 (1.0–1.3) 1.3 (1.1–1.5) 1.6 (1.2–2.1)	Tumor size, grade, histology, ER/PR	[19]
Du et al. (2008) SEER–Medicare (1992–1999)	35,029 59% I	W: 30,484 B: 1971	N/A	Reference group 1.2 (1.0–1.5)	Age, marital status, tumor details, ER/PR, SES, comorbidity, treatment	[27]
Curtis et al. (2008) SEER–Medicare (1994–1999)	41,020 56% 0/I	W: 35,878 B: 2479 L: 1172 A/PI: 1086	4672 477 171 82	Reference group 1.1 (1.0–1.2) 0.9 (0.8–1.0) 0.6 (0.5–0.8)	Age, region, screening, tumor type, ER, grade, treatment, comorbidity, community, SES	[26]
Dawood et al. (2008) SEER (1988–2003)	15,438 All stage IV	W: 11,049 B: 2219	N/A	Reference group 0.9 (0.7–1.2)	Age, grade, ER/PR surgery, marital status	[20]
Chu et al. (2009) Louisiana State University LA, USA (1998–2008)	786 35%0/I Equal access	W: 318 B: 468	46 86	Reference group All deaths 0.9 (0.6–1.3)	Age, stage, therapy, grade, income, SES	[29]
Albain et al. (2009) SWOG Phase III trials	6676 Equal access	W: 6014 B: 662	N/A	Reference group 1.4 (1.1–1.8)	Age, tumor size, number of lymph nodes	[34]
Holmes et al. (2010) SEER (1992–1998)	6951 56% 0/I	W: 5981 B: 506 A: 359	N/A	1.5 (1.1–1.9) 2.6 (1.9–3.6) Reference group	Age, marital status, stage, surgery, radiation	[21]
Gomez et al. (2010) CCR, SEER (1988–2005)	20,747 13% I	J (US): 2130 J (foreign): 1456 C (US): 1217 C (foreign): 4437 F (US): 614 F (foreign): 6814	239 159 114 647 62 1076	Reference group 1.1 (0.9–1.4) 1.5 (1.3–1.7) 1.5 (1.3–1.7) 1.2 (0.9–1.5) 1.5 (1.3–1.7)	Age, immigrant status, marital status, stage, grade, histology, ER, surgery/treatment, neighborhood SES	[22]
Hill et al. (2010) SEER, Mammography Project (1995–2004)	3891 49% I	W: 2881 L: 1010	N/A	Reference group 1.2 (1.0–1.5)	Age, detection, income, education, rural residence, tumor size, stage, grade	[23]
Komenaka et al. (2010) Wishard Memorial Hospital, IN, USA (1997–2006)	574 53% 0/I Equal access	W: 259 B: 315	30 55	Reference group 1.3 (0.8–2.0)	Age, stage, ER/PR, employment, comorbidity	[28]
Barcenas et al. (2010) Medical College, GA, USA (1990–2005)	1159 33% 0/I	W: 670 B: 489	225 217	Reference group 1.4 (1.1–1.6)	Age, stage, therapy, surgery	[30]
Ooi et al. (2011) SEER (2000–2006)	229,594 48% I	W: 176,094 B: 20,486 L: 14,951 J: 2658 H: 885 NA: 1004	10,823 2808 1188 105 68 79	Reference group 1.5 (1.4–1.6) 1.1 (1.0–1.2) 0.8 (0.6–1.0) 1.5 (1.1–2.0) 1.1 (0.8–1.4)	Age, SEER registry, stage, ER/PR, treatment, poverty, education	[6]
Maskarinec et al. (2011) HTR (1995–1996) Plus interview	382 65% 0/I Equal access	J: 137 W: 93 H: 49 C: 45 F: 27	8 7 16 20 19	Reference group 0.4 (0.1–1.2) 0.6 (0.2–1.9) 2.3 (0.9–6.0) 1.7 (0.5–5.7)	Age, menopausal status, BMI, stage, ER/PR, treatment, toxicity, comorbidity, health insurance	[24]
Conroy et al. (2011) MEC, CA County Cancer Surveillance Program, CCR, HTR (1993–2007)	3842 71% Loc	J: 1141 W: 991 B: 748 L: 623 H: 339	65 93 115 72 31	0.8 (0.6–1.1) Reference group 1.4 (1.1–2.0) 1.2 (0.9–1.7) 1.0 (0.7–1.6)	Age, ER/PR, stage, treatment, comorbidity	[25]

Ethnic groups: A: Asian–American; AN: Alaska Native; B: African–American; C: Chinese–American; F: Filipino; H: Native Hawaiian; J: Japanese–American; L: Latino; NA: Native American; PI: Pacific Islander; S: Samoan; W: Caucasian.

Stages: 0: In situ; I: Stage I; Loc: Localized.

CCR: California Cancer Registry; CRN: Cancer Research Network; ER: Estrogen receptor; HR: Hazard ratio; HTR: Hawaii Tumor Registry (part of SEER); IHS: Indian Health Service; MEC: Multiethnic Cohort study; N/A: Not available; PR: Progesterone receptor; SEER: Surveillance, Epidemiology and End Results; SES: Socioeconomic status; SWOG: Southwest Oncology Group; WHI: Women's Health Initiative.

Figure 1.

Breast cancer-specific survival by ethnic group.

Results

African–Americans

The literature on ethnic-specific survival differences is most abundant for African–Americans. The higher breast cancer mortality rates have been a concern for many years, in particular in light of the incidence rates below those for Caucasians [1,3]. Despite some exceptions, the majority of publications show an elevated risk of dying for African–Americans compared with Caucasian breast cancer cases with HRs ranging between 1.2 and 2.6 ( Figure 1A ). A meta-analysis summarizing 20 studies up to 2005 [4] found a higher risk of breast cancer-specific mortality for African–American women (HR = 1.3; 95% CI: 1.2–1.4). Even after controlling for an area-wide measure of SES the association remained significant; the risk estimate was attenuated to 1.2 (95% CI: 1.1–1.3). Two earlier investigations that did not have SES information reported risk estimates of 1.5 [8] and 1.3 [32]; the latter study included women with equal access to healthcare. Since the meta-analysis, a number of conflicting reports have been published. No ethnic differences in outcome were detected in a SEER–Medicare analysis that controlled for SES and comorbidities [26] and in a population of women with low SES who were treated at a single academic center [29]. In a review of medical records within one medical center, no difference in overall survival was observed after adjustment for sociodemographic factors, but the risk for recurrence was nonsignificantly elevated among African–Americans (HR = 1.3; p = 0.11) [28]. Although a study limited to metastasized breast cancers found no ethnic difference in survival, an interaction term between ethnicity and year of diagnosis was statistically significant, indicating that the gap for African–American relative to Caucasian patients, despite being small, increased over time [20]. A range of elevated risks for breast cancer-specific mortality were described in more recent studies ranging from 1.2 [27] and 1.4 [19,25,30] to 1.5 [6,31] and 2.6 [21]. Although a wide range of covariates were included in the models, the predictors varied across reports, for example, education, SES and region [6]; obesity, stage, treatment, comorbidities and hormone receptor status [25]; or access to care [30]. Therefore, the results in Figure 1 reflect the remaining ethnic differences after accounting for different sets of explanatory factors in each study and are difficult to compare. The ideal method to control for differences in treatment is clinical trials; however, an analysis of Phase III clinical trials conducted by the Southwest Oncology Group (SWOG) showed that African–American ethnicity was associated with a 40% higher mortality in patients with early-stage premenopausal breast cancer and a 50% higher mortality among early-stage postmenopausal breast cancer cases, despite treatment on the same protocols and adjustment for multiple prognostic factors [34]. Many of the comparative reports noted the presence of worse predictors of outcome, such as advanced stage, negative estrogen receptor/progesterone receptor (ER/PR) status and triple-negative tumors, among African–American women [11,25,28,29,32].

Asian–Americans

Due to the large differences in SES across Asian–American subgroups, mortality differs considerably by subgroup and also by immigrant status. For example, in a California study, foreign born Chinese and Filipino women had poorer outcomes than those born in the USA [22]. For women of Japanese and Chinese ancestry, generally more favorable outcomes have been reported than for Caucasians, whereas Filipino, Korean, south Asian and Vietnamese immigrants tend to experience poorer outcomes [8,16,22]. When risk estimates for Asian–Americans as a group were presented, outcomes were better than for Caucasians [21,26]. Given the limited data on most Asian–American subgroups, we only summarize studies with Japanese–Americans in Figure 1B. Whereas the risk of dying from breast cancer was similar as for Caucasians in four investigations [5,16,24,25], two reports described survival advantages in the range of 20 [18] to 40% [8] without adjusting for BMI or other lifestyle factors.

Native Hawaiians/Pacific Islanders

Similar to African–Americans, health disparities in Native Hawaiians and other Pacific Islanders due to low SES and lack of access to care have been an area of great concern and active research [35]. Because only one report presented separate results for Samoans [19], all investigations shown in Figure 1C refer to Native Hawaiians. Out of eight studies, all but three [19,24,25] observed statistically significant poorer outcomes. The risk estimates ranged from 1.3 [8] to 1.5 [6,18] and 1.6 [5] when compared with Caucasians; in comparison to Japanese–Americans the HR was 1.7 in one report [16]. The higher risk estimates tended to be in SEER-based analyses without additional information on treatment and comorbidity [6,8,18], whereas studies performed in recent years and controlling for more detailed information on lifestyle factors tended to observe less disparity in survival [24,25]. A study linking insurance claims with Hawaii SEER data, thus controlling for comorbidities and adequacy of treatment, also showed little ethnic differences [36]. This indicates that obesity and comorbidities may explain part of the poorer survival observed among Native Hawaiians who suffer from high rates of obesity, hypertension and diabetes [37,38]. The poor survival of Samoan women as reported by a SEER-based investigation was most likely due to late diagnosis and lack of access to appropriate screening and treatment [6].

Latinos

Of the five studies that included Latinos ( Figure 1D ), three described poorer breast cancer survival outcomes for Latino women who had immigrated from different countries [6,8,23] and two observed no differences [25,26]. However, in comparison with the risk estimates for African–Americans, the HRs for Latinos were relatively small. In a SEER-based report, the risk of dying from breast cancer was 10% higher for Latinos than Caucasians while controlling for stage, age, treatment, ER/PR status and access to healthcare [8]. Later research by Ooi et al. [6] and Hill et al. [23], also based on SEER data for Latinos, found an excess risk of 10% in one study after controlling for stage, age, income, education, residence, ER/PR status and treatment [6], and 23% in the other study after adjustment for method of detection [23]. Two later studies that detected no ethnic differences controlled for additional variables, that is, equal insurance status (Medicare), detection method, comorbidities, SES, surrounding community and region [26] as well as BMI [25].

Native Americans

We identified five studies ( Figure 1E ) among Native American women. A 1974–1989 investigation from Washington state reported poorer breast cancer survival among Native Americans than Caucasians in the same area (HR = 1.4) after controlling for age, stage, residence and treatment [7]. Three later reports also showed 30–70% higher risks of dying from breast cancer for Native American women after adjustment for different predictors [8,17,19]. The most recent study that controlled for stage, age, ER/PR status and treatment in addition to access to healthcare, poverty, education and geographic location detected no statistical difference between Native Americans and Caucasians [6].

Discussion

While there is little doubt that mortality from breast cancer has decreased for all ethnic groups during the last 20 years [1,2], it is clear that survival differences between ethnic groups have not been eradicated. Based on many reports confirming disproportionate numbers of late stage disease, lack of screening and early detection due to limited access to healthcare remain important contributors to this situation [9,23]. Nevertheless, the role of lifestyle factors, such as obesity and physical activity, has become better understood and gained more attention [39]. The differences and time trends across populations are not easily disentangled since the studies do not control for a common set of covariates known to influence survival. As described in an excellent review, many of these factors are related to SES and affect prognosis in combination and through multiple pathways [10]. For example, poverty may directly be responsible for lack of screening but also indirectly affect tumor biology because obesity, smoking and poor nutrition may promote the development of tumors with adverse characteristics. We will consider the major factors that have been identified as contributors to the observed differences and explain the inconsistencies in the reports discussed above.

Early detection & access to care

Given the importance of stage at diagnosis for prognosis [1], screening participation and early detection are the most important predictors of survival. There are many examples of this in the literature, such as the analysis of 229,594 cases from the SEER registries that shows respective rates of 50 and 57% stage I cases among Caucasians and Japanese–Americans, compared with 35, 38,42 and 45% in African–Americans, Latinos, Pacific Islanders and Native Americans, respectively [6]. In a study among Latinos, the screen-detected proportion of cancers was only 52% compared with 61% in Caucasians, and adjustment for type of detection reduced the ethnic difference [23]. As described in a large trend analysis for 1987–2005 [2], absolute ethnic disparities declined for mammography screening, stage at diagnosis and 5-year cause-specific probability of death during this time period; however, relative ethnic disparities in 5-year cause-specific probability of death persisted.

Lack of early detection is further complicated by delay in treatment initiation [9]. Another important issue is compliance with consensus recommendations to treat breast cancer, which have been associated with improved survival [40]. Many reports suggest less surgery, radiation therapy and hormone treatment and 20–50% rates of inappropriate treatment among African-Americans as compared with Caucasians [8,32]. When detailed information from medical charts was used to assess breast cancer treatment [41] or comorbidity and treatment patterns from insurance claims were included as covariates [36], survival times were relatively similar across ethnic groups in Hawaii with a rather unique healthcare environment. Because cancer registries do not typically collect information on treatment beyond 6 months, many of the published reports are missing detailed treatment information after initial treatment. However, access to care and health insurance rates [42] are probably not the only reason for these delays; geographic distance from good treatment centers and cultural factors probably also contribute as suggested by the disparate outcome in the SWOG trials [34].

Tumor type

Advances in molecular classification and characterization of breast tumors into distinct subtypes by using DNA micro arrays independent of disease stage has allowed stratification of cases by prognosis [43,44]. Whereas the respective proportions for the major subtypes appear to be similar in Japanese–Americans and Chinese–Americans as in Caucasians [45], the distribution in African–Americans is skewed toward the subtypes with poorer outcomes [46,47]. African–American women are more likely to be diagnosed with higher tumor grades as well as ER/PR-negative and triple-negative tumors than Caucasians, partly as a result of later stage at diagnosis [9,11,33,48]. The same observation was made for Latino women, although to a lesser degree [6]. Interestingly, a study among a socio-economically deprived population with high obesity rates showed more tumors with poor prognostic features (i.e., late stage, triple negative and lymph node metastases [49]). This suggests that a low SES regardless of ethnic background is associated with breast cancer tumors that have an unfavorable prognosis [10].

Comorbidity

Closely related to the question of appropriate treatment is the issue of pre-existing conditions. Given the high rates of obesity, diabetes and hypertension among African–American and Latino [42] as well as Pacific Islander women [37,38], the presence of these conditions may be responsible for worse breast cancer outcomes, possibly due to less tolerance to cancer treatments. Women with comorbidities may receive less aggressive treatment, as described for diabetic women, due to disease-related complications [50]. The association of comorbidity with lower survival rates among breast cancer patients has been shown repeatedly [36,51,52]; however, comorbidity contributes more to higher overall mortality in breast cancer patients than to breast cancer-specific mortality [31]. On the other hand, controlling for comorbidity does not eliminate all ethnic differences as can be seen in several studies within the meta-analysis [4].

Socioeconomic status

As for many conditions, outcomes tend to be worse for individuals with lower education and income than for those with higher SES [53]. In a recent report on health disparities [42], the persisting ethnic differences in education, health insurance coverage and poverty status are well documented. Although many survival analyses included SES indicators, the registry-based studies usually only had neighborhood-level SES indicators with well documented limitations available since more accurate individual-level SES data are difficult to collect [54]. Nevertheless, in the meta-analysis of studies among African–American women, the area-wide measure of SES narrowed the survival difference considerably [4]. Interestingly, it appears from a limited number of studies within Caucasian populations with low SES that poverty is associated with similar cancer disparities as observed across ethnic groups [2,10,49]. Adjustment for SES probably remains insufficient because a person's economic and social situation is more complex than just assessing income and education; housing, environmental, dietary, cultural, behavioral and access to healthcare issues are additional contributors to health effects and are not easily captured by traditional demographic data [4,53,55]. Since SES is not a biologic risk factor itself and rather a marker for other factors, such as access to screening and healthcare, it is also challenging to interpret studies that controlled for SES and true mediating variables, such as obesity, at the same rime.

Obesity & physical activity

The role of obesity at diagnosis and later has become much clearer over recent years and is important in light of the higher obesity rates in non-Caucasian women [37,42]. There is increasing evidence that obese women with breast cancer experience worse breast cancer survival, as much as 30% higher mortality, than survivors with normal weight [39,56]. This difference appears to be due to estradiol formation in adipose tissue, which stimulates neoplastic cell proliferation in obese women [57], contributing to more biologically aggressive tumors [58]. Estrogen-independent pathways, in particular adipokine production (e.g., adiponectin and leptin), may also contribute to an aggressive breast cancer phenotype [59,60]. Furthermore, obese women may be given lower doses of chemotherapy because the ideal body surface area rather than true body surface area is used to estimate the dose of chemotherapy [61]. Epidemiologic data for other modifiable factors such as physical activity and healthful diets are not as convincing [39], but a growing number of large observational studies have demonstrated that participation in moderate intensity recreational physical activity after diagnosis may improve survival in women with breast cancer [62,63].

Methodological issues

In the studies included in this review ( Table 1 ), variations in study populations and research methodology appear to be major contributors to the conflicting findings. In general, it appears that smaller ethnic differences in survival are observed when more predictors were included [24] or when patients come from a similar background and are treated in the same institution [28,29]. However, each study controlled for a different combination of covariates, which makes it difficult to determine which factors explain the ethnic disparity across populations. Sample sizes and especially the number of cause-specific deaths were very small in several investigations. Although the studies were based on different populations across the country, the majority relied on data collected by SEER registries. While the SEER data provide information for a large number of cases and follow a standardized protocol for data collection, they lack information on personal and lifestyle factors, such as BMI, SES, access to healthcare and comorbidities. Another limitation is that the majority of studies with Asian–Americans and Pacific Islanders relied on similar datasets or geographic locations because the number of breast cancer patients with Asian and Pacific Islander ancestry in the USA is limited. Thus, the multiple SEER analyses are not independent from each other. For example, some of the cases in smaller SEER studies may also be included in the larger or national SEER studies and other reports are updates of earlier investigations with partial overlap. An ideal study would present the association between ethnicity and survival among women with breast cancer in age-adjusted models and compare this to models that control for other predictors of breast cancer survival separately and in combination. These predictors should include stage at diagnosis, hormone receptor status, tumor characteristics, treatment received, comorbidities, insurance status, SES, obesity and preferably also smoking, physical activity and other lifestyle factors. This would answer the question of what proportion of ethnic differences in survival are explained by individual factors and their combinations and would suggest the most likely interventions to reduce the disparity in breast cancer survival.

Conclusion

From the existing evidence, it appears that African–American women continue to experience the poorest breast cancer-specific survival of all ethnic groups in the USA. The prognosis for Latinos, Native Hawaiians and Native Americans is intermediate, better than for African–Americans but not as good as for Caucasians and Japanese–Americans. One possible explanation of this evidence is that genetic susceptibility or lifestyle factors predispose some ethnic groups to tumors with more adverse behavior [12 –15]. Future genetic investigations may also detect ethnic-related genetic polymorphisms of chemotherapy metabolizing enzymes [64]. However, an alternative interpretation is that, regardless of ethnic background, women with low SES and unhealthy lifestyles are more likely to experience late stage disease and to develop more aggressive tumors than more affluent women. This hypothesis is supported by the following pieces of evidence. One, research among Caucasian women with low SES indicates similar tumor types and poor survival as observed in African–American populations [49]. Second, improvements in outcomes have occurred over time across ethnic groups [2]. Finally, inclusion of more treatment, comorbidity, SES and lifestyle information in the statistical analysis appears to diminish the observed ethnic differences ( Figure 1 ).

Future perspective

For the future, Newman et al. proposed two research areas that need to be strengthened in addition to improved early detection and access to care: methods to measure effects of sociobehavioral issues and poverty (e.g., environmental, economic, cultural and lifestyle factors) on breast cancer risk, and an exploration of associations between ethnicity and variation in primary breast tumor biology [4]. As to efforts in reducing the unequal mortality to breast cancer, improvements in SES, health insurance and access to care will still achieve great improvements, although we do not know at this time whether a part of the observed ethnic differences is due to genetic factors that cannot be modified.

Executive summary

Background

Although breast cancer survival has improved for all ethnic groups over the last 20 years, poor survival rates in some ethnic groups remain an important concern.

Results

In comparison to other ethnic groups in the USA, African–Americans have worse breast cancer-specific survival rates.

Breast cancer-related mortality among Latino, Native Hawaiian and Native American women is intermediate between African–Americans and Caucasians, whereas Japanese–Americans and some other Asian–American groups show better survival rates than Caucasians.

Adjustment for prognostic predictors reduces ethnic differences in breast cancer survival.

Lack of early detection, late stage at diagnosis and limited access to healthcare are the most important predictors of poor breast cancer survival.

Low socioeconomic status appears to be associated with tumors showing unfavorable characteristics and higher breast cancer-related mortality independent of ethnic background.

Comorbidities, obesity and lifestyle factors have emerged as additional significant determinants of prognosis.

Future perspective

Improvements in early detection of breast cancer and access to healthcare will lead to further reductions in breast cancer-related mortality.

Better methods of measuring the effects of sociobehavioral factors and poverty on tumor biology are needed to understand these associations.

Explorations of tumor biology and genetic susceptibility may be able to identify additional determinants of ethnic differences.

Footnotes

SM Conroy was supported by a postdoctoral fellowship on grant R25 CA 90956. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

References

Papers of special note have been highlighted as:

of interest

Howlader

Noone

Krapcho

. SEER Cancer Statistics Review, 1975–2008. National Cancer Institute, Bethesda, MD, USA (2011).

Provides recent breast cancer incidence, mortality and survival data for cancer registries in the USA.

Harper

Lynch

Meersman

Breen

Davis

Reichman

. Trends in area-socioeconomic and race-ethnic disparities in breast cancer incidence, stage at diagnosis, screening, mortality, and survival among women ages 50 years and over (1987–2005). Cancer Epidemiol. Biomarkers Prev. 18(1), 121–131 (2009).

Smigal

Jemal

Ward

. Trends in breast cancer by race and ethnicity: update 2006. CA Cancer J. Clin. 56(3), 168–183 (2006).

Newman

Griffith

Jatoi

Simon

Crowe

Colditz

. Meta-analysis of survival in African–American and white American patients with breast cancer: ethnicity compared with socioeconomic status. J. Clin. Oncol. 24(9), 1342–1349 (2006).

Large analysis of 20 different studies that included African–American women and was adjusted for socioeconomic status.

Le Marchand

Kolonel

Nomura

. Relationship of ethnicity and other prognostic factors to breast cancer survival patterns in Hawaii. J. Natl Cancer Inst. 73(6), 1259–1265 (1984).

10.

Ooi

Martinez

. Disparities in breast cancer characteristics and outcomes by race/ethnicity. Breast Cancer Res. Treat. 127(3), 729–738 (2011).

11.

Sugarman

Dennis

White

. Cancer survival among American Indians in western Washington State (United States). Cancer Causes Control 5(5), 440–448 (1994).

12.

Malone

Daling

. Differences in breast cancer stage, treatment, and survival by race and ethnicity. Arch. Intern. Med. 163 (1), 49–56 (2003).

13.

Gorin

Heck

Cheng

Smith

. Delays in breast cancer diagnosis and treatment by racial/ethnic group. Arch. Intern. Med. 166(20), 2244–2252 (2006).

14.

Vona-Davis

Rose

. The influence of socioeconomic disparities on breast cancer tumor biology and prognosis: a review. J. Womens Health (Larchmt) 18(6), 883–893 (2009).

15.

Presents an insightful analysis of how poverty affects the biology and the prognosis of breast tumors.

16.

Bauer

Brown

Cress

Parise

Caggiano

. Descriptive analysis of estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and HER2-negative invasive breast cancer, the so-called triple-negative phenotype: a population-based study from the California Cancer Registry. Cancer 109(9), 1721–1728 (2007).

17.

Cunningham

Butler

. Racial disparities in female breast cancer in South Carolina: clinical evidence for a biological basis. Breast Cancer Res. Treat. 88(2), 161–176 (2004).

18.

Schwartz

Crossley-May

Vigneau

Brown

Banerjee

. Race, socioeconomic status and stage at diagnosis for five common malignancies. Cancer Causes Control 14(8), 761–766 (2003).

19.

Mountain

Risch

. Assessing genetic contributions to phenotypic differences among ‘racial’ and ‘ethnic’ groups. Nat. Genet. 36(Suppl. 11), S48–S53 (2004).

20.

Cunningham

Montero

Garrett-Mayer

Berkel

Ely

. Racial differences in the incidence of breast cancer subtypes defined by combined histologic grade and hormone receptor status. Cancer Causes Control 21(3), 399–409 (2010).

21.

Meng

Maskarinec

Wilkens

. Ethnic differences and factors related to breast cancer survival in Hawaii. Int. J. Epidemiol. 26(6), 1151–1158 (1997).

22.

Wampler

Lash

Silliman

Heeren

. Breast cancer survival of American Indian/Alaska Native women, 1973–1996. Soz. Praventivmed. 50(4), 230–237 (2005).

23.

Braun

Fong

Gotay

Pagano

Chong

. Ethnicity and breast cancer in Hawaii: increased survival but continued disparity. Ethn. Dis. 15(3), 453–460 (2005).

24.

Goggins

Wong

. Poor survival for US Pacific Islander cancer patients: evidence from the Surveillance, Epidemiology, and End Results database: 1991 to 2004. J. Clin. Oncol. 25(36), 5738–5741 (2007).

25.

Dawood

Broglio

Gonzalez-Angulo

Buzdar

Hortobagyi

Giordano

. Trends in survival over the past two decades among white and black patients with newly diagnosed stage IV breast cancer. J. Clin. Oncol. 26(30), 4891–4898 (2008).

26.

Holmes

Jr Opara

Hossain

. A five-year breast cancer-specific survival disadvantage of African–American women. Afr. J. Reprod. Health 14(3), 195–200 (2010).

27.

Gomez

Clarke

Shema

Chang

Keegan

Glaser

. Disparities in breast cancer survival among Asian women by ethnicity and immigrant status: a population-based study. Am. J. Pub. Health 100(5), 861–869 (2010).

28.

Hill

Nibbe

Royce

. Method of detection and breast cancer survival disparities in Hispanic women. Cancer Epidemiol. Biomarkers Prev. 19(10), 2453–2460 (2010).

29.

Maskarinec

Pagano

Lurie

Bantum

Gotay

Issell

. Factors affecting survival among women with breast cancer in Hawaii. J. Womens Health (Larchmt) 20(2), 231–237 (2011).

30.

Conroy

Maskarinec

Wilkens

White

Henderson

Kolonel

. Obesity and breast cancer survival in ethnically diverse postmenopausal women: the Multiethnic Cohort Study. Breast Cancer Res. Treat. 129(2), 565–574 (2011).

31.

Curtis

Quale

Haggstrom

Smith-Bindman

. Racial and ethnic differences in breast cancer survival: how much is explained by screening, tumor severity, biology, treatment, comorbidities, and demographics? Cancer 112(1), 171–180 (2008).

32.

Fang

Meyer

. Impact of treatment and socioeconomic status on racial disparities in survival among older women with breast cancer. Am. J. Clin. Oncol. 31(2), 125–132 (2008).

33.

Komenaka

Martinez

Pennington

Jr . Race and ethnicity and breast cancer outcomes in an underinsured population. J. Natl Cancer Inst. 102(15), 1178–1187 (2010).

34.

Chu

Smith

Williams

. Race/ethnicity has no effect on outcome for breast cancer patients treated at an academic center with a public hospital. Cancer Epidemiol. Biomarkers Prev. 18(8), 2157–2161 (2009).

35.

Barcenas

Wells

Chong

French

Looney

Samuel

. Race as an independent risk factor for breast cancer survival: breast cancer outcomes from the Medical College of Georgia Tumor Registry. Clin. Breast Cancer 10(1), 59–63 (2010).

36.

Tammemagi

Nerenz

Neslund-Dudas

Feldkamp

Nathanson

. Comorbidity and survival disparities among black and white patients with breast cancer. JAMA 294(14), 1765–1772 (2005).

37.

Field

Buist

Doubeni

. Disparities and survival among breast cancer patients. J. Natl Cancer Inst. Monogr. 35, 88–95 (2005).

38.

Chlebowski

Chen

Anderson

. Ethnicity and breast cancer: factors influencing differences in incidence and outcome. J. Natl Cancer Inst. 97(6), 439–448 (2005).

39.

Albain

Unger

Crowley

Coltman

Jr Hershman

. Racial disparities in cancer survival among randomized clinical trials patients of the Southwest Oncology Group. J. Natl Cancer Inst. 101(14), 984–992 (2009).

40.

Survival analysis within a large clinical trial that treated all women on the same protocol.

41.

Blaisdell

. The health status of the Kanaka Maoli (indigenous Hawaiians). Asian Am. Pac. Isl. J. Health 1(2), 116–160 (1993).

42.

Maskarinec

Pagano

Yamashiro

Issell

. Influences of ethnicity, treatment, and comorbidity on breast cancer survival. J. Clin. Epidemiol. 56(7), 678–685 (2003).

43.

Davis

Busch

Hammatt

. The relationship between ethnicity and obesity in Asian and Pacific Islander populations: a literature review. Ethn. Dis. 14(1), 111–118 (2004).

44.

Salvail

Nguyen

Liang

. 2010 State of Hawaii Behavioral Risk Factor Surveillance System. Hawaii Department of Health, Honolulu, HI, USA (2011).

45.

Patterson

Cadmus

Emond

Pierce

. Physical activity, diet, adiposity and female breast cancer prognosis: a review of the epidemiologic literature. Maturitas 66(1), 5–15 (2010).

46.

Summarizes studies that examined the effect of obesity and physical activity on breast cancer survival.

47.

Hebert-Croteau

Brisson

Latreille

Rivard

Abdelaziz

Martin

. Compliance with consensus recommendations for systemic therapy is associated with improved survival of women with node-negative breast cancer. J. Clin. Oncol. 22(18), 3685–3693 (2004).

48.

Issell

Maskarinec

Pagano

Gotay

. Breast cancer treatment among women of different ethnicity in Hawaii. Cancer Invest. 23(6), 497–504 (2005).

49.

Frieden

, Centers for Disease Control and Prevention. CDC health disparities and inequalities report – United States, 2011. MMWR 60(Suppl.), 1–113 (2011).

50.

Sorlie

Perou

Tibshirani

. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl Acad. Sci. USA 98(19), 10869–10874 (2001).

51.

Sorlie

. Molecular classification of breast tumors: toward improved diagnostics and treatments. Methods Mol. Biol. 360, 91–114 (2007).

52.

Telli

Chang

Kurian

. Asian ethnicity and breast cancer subtypes: a study from the California Cancer Registry. Breast Cancer Res. Treat. 127(2), 471–478 (2011).

53.

Carey

Perou

Livasy

. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 295(21), 2492–2502 (2006).

54.

Ihemelandu

Naab

Mezghebe

. Treatment and survival outcome for molecular breast cancer subtypes in black women. Ann. Surg. 247(3), 463–469 (2008).

55.

Morris

Naidu

Topham

. Differences in breast carcinoma characteristics in newly diagnosed African-American and Caucasian patients: a single-institution compilation compared with the National Cancer Institute's Surveillance, Epidemiology, and End Results database. Cancer 110(4), 876–884 (2007).

56.

Vona-Davis

Rose

Hazard

. Triple-negative breast cancer and obesity in a rural Appalachian population. Cancer Epidemiol. Biomarkers Prev. 17(12), 3319–3324 (2008).

57.

Shows that Caucasian women with low socoioconomic status experience poor breast cancer survival.

58.

Srokowski

Fang

Hortobagyi

Giordano

. Impact of diabetes mellitus on complications and outcomes of adjuvant chemotherapy in older patients with breast cancer. J. Clin. Oncol. 27(13), 2170–2176 (2009).

59.

Satariano

Ragland

. The effect of comorbidity on 3-year survival of women with primary breast cancer. Ann. Intern. Med. 120(2), 104–110 (1994).

60.

West

Satariano

Ragland

Hiatt

. Comorbidity and breast cancer survival: a comparison between black and white women. Ann. Epidemiol. 6(5), 413–419 (1996).

61.

Adler

Ostrove

. Socioeconomic status and health: what we know and what we don't. Ann. NY Acad. Sci. 896, 3–15 (1999).

62.

Krieger

. Overcoming the absence of socioeconomic data in medical records: validation and application of a census-based methodology. Am. J. Pub. Health 82, 703–710 (1992).

63.

Krieger

Williams

Moss

. Measuring social class in US public health research: concepts, methodologies, and guidelines. Ann. Rev. Pub. Health 18, 341–378 (1997).

64.

Carmichael

. Obesity and prognosis of breast cancer. Obes. Rev. 7(4), 333–340 (2006).

65.

Calle

Kaaks

. Overweight, obesity and cancer: epidemiological evidence and proposed mechanisms. Nat. Rev. Cancer 4(8), 579–591 (2004).

66.

Lonning

Helle

Duong

Ekse

Aas

Geisler

. Tissue estradiol is selectively elevated in receptor positive breast cancers while tumour estrone is reduced independent of receptor status. J. Steroid Biochem. Mol. Biol. 117(1–3), 31–41 (2009).

67.

Rose

Gilhooly

Nixon

. Adverse effects of obesity on breast cancer prognosis, and the biological actions of leptin (review). Int. J. Oncol. 21(6), 1285–1292 (2002).

68.

Brakenhielm

Veitonmaki

Cao

. Adiponectin-induced antiangiogenesis and antitumor activity involve caspase-mediated endothelial cell apoptosis. Proc. Natl Acad. Sci. USA 101(8), 2476–2481 (2004).

69.

Griggs

Sorbero

Lyman

. Undertreatment of obese women receiving breast cancer chemotherapy. Arch. Intern. Med. 165(11), 1267–1273 (2005).

70.

Barbaric

Brooks

Moore

Cheifetz

. Effects of physical activity on cancer survival: a systematic review. Physiother. Can. 62(1), 25–34 (2010).

71.

Carmichael

Daley

Rea

Bowden

. Physical activity and breast cancer outcome: a brief review of evidence, current practice and future direction. Eur. J. Surg. Oncol. 36(12), 1139–1148 (2010).

72.

Neber

Roe

. Ethnic and genetic differences in metabolism genes and risk of toxicity and cancer. Sci. Total Environ. 274(1–3), 93–102 (2001).

Ethnic Differences in Breast Cancer Survival: Status and Determinants

Abstract

Keywords

Methods

Results

African–Americans

Asian–Americans

Native Hawaiians/Pacific Islanders

Latinos

Native Americans

Discussion

Early detection & access to care

Tumor type

Comorbidity

Socioeconomic status

Obesity & physical activity

Methodological issues

Conclusion

Future perspective

Footnotes

References