Background:

This study was conducted to evaluate trends in survival, by race-ethnicity, for women diagnosed with breast cancer in Florida over a 26-year period.

Methods:

This was a retrospective cohort study of women diagnosed with invasive breast cancer in Florida between 1990 and 2015. Data were obtained from the Florida Cancer Data System. Women in the study were categorized according to race (white/black) and Hispanic ethnicity (yes/no). Cumulative incidence estimates of 5- and 10-year breast cancer–related death with 95% confidence intervals (CI) were obtained by race-ethnicity, according to diagnosis year. Subdistribution hazard models were used to obtain subdistribution HRs (sHR) for the relative rate of breast cancer death accounting for competing causes.

Results:

Breast cancer mortality decreased for all racial-ethnic groups, and racial-ethnic minorities had greater absolute and relative improvement for nearly all metrics compared with non-Hispanic white (NHW) women. However, for the most recent time period (2010–2015), black women still experienced significant survival disparities with non-Hispanic black (NHB) women, having twice the rate of 5-year [sHR = 2.04; 95% confidence interval (CI), 1.91–2.19] and 10-year (sHR = 2.02; 95% CI, 1.89–2.16) breast cancer–related death. Adjustment for covariates substantially reduced the excess rate of breast cancer–related death for black women.

Conclusions:

Despite efforts to improve disparities in breast cancer outcomes for underserved women in Florida, black women continue to experience significant survival disparities.

Impact:

These results highlight the need for targeted approaches to eliminate disparities in breast cancer survival for black women.

For women in the United States, among cancers, breast cancer ranks first in incidence and second in mortality behind lung cancer (1). Trends over time indicate variability by race/ethnicity. For example, the incidence of breast cancer in non-Hispanic white (NHW) women was much higher than that of non-Hispanic Black (NHB) women in 1980. Both groups of women had large increases in incidence during the 1980s due to uptake of screening mammography, although annual increases were greater for white women (2). Incidence in NHW women decreased from 1999–2004, possibly due to decreased use of postmenopausal hormone replacement therapy subsequent to findings from the Women's Health Initiative (3). Unlike the case for NHW women, following the relatively large increases in incidence from the late 1970s and 1980s, NHB women have had a consistently small, increasing incidence, such that rates have recently converged with that of white women (3). Compared with NHW women, Hispanic women have a 30% lower breast cancer incidence rate that, on average, has gradually increased since 1992 (2, 4).

In terms of mortality, NHW and NHB women had similar rates from 1975–1981 (2). Both groups had an increasing mortality rate from the mid-1970s to the early 1990s. However, this increasing mortality rate was nearly five times higher for NHB women. In addition, breast cancer mortality has been decreasing for NHW women since 1990. For NHB women, mortality did not begin to decrease until 1993, and the improvement was of lesser magnitude than that for NHW women. The result of this differential improvement in breast cancer mortality has been a widening disparity in mortality rates over time (2). However, recent data indicates that the disparity gap may be slightly narrowing. Similar to what was described for incidence, mortality rates for Hispanic women are considerably lower than those for NHW and NHB women and, on average, the rate has been declining since 1992 (2, 4).

Cancer disparities can be defined as disproportionately poorer cancer outcomes among certain population groups primarily as a result of social factors, sometimes in concert with behavioral, environmental, biological, and genetic factors (5–7). Widening racial/ethnic disparities in cancer mortality over the past several decades brought renewed interest to cancer health disparities research, which continues today (7). In an effort to redress disparities in breast cancer outcomes, numerous initiatives have been launched by government agencies, private foundations, community groups, and researchers (8–14). Examination of trends in breast cancer disparities over time is necessary to assess the effectiveness of these programs, determine whether progress is being made to narrow inequalities in cancer outcomes, and to identify the extent to which targeted approaches are needed to eliminate disparities in breast cancer outcomes by race/ethnicity.

The goal of this study was to evaluate trends in survival by race-ethnicity for women diagnosed with breast cancer in Florida from 1990 to 2015. Florida is the third most populous state in the country and home to a diverse population with 27% of the population comprised of Hispanic residents and 17% identifying as NHB (15). Viewing disparities in breast cancer outcomes from a historical and more recent point of view allows an appraisal of any improvements that have occurred over time and highlights additional efforts that are needed to ensure that all women in the state have equitable access to breast cancer prevention and high quality care from diagnosis, through treatment, and into survivorship.

Study population

This was a retrospective cohort study of women greater than and equal to 18 years of age in Florida diagnosed with breast cancer during the years 1990–2015. Data for this study were obtained from the Florida Cancer Data System (FCDS), which serves as the statewide cancer registry. The FCDS has been collecting data on incident cases of cancer in the state since 1981 (16). We had the following exclusions: diagnosed with noninvasive breast cancer (carcinoma in situ, n = 66,024); prior cancer diagnosis (n = 50,566); unknown disease stage (n = 17,975); diagnosed at autopsy, via death certificate, or no survival time (n = 6,397); race other than white or black (n = 5,979); missing or invalid census tract (3,713); sex other than female (n = 2,797); missing diagnosis date or last follow-up date (n = 1,187); residence outside of Florida (n = 1,033); and unknown age at diagnosis (n = 8). This study was approved by the Institutional Review Boards (IRB) of the Florida Department of Health and the University of Central Florida.

Study variables

The FCDS collects demographic, tumor-related, first course of treatment, follow-up, and cause of death data for all reported cases in the registry. The demographic variables of interest in this study included race/ethnicity, age, census tract poverty and geography, and insurance status. Race/ethnicity was self-reported and categorized according to race and ethnicity as NHW, NHB, Hispanic white (HW), Hispanic black (HB). Ages were categorized as 18–29, 30–39, 40–49, 50–64, 65–74, 75–84, and 85+ years. Census tract poverty was classified as low (< 5.0%), lower-middle (5.0%–9.9%), upper-middle (10%–19.9%), and high (≥20%) according to the percentage of households that lived in poverty. This information was obtained from the following data files according to diagnosis year: 1990–1994, Census 1990; 1995–2004, Census 2000; 2005–2015, American Community Survey. Census tract geography was classified according to rural-urban commuting area (RUCA) secondary codes as urban, large rural, small rural, and isolated rural as others have described (17, 18). This information was obtained from Census 1990, 2000, and 2010 data files. Insurance status was categorized according to primary payer of health-related claims at diagnosis and/or treatment.

Tumor-related characteristics included disease stage based on the Surveillance, Epidemiology, and End Results classification (localized, regional, and distant) and tumor grade (high and low). Information on molecular characteristics of tumor cells regarding hormone receptor status and HER2 status was only available for more recently diagnosed cases; data is reported only for these more recently diagnosed women. Treatment information concerning receipt of surgery, radiation, chemotherapy, hormone therapy, and immune therapy was available for all women in the study although information concerning the time of initial treatment was missing for a subset of women. Cause of death was classified as due to breast cancer, other cancer, and noncancer causes.

Statistical analyses

Characteristics of study participants according to race/ethnicity are presented as frequencies/percentages. Statistical significance was defined as P < 0.05. The primary outcome of this study was survival and specifically, breast cancer–specific survival. Survival time was calculated from the date of diagnosis to the date of the event or censoring. We obtained 5- and 10-year estimates of the cumulative incidence of breast cancer–related death with 95% confidence intervals (CI) for each time period of diagnosis. Hypothesis testing of the cumulative incidence function according to race/ethnicity was performed by Gray test. For all women in the study, the 10-year cumulative incidence functions according to race/ethnicity are displayed graphically.

The Fine-Gray subdistribution hazards regression model was used to estimate subdistribution HRs (sHR) with 95% CI for the relative hazard rate of breast cancer–specific death accounting for competing causes (19–21). Cause-specific HRs (csHR; treating competing causes as censoring events) were also obtained via Cox regression. For this study, we obtained the relative subdistribution hazard rate for the racial/ethnic groups of interest compared with NHW. In our primary analysis, no adjustment was made for any potential confounders or mediators of the race/ethnicity effect on survival. Thus, the obtained HRs demonstrate the total effect for the relative rate of death for the women in the racial/ethnic groups of interest in this study compared with NHW women. As a secondary analysis, we restricted the study sample to more recently diagnosed women (2005–2015) and obtained sHRs adjusted for age, census-tract poverty level, geography, health insurance status, Surveillance Epidemiology and End Results (SEER) summary stage, hormone receptor status, tumor grade, and treatment (surgery, chemotherapy, radiation, hormone therapy, and immunotherapy).

There were 257,171 women diagnosed with breast cancer in Florida during the study period that were available for analysis. Characteristics of the women according to race/ethnicity are displayed in Table 1. Most women were NHW (n = 204,552, 79.5%), followed by Hispanic white (n = 27,028, 10.5%), NHB (n = 24,870, 9.7%), with a small minority of women classified as Hispanic black (n = 721, 0.3%). NHW women were older than the other race-ethnicity groups [≥ 65 years: 51% vs. 30.5% (NHB), 40.1% (HW), and 30.0% (HB)]. NHB and HB were more likely to live in high poverty neighborhoods, to be diagnosed at distant stage, to receive chemotherapy, and less likely to receive surgery.

Table 1.

Demographic and clinical characteristics of female patients with breast cancer in Florida, 1990–2015 (n = 257,171).

NHWNHBHispanic whiteHispanic black
Characteristicsn (%)n (%)n (%)n (%)
Study population 204,552 (79.5) 24,870 (9.7) 27,028 (10.5) 721 (0.3) 
Median follow-up time (months), 95% CI 108.8 (108.0–109.6) 79.1 (77.1–81.0) 74.8 (73.1–76.5) 57.9 (50.2–68.6) 
Age at diagnosis 
 18–29 691 (0.3) 338 (1.4) 195 (0.7) 9 (1.3) 
 30–39 7,283 (3.6) 2,224 (8.9) 1,739 (6.4) 65 (9.0) 
 40–50 27,499 (13.4) 5,552 (22.3) 5,215 (19.3) 154 (21.4) 
 50–64 64,584 (31.6) 9,178 (36.9) 9,027 (33.4) 277 (38.4) 
 65–74 55,525 (27.1) 4,486 (18.0) 6,244 (23.1) 139 (19.3) 
 75–84 38,261 (18.7) 2,374 (9.6) 3,705 (13.7) 61 (8.5) 
 ≥85 10,709 (5.2) 718 (2.9) 903 (3.3) 16 (2.2) 
Diagnosis period 
 1990–1994 34,355 (16.8) 2,919 (11.7) 3,050 (11.3) 80 (11.1) 
 1995–1999 39,371 (19.3) 3,756 (15.1) 3,895 (14.4) 110 (15.3) 
 2000–2004 40,227 (19.7) 4,468 (18.0) 4,858 (18.0) 111 (15.4) 
 2005–2009 39,588 (19.4) 5,506 (22.1) 6,173 (22.8) 166 (23.0) 
 2010–2015 51,011 (24.9) 8,221 (33.1) 9,052 (33.5) 254 (35.2) 
Neighborhood poverty 
 Low 38,858 (19.0) 1,461 (5.9) 2,662 (9.9) 53 (7.4) 
 Lower-middle 74,304 (36.3) 3,300 (13.3) 5,986 (22.2) 112 (15.5) 
 Upper-middle 70,301 (34.4) 8,456 (34.0) 10,746 (39.8) 262 (36.3) 
 High 21,089 (10.3) 11,653 (46.9) 7,634 (28.2) 294 (40.8) 
Insurance status 
 Private 77,787 (38.0) 10,672 (42.9) 11,294 (41.8) 259 (35.9) 
 Medicaid 6,287 (3.1) 3,012 (12.1) 3,584 (13.3) 122 (16.9) 
 Medicare 73,438 (35.9) 5,347 (21.5) 5,947 (22.0) 122 (16.9) 
 Military 2,669 (1.3) 350 (1.4) 144 (0.5) 6 (0.8) 
 Indian health service 235 (0.1) 174 (0.7) 139 (0.5) 5 (0.7) 
 Uninsured 4,446 (2.2) 1,704 (6.9) 2,313 (8.6) 106 (14.7) 
 Unknown 39,690 (19.4) 3,611 (14.5) 3,607 (13.4) 101 (14.0) 
Geography 
 Urban 197,492 (96.6) 24,204 (97.3) 26,813 (99.2) 719 (99.7) 
 Large rural 3,963 (1.9) 271 (1.1) 156 (0.6) 2 (0.3) 
 Small rural 1,856 (0.9) 319 (1.3) 26 (0.1) 0 (0.0) 
 Isolated rural 1,241 (0.6) 76 (0.3) 33 (0.1) 0 (0.0) 
Disease stage 
 Localized 134,861 (65.9) 12,644 (50.8) 15,970 (59.1) 372 (51.6) 
 Regional 59,045 (28.9) 9,794 (39.4) 9,438 (34.9) 286 (39.7) 
 Distant 10,646 (5.2) 2,432 (9.8) 1,620 (6.0) 63 (8.7) 
Tumor grade 
 Low grade 106,682 (52.2) 9,074 (36.5) 12,841 (47.5) 287 (39.8) 
 High grade 61,311 (30.0) 11,683 (47.0) 9,121 (33.8) 305 (42.3) 
 Unknown 36,559 (17.9) 4,113 (16.5) 5,066 (18.7) 129 (17.9) 
HR status (2004–2015 only) 
 Positive 72,431 (73.8) 8,957 (61.1) 11,797 (72.5) 303 (69.0) 
 Negative 13,999 (14.3) 4,123 (28.1) 2,701 (16.6) 100 (22.8) 
 Unknown/missing 11,700 (11.9) 1,580 (10.8) 1,769 (10.9) 36 (8.2) 
HER2 status (2011–2015 only) 
 Positive 5,404 (12.6) 1,130 (16.2) 1,165 (15.2) 34 (15.0) 
 Negative 32,780 (76.5) 5,004 (71.9) 5,590 (72.8) 172 (75.8) 
 Borderline 1,000 (2.3) 180 (2.6) 163 (2.1) 3 (1.3) 
 Unknown/missing 3,642 (8.5) 649 (9.3) 762 (9.9) 18 (7.9) 
Surgery 
 Yes 192,313 (94.0) 21,666 (87.1) 24,885 (92.1) 622 (86.3) 
 No 11,406 (5.6) 2,918 (11.7) 1,862 (6.9) 81 (11.2) 
 Unknown 833 (0.4) 286 (1.2) 281 (1.0) 18 (2.5) 
Chemotherapy 
 Yes 58,825 (28.8) 11,325 (45.5) 9,896 (36.6) 349 (48.4) 
 No 139,766 (68.3) 12,608 (50.7) 15,908 (58.9) 338 (46.9) 
 Unknown 5,961 (2.9) 937 (3.8) 1,224 (4.5) 34 (4.7) 
Radiation 
 Yes 74,327 (36.3) 8,125 (32.7) 9,473 (35.1) 252 (35.0) 
 No 123,072 (60.2) 15,624 (62.8) 16,159 (59.8) 437 (60.6) 
 Unknown 7,153 (3.5) 1,121 (4.5) 1,396 (5.2) 32 (4.4) 
Hormone therapy 
 Yes 52,588 (25.7) 5,240 (21.1) 7,879 (29.2) 197 (27.3) 
 No 143,931 (70.4) 18,540 (74.6) 17,776 (65.8) 484 (67.1) 
 Unknown 8,033 (3.9) 1,090 (4.4) 1,373 (5.1) 40 (5.6) 
Immune therapy 
 Yes 4,555 (2.2) 669 (2.7) 688 (2.6) 17 (2.4) 
 No 198,219 (96.9) 23,972 (96.4) 25,933 (96.0) 689 (95.6) 
 Unknown 1,778 (0.9) 229 (0.9) 407 (1.5) 15 (2.1) 
Time to first treatment 
 0–30 days 102,843 (50.3) 10,042 (40.4) 9,827 (36.4) 210 (29.1) 
 31–60 days 38,407 (18.8) 5,487 (22.1) 6,973 (25.8) 199 (27.6) 
 61–90 days 8,304 (4.1) 1,832 (7.4) 2,358 (8.7) 79 (11.0) 
 >90 days 4,028 (2.0) 1,261 (5.1) 1,292 (4.8) 49 (6.8) 
 Missing 50,970 (24.9) 6,248 (25.1) 6,578 (24.3) 184 (25.5) 
NHWNHBHispanic whiteHispanic black
Characteristicsn (%)n (%)n (%)n (%)
Study population 204,552 (79.5) 24,870 (9.7) 27,028 (10.5) 721 (0.3) 
Median follow-up time (months), 95% CI 108.8 (108.0–109.6) 79.1 (77.1–81.0) 74.8 (73.1–76.5) 57.9 (50.2–68.6) 
Age at diagnosis 
 18–29 691 (0.3) 338 (1.4) 195 (0.7) 9 (1.3) 
 30–39 7,283 (3.6) 2,224 (8.9) 1,739 (6.4) 65 (9.0) 
 40–50 27,499 (13.4) 5,552 (22.3) 5,215 (19.3) 154 (21.4) 
 50–64 64,584 (31.6) 9,178 (36.9) 9,027 (33.4) 277 (38.4) 
 65–74 55,525 (27.1) 4,486 (18.0) 6,244 (23.1) 139 (19.3) 
 75–84 38,261 (18.7) 2,374 (9.6) 3,705 (13.7) 61 (8.5) 
 ≥85 10,709 (5.2) 718 (2.9) 903 (3.3) 16 (2.2) 
Diagnosis period 
 1990–1994 34,355 (16.8) 2,919 (11.7) 3,050 (11.3) 80 (11.1) 
 1995–1999 39,371 (19.3) 3,756 (15.1) 3,895 (14.4) 110 (15.3) 
 2000–2004 40,227 (19.7) 4,468 (18.0) 4,858 (18.0) 111 (15.4) 
 2005–2009 39,588 (19.4) 5,506 (22.1) 6,173 (22.8) 166 (23.0) 
 2010–2015 51,011 (24.9) 8,221 (33.1) 9,052 (33.5) 254 (35.2) 
Neighborhood poverty 
 Low 38,858 (19.0) 1,461 (5.9) 2,662 (9.9) 53 (7.4) 
 Lower-middle 74,304 (36.3) 3,300 (13.3) 5,986 (22.2) 112 (15.5) 
 Upper-middle 70,301 (34.4) 8,456 (34.0) 10,746 (39.8) 262 (36.3) 
 High 21,089 (10.3) 11,653 (46.9) 7,634 (28.2) 294 (40.8) 
Insurance status 
 Private 77,787 (38.0) 10,672 (42.9) 11,294 (41.8) 259 (35.9) 
 Medicaid 6,287 (3.1) 3,012 (12.1) 3,584 (13.3) 122 (16.9) 
 Medicare 73,438 (35.9) 5,347 (21.5) 5,947 (22.0) 122 (16.9) 
 Military 2,669 (1.3) 350 (1.4) 144 (0.5) 6 (0.8) 
 Indian health service 235 (0.1) 174 (0.7) 139 (0.5) 5 (0.7) 
 Uninsured 4,446 (2.2) 1,704 (6.9) 2,313 (8.6) 106 (14.7) 
 Unknown 39,690 (19.4) 3,611 (14.5) 3,607 (13.4) 101 (14.0) 
Geography 
 Urban 197,492 (96.6) 24,204 (97.3) 26,813 (99.2) 719 (99.7) 
 Large rural 3,963 (1.9) 271 (1.1) 156 (0.6) 2 (0.3) 
 Small rural 1,856 (0.9) 319 (1.3) 26 (0.1) 0 (0.0) 
 Isolated rural 1,241 (0.6) 76 (0.3) 33 (0.1) 0 (0.0) 
Disease stage 
 Localized 134,861 (65.9) 12,644 (50.8) 15,970 (59.1) 372 (51.6) 
 Regional 59,045 (28.9) 9,794 (39.4) 9,438 (34.9) 286 (39.7) 
 Distant 10,646 (5.2) 2,432 (9.8) 1,620 (6.0) 63 (8.7) 
Tumor grade 
 Low grade 106,682 (52.2) 9,074 (36.5) 12,841 (47.5) 287 (39.8) 
 High grade 61,311 (30.0) 11,683 (47.0) 9,121 (33.8) 305 (42.3) 
 Unknown 36,559 (17.9) 4,113 (16.5) 5,066 (18.7) 129 (17.9) 
HR status (2004–2015 only) 
 Positive 72,431 (73.8) 8,957 (61.1) 11,797 (72.5) 303 (69.0) 
 Negative 13,999 (14.3) 4,123 (28.1) 2,701 (16.6) 100 (22.8) 
 Unknown/missing 11,700 (11.9) 1,580 (10.8) 1,769 (10.9) 36 (8.2) 
HER2 status (2011–2015 only) 
 Positive 5,404 (12.6) 1,130 (16.2) 1,165 (15.2) 34 (15.0) 
 Negative 32,780 (76.5) 5,004 (71.9) 5,590 (72.8) 172 (75.8) 
 Borderline 1,000 (2.3) 180 (2.6) 163 (2.1) 3 (1.3) 
 Unknown/missing 3,642 (8.5) 649 (9.3) 762 (9.9) 18 (7.9) 
Surgery 
 Yes 192,313 (94.0) 21,666 (87.1) 24,885 (92.1) 622 (86.3) 
 No 11,406 (5.6) 2,918 (11.7) 1,862 (6.9) 81 (11.2) 
 Unknown 833 (0.4) 286 (1.2) 281 (1.0) 18 (2.5) 
Chemotherapy 
 Yes 58,825 (28.8) 11,325 (45.5) 9,896 (36.6) 349 (48.4) 
 No 139,766 (68.3) 12,608 (50.7) 15,908 (58.9) 338 (46.9) 
 Unknown 5,961 (2.9) 937 (3.8) 1,224 (4.5) 34 (4.7) 
Radiation 
 Yes 74,327 (36.3) 8,125 (32.7) 9,473 (35.1) 252 (35.0) 
 No 123,072 (60.2) 15,624 (62.8) 16,159 (59.8) 437 (60.6) 
 Unknown 7,153 (3.5) 1,121 (4.5) 1,396 (5.2) 32 (4.4) 
Hormone therapy 
 Yes 52,588 (25.7) 5,240 (21.1) 7,879 (29.2) 197 (27.3) 
 No 143,931 (70.4) 18,540 (74.6) 17,776 (65.8) 484 (67.1) 
 Unknown 8,033 (3.9) 1,090 (4.4) 1,373 (5.1) 40 (5.6) 
Immune therapy 
 Yes 4,555 (2.2) 669 (2.7) 688 (2.6) 17 (2.4) 
 No 198,219 (96.9) 23,972 (96.4) 25,933 (96.0) 689 (95.6) 
 Unknown 1,778 (0.9) 229 (0.9) 407 (1.5) 15 (2.1) 
Time to first treatment 
 0–30 days 102,843 (50.3) 10,042 (40.4) 9,827 (36.4) 210 (29.1) 
 31–60 days 38,407 (18.8) 5,487 (22.1) 6,973 (25.8) 199 (27.6) 
 61–90 days 8,304 (4.1) 1,832 (7.4) 2,358 (8.7) 79 (11.0) 
 >90 days 4,028 (2.0) 1,261 (5.1) 1,292 (4.8) 49 (6.8) 
 Missing 50,970 (24.9) 6,248 (25.1) 6,578 (24.3) 184 (25.5) 

Abbreviation: HR, hormone receptor.

Estimates of 5- and 10-year cumulative incidence of breast cancer mortality are displayed in Table 2. For all time periods, white women had significantly lower 5- and 10-year breast cancer mortality compared with black women, regardless of ethnicity. Breast cancer mortality declined for all race-ethnicity groups across each time-period (except 2005–2009 for HB). For 5-year breast cancer mortality, the percent decrease in breast cancer mortality comparing 1990–1994 to 2010–2015 was greater for all race-ethnicity combinations than NHW on both the absolute and relative (percent decrease) scale. This relationship held for absolute differences for 10-year breast cancer mortality, but black race had less of an improvement on the relative scale. The cumulative incidence function for 10-year breast cancer mortality by race-ethnicity for the overall study period is shown in Fig. 1.

Table 2.

Unadjusted 5- and 10-year estimates for the cumulative incidence of breast cancer–specific mortality by race/ethnicity according to time of diagnosis.

Cumulative incidence of 5-year BC-specific death1990–1994 to 2010–2015
1990–19941995–19992000–20042005–20092010–2015Absolute difference% decrease
Race/ethnicitya % (95% CI) % (95% CI) % (95% CI) % (95% CI) % (95% CI)   
 NHW 14.0 (13.6–14.4) 12.3 (12.0–12.6) 11.6 (11.2–11.9) 12.2 (11.8–12.6) 11.8 (11.4–12.2) 2.2% 15.7% 
 NHB 29.0 (27.3–30.8) 25.6 (24.1–27.1) 24.9 (23.5–26.3) 25.1 (23.8–26.4) 23.2 (21.9–24.6) 5.8% 20.0% 
 Hispanic White 17.0 (15.6–18.4) 14.9 (13.8–16.2) 12.9 (11.9–14.0) 12.9 (12.0–13.9) 13.4 (12.3–14.6) 3.6% 21.2% 
 Hispanic Black 27.8 (17.1–39.4) 26.1 (17.4–35.6) 15.1 (8.5–23.6) 27.8 (20.2–35.9) 22.3 (14.3–31.5) 5.5% 19.8% 
Cumulative incidence of 5-year BC-specific death1990–1994 to 2010–2015
1990–19941995–19992000–20042005–20092010–2015Absolute difference% decrease
Race/ethnicitya % (95% CI) % (95% CI) % (95% CI) % (95% CI) % (95% CI)   
 NHW 14.0 (13.6–14.4) 12.3 (12.0–12.6) 11.6 (11.2–11.9) 12.2 (11.8–12.6) 11.8 (11.4–12.2) 2.2% 15.7% 
 NHB 29.0 (27.3–30.8) 25.6 (24.1–27.1) 24.9 (23.5–26.3) 25.1 (23.8–26.4) 23.2 (21.9–24.6) 5.8% 20.0% 
 Hispanic White 17.0 (15.6–18.4) 14.9 (13.8–16.2) 12.9 (11.9–14.0) 12.9 (12.0–13.9) 13.4 (12.3–14.6) 3.6% 21.2% 
 Hispanic Black 27.8 (17.1–39.4) 26.1 (17.4–35.6) 15.1 (8.5–23.6) 27.8 (20.2–35.9) 22.3 (14.3–31.5) 5.5% 19.8% 
Cumulative incidence of 10-year BC-specific death1990–1994 to 2010–2015
1990–19941995–19992000–20042005–20092010–2015Absolute difference% decrease
Race/ethnicitya % (95% CI) % (95% CI) % (95% CI) % (95% CI) % (95% CI)   
 NHW 20.6 (20.2–21.1) 18.6 (18.2–19.0) 18.4 (18.0–18.8) 19.6 (19.1–20.1) 14.0 (13.5–14.5) 6.6% 32.04% 
 NHB 36.0 (34.2–37.9) 34.2 (32.5–35.8) 34.4 (32.8–36.0) 35.9 (34.3–37.5) 25.9 (24.3–27.5) 10.1% 28.06% 
 Hispanic White 24.5 (22.9–26.2) 22.4 (21.0–23.8) 20.1 (18.9–21.4) 22.6 (21.2–24.0) 15.8 (14.4–17.3) 8.7% 35.51% 
 Hispanic Black 36.6 (24.5–48.8) 32.5 (22.7–42.6) 25.9 (16.5–36.4) 42.7 (30.8–54.0) 28.0 (17.5–39.5) 8.6% 23.50% 
Cumulative incidence of 10-year BC-specific death1990–1994 to 2010–2015
1990–19941995–19992000–20042005–20092010–2015Absolute difference% decrease
Race/ethnicitya % (95% CI) % (95% CI) % (95% CI) % (95% CI) % (95% CI)   
 NHW 20.6 (20.2–21.1) 18.6 (18.2–19.0) 18.4 (18.0–18.8) 19.6 (19.1–20.1) 14.0 (13.5–14.5) 6.6% 32.04% 
 NHB 36.0 (34.2–37.9) 34.2 (32.5–35.8) 34.4 (32.8–36.0) 35.9 (34.3–37.5) 25.9 (24.3–27.5) 10.1% 28.06% 
 Hispanic White 24.5 (22.9–26.2) 22.4 (21.0–23.8) 20.1 (18.9–21.4) 22.6 (21.2–24.0) 15.8 (14.4–17.3) 8.7% 35.51% 
 Hispanic Black 36.6 (24.5–48.8) 32.5 (22.7–42.6) 25.9 (16.5–36.4) 42.7 (30.8–54.0) 28.0 (17.5–39.5) 8.6% 23.50% 

Abbreviation: BC, breast cancer.

aValues within year categories were all significantly different at P < 0.001 by Gray test.

Figure 1.

Ten-year cumulative incidence curves of breast cancer–related death by race-ethnicity.

Figure 1.

Ten-year cumulative incidence curves of breast cancer–related death by race-ethnicity.

Close modal

sHRs for the relative rate of 5- and 10-year breast cancer mortality for race-ethnicity groups compared with NHW according to time period are shown in Table 3. The race-ethnic disparity improved over time for all groups relative to NHW women such that for the most recent periods, there was no negative effect of Hispanic ethnicity for white women. However, for black women, Hispanic women still had a 77% increased rate of breast cancer–related death (sHR, 1.77; 95% CI, 1.21–2.59) for the most recent time period and NHB women had twice the rate of death (sHR, 2.04; 95% CI, 1.91–2.19). Similar trends were observed for 10-year breast cancer mortality. csHR for 5- and 10-year breast cancer–related deaths were virtually identical to sHRs and are provided as Supplementary Data (Supplementary Table S1).

Table 3.

sHR for 5- and 10-year cumulative incidence of breast cancer mortality by time period.

Relative cumulative incidence of 5-year BC-specific death
1990–1994 events = 5,5891995–1999 events = 5,6642000–2004 events = 5,3362005–2009 events = 5,4482010–2015 events = 5,924
sHR (95% CI)sHR (95% CI)sHR (95% CI)sHR (95% CI)sHR (95% CI)
Race/ethnicity 
 NHW ref ref ref ref ref 
 NHB 2.30 (2.13–2.49) 2.26 (2.10–2.43) 2.35 (2.19–2.53) 2.26 (2.11–2.42) 2.04 (1.91–2.19) 
 Hispanic White 1.23 (1.12–1.35) 1.22 (1.11–1.34) 1.11 (1.01–1.21) 1.04 (0.95–1.13) 1.01 (0.92–1.10) 
 Hispanic Black 2.19 (1.35–3.56) 2.21 (1.48–3.13) 1.27 (0.74–2.16) 2.68 (1.92–3.75) 1.77 (1.21–2.59) 
Relative cumulative incidence of 5-year BC-specific death
1990–1994 events = 5,5891995–1999 events = 5,6642000–2004 events = 5,3362005–2009 events = 5,4482010–2015 events = 5,924
sHR (95% CI)sHR (95% CI)sHR (95% CI)sHR (95% CI)sHR (95% CI)
Race/ethnicity 
 NHW ref ref ref ref ref 
 NHB 2.30 (2.13–2.49) 2.26 (2.10–2.43) 2.35 (2.19–2.53) 2.26 (2.11–2.42) 2.04 (1.91–2.19) 
 Hispanic White 1.23 (1.12–1.35) 1.22 (1.11–1.34) 1.11 (1.01–1.21) 1.04 (0.95–1.13) 1.01 (0.92–1.10) 
 Hispanic Black 2.19 (1.35–3.56) 2.21 (1.48–3.13) 1.27 (0.74–2.16) 2.68 (1.92–3.75) 1.77 (1.21–2.59) 
Relative cumulative incidence of 10-year BC-specific death
1990–1994 events = 7,9951995–1999 events = 8,2132000–2004 events = 7,8352005–2009 events = 7,5542010–2015 events = 5,531
sHR (95% CI)sHR (95% CI)sHR (95% CI)sHR (95% CI)sHR (95% CI)
Race/ethnicity 
 NHW ref Ref ref ref Ref 
 NHB 2.00 (1.87–2.15) 2.07 (1.94–2.21) 2.14 (2.01–2.28) 2.13 (2.01–2.27) 2.02 (1.89–2.16) 
 Hispanic White 1.22 (1.12–1.32) 1.21 (1.13–1.31) 1.09 (1.01–1.18) 1.11 (1.03–1.19) 1.01 (0.93–1.10) 
 Hispanic Black 2.02 (1.32–3.10) 1.92 (1.32–2.80) 1.37 (0.89–2.10) 2.57 (1.91–3.46) 1.85 (1.28–2.66) 
Relative cumulative incidence of 10-year BC-specific death
1990–1994 events = 7,9951995–1999 events = 8,2132000–2004 events = 7,8352005–2009 events = 7,5542010–2015 events = 5,531
sHR (95% CI)sHR (95% CI)sHR (95% CI)sHR (95% CI)sHR (95% CI)
Race/ethnicity 
 NHW ref Ref ref ref Ref 
 NHB 2.00 (1.87–2.15) 2.07 (1.94–2.21) 2.14 (2.01–2.28) 2.13 (2.01–2.27) 2.02 (1.89–2.16) 
 Hispanic White 1.22 (1.12–1.32) 1.21 (1.13–1.31) 1.09 (1.01–1.18) 1.11 (1.03–1.19) 1.01 (0.93–1.10) 
 Hispanic Black 2.02 (1.32–3.10) 1.92 (1.32–2.80) 1.37 (0.89–2.10) 2.57 (1.91–3.46) 1.85 (1.28–2.66) 

Abbreviations: BC, breast cancer; ref, reference group.

For the secondary analysis, adjusted sHRs according to race-ethnicity are depicted in Table 4. For 5-year breast cancer–specific mortality, sHRs were significantly attenuated with NHB women showing a 19% increased hazard rate of breast cancer–related death (sHR = 1.19: 95% CI, 1.12–1.27), and HB women having a 23% increased rate (sHR, 1.23; 95% CI, 1.21–2.59) compared with NHW women. The adjusted relationship for HW reversed with these women experiencing a 17% decreased rate of breast cancer–related death (sHR = 0.83: 95% CI, 0.78–0.88). Similar estimates were obtained for 10-year breast cancer mortality.

Table 4.

Adjusteda sHRs for 5- and 10-year cumulative incidence of breast cancer mortality, 2005–2015.

5-year BC-related death events = 10,74210-year BC-related death events = 13,085
sHRa (95% CI)sHRa (95% CI)
Race/ethnicity 
 NHW Ref  
 NHB 1.19 (1.12–1.27) 1.20 (1.14–1.27) 
 Hispanic White 0.79 (0.74–0.83) 0.83 (0.78–0.88) 
 Hispanic Black 1.23 (0.91–1.65) 1.29 (0.97–1.71) 
5-year BC-related death events = 10,74210-year BC-related death events = 13,085
sHRa (95% CI)sHRa (95% CI)
Race/ethnicity 
 NHW Ref  
 NHB 1.19 (1.12–1.27) 1.20 (1.14–1.27) 
 Hispanic White 0.79 (0.74–0.83) 0.83 (0.78–0.88) 
 Hispanic Black 1.23 (0.91–1.65) 1.29 (0.97–1.71) 

Abbreviations: BC, breast cancer.

aAdjusted for age, census-tract poverty level, geography, health insurance status, SEER summary stage, hormone receptor status, tumor grade, and treatment (surgery, chemotherapy, radiation, hormone therapy, and immunotherapy).

The purpose of this study was to analyze trends in survival outcomes, specifically racial-ethnic survival disparities, for women diagnosed with breast cancer in Florida over a 26-year period of observation. For all women in this study, breast cancer–specific survival improved for all racial/ethnic groups during the follow-up period. Encouragingly, in terms of the absolute improvement in breast cancer survival (and percent decrease for 5-year breast cancer mortality), slightly greater gains occurred for minority women than NHW women which is consistent with national trends (1, 2, 4, 22–28). Furthermore, any detrimental prognostic association with Hispanic ethnicity disappeared over time, which has also been reported nationally (4, 27–30). Namely, there was no disparity associated with Hispanic ethnicity for white or black Hispanic women compared to their racially concordant, non-Hispanic counterparts. However, compared with NHW women, black race (both NHB and HB) was associated with significantly inferior survival with NHB women having the worst outcomes, again, mirroring national trends (1, 22–26). Thus, although both public and private initiatives have been undertaken to address poorer outcomes in NHB (and underserved) women, additional, targeted approaches are needed to reduce the disparate burden of breast cancer in this cohort of Florida women.

The trends in reported survival disparities over time reflect the underlying influence of numerous causal mechanisms. For our primary analysis, we chose not to employ any statistical adjustment in our survival models, but rather to report the total race effect and, thus, the actual disparity that exists for racial-ethnic groups in Florida (5). Although we agree with the view that race-ethnicity is a social construct and that social and environmental factors are likely the primary causes of the poorer outcomes in NHB women, biologic characteristics of tumor cells and, to some degree, genetic factors may also play a role in breast cancer disparities (31, 32). Thus, we hypothesize that there is no true direct effect of black race on breast cancer survival but rather that black race is a proxy for other negative causal factors which drive survival disparities.

On the basis of the data in Table 1, several factors contribute to the increased mortality for NHB women. In terms of demographics, NHB women were more likely to be younger at diagnosis compared with white (NHW and HW) women as others have reported nationally (29, 33). Younger age at diagnosis is associated with more aggressive disease which negatively impacts survival (34). Socioeconomic and insurance status are predictive of breast cancer survival and a number of upstream outcomes such as stage of disease at diagnosis and receipt of treatment (35–41). In our study, NHB women were 4.5 times more likely to live in high poverty areas and over three times more likely to be uninsured compared with NHW women.

Stage of disease at diagnosis and biologic characteristics of tumors are the most important predictors of prognosis for women with breast cancer (42). As has been demonstrated in prior studies, NHB women were the least likely racial-ethnic group to be diagnosed with localized disease and the most likely to be diagnosed with distant disease (29, 42). In addition, NHB women had more aggressive tumors (high grade) than any other group which is also consistent with previous reports (42–44). We reported hormone receptor status and HER2 for the years in which this data was collected. Consistent with earlier reports, NHB women were more likely to be diagnosed with hormone receptor/HER2-negative cancers that are associated with more aggressive, less treatable disease with lower survival (3, 42, 45–47). Differences in treatment also play a role. We found that NHB women were less likely to receive surgery, radiotherapy, and hormone therapy while being more likely to receive chemotherapy and to experience delays in receiving treatment as others have reported (33, 40, 48–50). The differential distribution of all of these risk factors in NHB women compared with NHW women are likely responsible for nearly all of the poorer survival in NHB women. In fact, this was demonstrated when comparing the adjusted results, in which the HRs for black women were significantly attenuated compared with the unadjusted results. Thus, a large portion of the survival disparity in black women could be explained by age, census tract poverty, insurance status, SEER summary disease stage, hormone receptor status of tumors, tumor grade, and receipt of treatment.

The inferior survival of NHB women with breast cancer in Florida continues despite considerable financial investment to improve disparities for minority and underserved women through programs like the Florida Breast and Cervical Cancer Early Detection Program (FBCCEDP) funded by the Centers for Disease Control and Prevention. Florida has been a grantee of this program since 1994 and considerable improvements in mammography screening have occurred in black women over this time period (51). For example, compared to NHW women, although screening mammography rates were slightly lower in 2002, rates for NHB women have been equivalent to or higher than those for NHW women since 2008. In fact, for women 50 years–74 years of age in 2019, 85.0% of NHB women had received a mammogram in the prior two years compared to 77.5% of NHW women (52). Despite, these encouraging numbers, some women in need of services still fall through the cracks which could manifest in the disparities presented herein. For example, a 2018 report of the FBCCEDP found that only 8% of eligible women are receiving screening mammograms which is similar to what has been reported nationally (53, 54). Successes of interventions such as mobile mammography and tailored messaging have been shown to improve knowledge of the program and reaching eligible women (53). Analysis of programs and the policies that support them are needed to increase the reach and effectiveness of these efforts in reducing breast cancer survival differences for minority and underserved women.

Even for NHB women who receive screening mammography, the likelihood of early-stage diagnosis is not as large as that for NHW women (55). This differential impact of screening to stage shift breast cancers to less advanced disease could indicate a failure to receive or delays in diagnostic resolution that differentially impact NHB women as others have demonstrated (56–58). Finding effective ways to remove barriers to prompt resolution of suspicious findings on screening mammography and transition to treatment are areas where improvements could be made to ensure equitable access to high quality care, leading to improved prognoses for NHB women.

Strengths and limitations

Strengths of this study include the use of the FCDS to analyze trends in racial/ethnic disparities over a 26-year period for women in Florida. The FCDS has excellent case ascertainment and consistently meets the highest standards of cancer registry data (59). As such, this study was conducted with nearly the entire population of women diagnosed with breast cancer in Florida. Study limitations relate to the availability and detail of data over the study period. For example, for women diagnosed during the earlier years of this study, data were either missing or lacked detail according to: date of first treatment, hormone receptor status, HER2 status, and American Joint Commission on Cancer disease staging. Finally, the data on trends in racial-ethnic disparities in breast cancer for Florida women may not apply to women in other parts of the United States, but the reported trends in Florida are highly consistent with what has been reported on a national level (1, 22–26).

Conclusion

Cancer disparities are complex and reflect the interplay of multiple causal factors (7). Several government, foundation, and community-based efforts have been undertaken to improve disparities in breast cancer outcomes, mostly focusing on improving uptake of screening mammography in underserved women. As we have noted, in terms of increasing uptake of screening mammography for NHB women in Florida, these programs have been very successful. In addition, breast cancer survival has improved for all women and Florida with greater gains occurring in minority women. However, Black women continue to experience dramatically worse cancer survival following diagnosis than NHW women. Thus, additional efforts are needed to eliminate race as a prognostic factor for women diagnosed with breast cancer in Florida. We are currently conducting a mediation analysis of more recent cases included in this cohort to identify the most important factors driving the poorer survival outcomes in NHB women and also to evaluate regions of the state with the highest racial disparities in survival outcomes. These data will then be used to inform policies, programs, and interventions in areas of the state in the greatest need of efforts to redress inequalities in survival outcomes according to race.

No disclosures were reported.

R.B. Hines: Conceptualization, resources, data curation, software, formal analysis, funding acquisition, investigation, methodology, writing–original draft, project administration, writing–review and editing. A.M. Johnson: Conceptualization, software, methodology, writing–original draft, writing–review and editing. E. Lee: Investigation, methodology, writing–original draft, writing–review and editing. S. Erickson: Investigation, writing–original draft, writing–review and editing. S.M.M. Rahman: Conceptualization, investigation, writing–original draft, writing–review and editing.

We would like to thank the staff at the Florida Department of Health and the Florida Cancer Data System for their assistance in providing the data used in this study.

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

Note: Supplementary data for this article are available at Cancer Epidemiology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/).

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Supplementary data