Background: In a racially and ethnically diverse sample of recently diagnosed urban patients with breast cancer, we examined associations of patient, tumor biology, and mammography facility characteristics on the probability of symptomatic discovery of their breast cancer despite a recent prior screening mammogram.

Methods: In the Breast Cancer Care in Chicago study, self-reports at interview were used to define patients as having a screen-detected breast cancer or having symptomatic awareness despite a recent screening mammogram (SADRS), in the past 1 or 2 years. Patients with symptomatic breast cancer who did not report a recent prior screen were excluded from these analyses. Characteristics associated with more aggressive disease [estrogen receptor (ER)– and progesterone receptor (PR)–negative status and higher tumor grade] were abstracted from medical records. Mammogram facility characteristics that might indicate aspects of screening quality were defined and controlled for in some analyses.

Results: SADRS was more common among non-Hispanic black and Hispanic than among non-Hispanic white patients (36% and 42% vs. 25%, respectively, P = 0.0004). SADRS was associated with ER/PR-negative and higher-grade disease. Patients screened at sites that relied on dedicated radiologists and sites that were breast imaging centers of excellence were less likely to report SADRS. Tumor and facility factors together accounted for two thirds of the disparity in SADRS (proportion mediated = 70%, P = 0.02).

Conclusion: Facility resources and tumor aggressiveness explain much of the racial/ethnic disparity in symptomatic breast cancer among recently screened patients.

Impact: A more equitable distribution of high-quality screening would ameliorate but not eliminate this disparity. Cancer Epidemiol Biomarkers Prev; 24(10); 1599–606. ©2015 AACR.

Mammography screening is effective in the early detection of breast cancer and the balance of the evidence suggests that it improves survival and reduces mortality from breast cancer (1–4). Early detection enables breast cancer to be diagnosed at an early stage when treatment is most effective (1, 4, 5). Despite reportedly similar mammography utilization rates among racial and ethnic groups in the United States (6), non-Hispanic black women both nationally (7, 8) and in Chicago die from breast cancer at a higher rate than non-Hispanic whites (9). Symptomatic tumors tend to display characteristics of more aggressive disease (10–14). Additional research in Chicago suggests that there exist disparities in access to high-quality mammography that may contribute to disparities in breast cancer outcomes in Chicago. In one study, minority women and those without private insurance were found to be less likely than non-Hispanic white women and women with private insurance to obtain screening mammography at facilities with characteristics suggesting high-quality screening (15). These characteristics included whether a facility was an academic medical center, relied exclusively on breast imaging specialists to read mammograms, and used digital mammography. Another study found that the probability of potentially missed detection (defined as an actionable lesion identified upon expert mammogram review in the same breast and quadrant as the subsequently diagnosed breast cancer) was greater among minority and socioeconomically disadvantaged women compared to non-Hispanic white women and those from socioeconomically advantaged backgrounds (16). Taken together, these findings suggest that the disparity in breast cancer mortality might relate to a combination of differences in patient, tumor biology, and healthcare quality factors.

In this study, symptomatic awareness despite a recent screen (SADRS) is defined as a patient reported symptomatic awareness despite reporting a recent screening mammogram in the past 1 or 2 years. We examined associations of patient, tumor biology, and healthcare quality factors on SADRS and the extent to which tumor biology and healthcare quality factors might account for racial/ethnic disparities in SADRS.

Patients for this study participated in the “Breast Cancer Care in Chicago (BCCC)” study of newly diagnosed female patients between 30 and 79 years of age at diagnosis, who resided in Chicago, had a first primary in situ or invasive breast cancer, were diagnosed between March 1, 2005 and February 31, 2008, and self-identified as either non-Hispanic white, non-Hispanic black, or Hispanic (17, 18). The study was approved by the Institutional Review Board at the University of Illinois at Chicago. All diagnosing facilities in the greater Chicago area (N = 56) were visited on a monthly basis and all eligible newly diagnosed cases were ascertained by review of pathology and tumor registry records at each hospital. Patients were further screened for eligibility and scheduled for interviews if eligible and interested. The 90-minute interview was administered either in English or Spanish as appropriate using computer-assisted personal interview (CAPI) procedures. The final interview response rate was 56% representing 989 completed interviews among eligible patients (397 non-Hispanic white, 411 non-Hispanic black, 181 Hispanic; response rates 51%, 59%, and 66%, respectively). Of patients who were interviewed, 86% (n = 849) consented to medical record reviews to obtain information on aspects of diagnosis and treatment. More details of the BCCC study have previously been reported (17, 18).

SADRS

Breast cancer mode of detection was based on the response to the question: “How was the problem noticed for the very first time?” with possible response categories being: (i) I found something, (ii) My partner/spouse found something, (iii) A doctor or nurse found something during a physical examination, (iv) mammogram, (v) ultrasound, (vi) MRI, and (vii) lung/chest X-ray. The method of detection was defined as “symptomatic” if the woman reported that she or her spouse/partner found something or that a healthcare provider found something during physical examination and as “screen-detected” if the disease was detected through a mammogram in the absence of symptoms (no patients in the analysis sample reported discovery through an ultrasound, MRI, or chest X-ray). All of the women were asked to report when their last mammogram had occurred before awareness of the problem later diagnosed as breast cancer. Patients were defined as having a screen-detected breast cancer or having SADRS in the past 1 or 2 years. Patients with symptomatic breast cancer in the absence of a recent prior screen were excluded from these analyses. The final sample size was 750 with respect to SADRS in the past 2 years and 674 with respect to SADRS in the past 1 year (76 patients reporting a screen more than 1 but less than 2 years before detection were excluded from this latter definition).

Analysis variables

Race/ethnicity.

Patients were categorized as (i) white, non-Hispanic, (ii) black, non-Hispanic, and (iii) Hispanic or Latino. Ethnicity was defined through separate self-identification of Hispanic ethnicity and race. Ethnicity was defined as Hispanic if the patient self-identified as Hispanic, reported a Latin American country of origin, or reported a Latin American country of origin for both biologic parents.

Socioeconomic factors.

Socioeconomic position (SEP) was defined by 4 variables. At the individual level, attained education was reported in years and annual household income was reported in categories of below $20,000, between $20,000–$50,000, and greater than $50,000. At the census tract level for the individual's home address, concentrated disadvantage was defined using variables from the 2000 U.S. Census on the percentage of families in the census tract with incomes below the poverty line, percentage of families receiving public assistance, percentage of persons unemployed, and percentage of female-headed households with children. Concentrated affluence was defined on the basis of the percentage of families with incomes of $75,000 or more, percentage of adults with a college education or more, and percentage of the civilian labor force in professional and managerial occupations. For each measure, an equally weighted sum across the relevant variables was calculated and then standardized to have a mean of 0 and a SD of 1.

Tumor aggressiveness factors and breast density.

Breast density, hormone receptor status, histologic grade, and stage at diagnosis were abstracted from patient medical records. Breast density was abstracted from mammography reports and defined using the BIRADS categories of fatty, scattered fibroglandular, heterogeneously dense, and extremely dense. Hormone receptor status was defined as positive if the tumor contained either estrogen (ER) or progesterone receptors (PR) or negative if negative for both receptor types. Histologic grade was defined as low, intermediate, and high. Stage at diagnosis was categorized into American Joint Committee on Cancer (AJCC) categories of 0, 1, 2, and 3 and 4 combined. For descriptive analyses, stage was dichotomized as late (stage 2, 3, 4) versus early (stage 0, 1). In situ tumors (stage 0) were excluded from some analyses.

Facility characteristics.

We used data from a mammography facility survey conducted in 2007 to define facility characteristics potentially associated with quality of mammography. With respect to the mammogram facility that detected the breast cancer (screen-detected) or the prior screening mammogram facility (symptomatic awareness), we defined facility reliance on dedicated breast imagers as none, partial, or sole reliance (15). We also characterized facilities in terms of their designation as an American College of Radiology Breast Imaging Center of Excellence (19). The disproportionate share DSH program in state Medicaid programs provides supplemental payments to facilities with high levels of uninsured and Medicaid patients (20). We defined facilities as DSH facilities if they were located within hospitals that were classified as such by the state of or if they were non-hospital sites that were public health facilities.

Statistical analyses

We tabulated the distribution of patient, tumor biologic, and facility characteristics by race/ethnicity (Table 1) and the prevalence of SADRS by patient, tumor biologic, and facility characteristics (Table 2) and reported associated P values from Pearson χ2 tests. Next, we estimated a series of nested logistic regression models and conducted likelihood ratio tests for the inclusion of variables representing either biologic or healthcare quality domains in the models (Table 3). For type 1 analysis, we started with a baseline model of SADRS containing age and race/ethnicity as covariates, then added either tumor biological or healthcare facility covariates, and conducted likelihood ratio tests to compare these models to the baseline model. For type 3 analyses, we began with a full model containing age, race/ethnicity, tumor biologic, and healthcare facility covariates, then removed either the tumor biologic or healthcare facility covariates as a group, and conducted likelihood ratio tests. P values from likelihood ratio tests <0.05 were interpreted as indicating that a specific domain contributed to the prediction of SADRS. We ran separate analysis for 2 definitions of SADRS: SADRS within 1 year and within 2 years.

Table 1.

Racial/ethnic differences in patient, facility, and tumor characteristics among breast cancer patients with a recent screen before their diagnosis in the BCCC study (2005–2008)

Non-Hispanic white (N = 314)Non-Hispanic black (N = 304)Hispanic (N = 132)
N%%%P
 SADRSa     0.0004 
  No 507 75 64 58  
  Yes 243 25 36 42  
 Stage at diagnosis     <0.0001 
  Stage 0, 1 423 75 60 54  
  Stages 2, 3, 4 227 25 40 46  
 Age, y     0.2848 
  25–49 169 24 20 26  
  50–59 246 32 33 34  
  60–79 335 44 47 40  
 Breast density     0.9437 
  Fatty 33  
  Scattered fibroglandular 208 45 46 36  
  Heterogeneously dense 171 34 36 42  
  Extremely dense 63 14 13 13  
Socioeconomic factors 
 Health insurancea     <0.0001 
  None 71 13 20  
  Public 117 23 23  
  Private 562 93 64 57  
 Education     <0.0001 
  <12 135 21 44  
  12 133 13 21 20  
  >12 479 82 57 36  
 Income     <0.0001 
  <20K 181 10 35 35  
  20–50K 343 41 51 52  
  >50K 203 49 13 13  
 Disadvantage     <0.0001 
  >1 SD below mean 113 32  
  Within 1 SD of the mean 493 67 56 85  
  >1 SD above mean 142 43  
 Affluence     <0.0001 
  >1 SD below mean 49 11 11  
  Within 1 SD of the mean 542 59 82 84  
  >1 SD above mean 157 41  
Facility characteristics 
 Designation     <0.0001 
  Not DSH 547 92 66 54  
  DSH 187 34 46  
 Designation     0.0220 
  Not a breast center of excellence 480 59 69 69  
  Breast center of excellence 257 41 31 31  
 University-based     <0.0001 
  No 545 59 78 92  
  Yes 205 41 22  
 Reliance on dedicated radiologists     0.0180 
  None 137 14 19 27  
  Partial 475 66 65 54  
  Sole reliance 138 20 16 20  
Tumor aggressiveness factors 
 ER/PR status     <0.0001 
  Either or both positive 461 91 75 82  
  Double negative 96 25 18  
 Histologic grade (1, 2, 3)     0.0085 
  Low 129 30 19 12  
  Moderate 237 36 43 48  
  High 209 33 38 40  
Non-Hispanic white (N = 314)Non-Hispanic black (N = 304)Hispanic (N = 132)
N%%%P
 SADRSa     0.0004 
  No 507 75 64 58  
  Yes 243 25 36 42  
 Stage at diagnosis     <0.0001 
  Stage 0, 1 423 75 60 54  
  Stages 2, 3, 4 227 25 40 46  
 Age, y     0.2848 
  25–49 169 24 20 26  
  50–59 246 32 33 34  
  60–79 335 44 47 40  
 Breast density     0.9437 
  Fatty 33  
  Scattered fibroglandular 208 45 46 36  
  Heterogeneously dense 171 34 36 42  
  Extremely dense 63 14 13 13  
Socioeconomic factors 
 Health insurancea     <0.0001 
  None 71 13 20  
  Public 117 23 23  
  Private 562 93 64 57  
 Education     <0.0001 
  <12 135 21 44  
  12 133 13 21 20  
  >12 479 82 57 36  
 Income     <0.0001 
  <20K 181 10 35 35  
  20–50K 343 41 51 52  
  >50K 203 49 13 13  
 Disadvantage     <0.0001 
  >1 SD below mean 113 32  
  Within 1 SD of the mean 493 67 56 85  
  >1 SD above mean 142 43  
 Affluence     <0.0001 
  >1 SD below mean 49 11 11  
  Within 1 SD of the mean 542 59 82 84  
  >1 SD above mean 157 41  
Facility characteristics 
 Designation     <0.0001 
  Not DSH 547 92 66 54  
  DSH 187 34 46  
 Designation     0.0220 
  Not a breast center of excellence 480 59 69 69  
  Breast center of excellence 257 41 31 31  
 University-based     <0.0001 
  No 545 59 78 92  
  Yes 205 41 22  
 Reliance on dedicated radiologists     0.0180 
  None 137 14 19 27  
  Partial 475 66 65 54  
  Sole reliance 138 20 16 20  
Tumor aggressiveness factors 
 ER/PR status     <0.0001 
  Either or both positive 461 91 75 82  
  Double negative 96 25 18  
 Histologic grade (1, 2, 3)     0.0085 
  Low 129 30 19 12  
  Moderate 237 36 43 48  
  High 209 33 38 40  

aP values for these 2 variables and for all binary variables are from a general χ2 test, whereas P values for the remaining ordered variables are from a test for trend via nominal logistic regression with race/ethnicity as a dependent variable. P > 0.15 is suppressed.

Table 2.

Patient, facility, and tumor aggressiveness factors and symptomatic awareness despite a recent screen in the BCCC study (2005–2008)

SADRS
Within the past yearWithin the past 2 years
n (%)Pn (%)P
 Ethnicitya  0.0004  0.0004 
  Non-Hispanic white 288 (18)  314 (25)  
  Non-Hispanic black 267 (27)  304 (36)  
  Hispanic 119 (36)  132 (42)  
 Age, y  0.0036  0.0002 
  25–49 147 (30)  169 (39)  
  50–59 215 (30)  246 (39)  
  60–79 312 (19)  335 (24)  
 Breast density  0.0005  0.0016 
  Fatty 29 (14)  33 (24)  
  Scattered fibroglandular 190 (18)  208 (25)  
  Heterogeneously dense 154 (32)  171 (39)  
  Extremely dense 56 (34)  63 (41)  
Socioeconomic factors 
 Health insurancea  0.7550  0.6840 
  None 63 (29)  71 (37)  
  Public 104 (25)  117 (33)  
  Private 507 (24)  562 (32)  
 Education  0.4806  0.4000 
  <12 121 (26)  135 (34)  
  12 117 (26)  133 (35)  
  >12 433 (24)  479 (31)  
 Income  0.095  0.0976 
  <20 K 164 (28)  181 (35)  
  20–50 K 302 (26)  343 (35)  
  >50 K 186 (20)  203 (27)  
 Disadvantage  0.2316  0.1172 
  >1 SD below mean 106 (21)  113 (26)  
  Within 1 SD of the mean 439 (25)  493 (33)  
  >1 SD above mean 127 (28)  142 (35)  
 Affluence  0.1124  0.0464 
  >1 SD below mean 45 (29)  49 (35)  
  Within 1 SD of the mean 480 (26)  542 (34)  
  >1 SD above mean 147 (20)  157 (25)  
Facility characteristics 
 Designation  0.1076  0.0500 
  Not DSH 496 (24)  547 (31)  
  DSH 164 (30)  187 (39)  
 Designation  0.0104  0.0536 
  Not a breast center of excellence 433 (28)  480 (35)  
  Breast center of excellence 228 (19)  257 (28)  
 University-based  0.0188  0.0069 
  No 485 (27)  545 (35)  
  Yes 189 (19)  205 (25)  
 Reliance on dedicated radiologists  0.0026  0.0017 
  None 122 (35)  137 (42)  
  Partial 248 (24)  475 (32)  
  Sole reliance 128 (19)  138 (25)  
Tumor aggressiveness factors 
 ER/PR status  0.00006  0.0011 
  Either or both positive 413 (22)  461 (30)  
  Double negative 88 (42)  96 (47)  
 Histologic grade (1, 2, 3)  0.0018  0.0020 
  Low 119 (17)  129 (23)  
  Moderate 212 (21)  237 (30)  
  High 187 (32)  209 (39)  
SADRS
Within the past yearWithin the past 2 years
n (%)Pn (%)P
 Ethnicitya  0.0004  0.0004 
  Non-Hispanic white 288 (18)  314 (25)  
  Non-Hispanic black 267 (27)  304 (36)  
  Hispanic 119 (36)  132 (42)  
 Age, y  0.0036  0.0002 
  25–49 147 (30)  169 (39)  
  50–59 215 (30)  246 (39)  
  60–79 312 (19)  335 (24)  
 Breast density  0.0005  0.0016 
  Fatty 29 (14)  33 (24)  
  Scattered fibroglandular 190 (18)  208 (25)  
  Heterogeneously dense 154 (32)  171 (39)  
  Extremely dense 56 (34)  63 (41)  
Socioeconomic factors 
 Health insurancea  0.7550  0.6840 
  None 63 (29)  71 (37)  
  Public 104 (25)  117 (33)  
  Private 507 (24)  562 (32)  
 Education  0.4806  0.4000 
  <12 121 (26)  135 (34)  
  12 117 (26)  133 (35)  
  >12 433 (24)  479 (31)  
 Income  0.095  0.0976 
  <20 K 164 (28)  181 (35)  
  20–50 K 302 (26)  343 (35)  
  >50 K 186 (20)  203 (27)  
 Disadvantage  0.2316  0.1172 
  >1 SD below mean 106 (21)  113 (26)  
  Within 1 SD of the mean 439 (25)  493 (33)  
  >1 SD above mean 127 (28)  142 (35)  
 Affluence  0.1124  0.0464 
  >1 SD below mean 45 (29)  49 (35)  
  Within 1 SD of the mean 480 (26)  542 (34)  
  >1 SD above mean 147 (20)  157 (25)  
Facility characteristics 
 Designation  0.1076  0.0500 
  Not DSH 496 (24)  547 (31)  
  DSH 164 (30)  187 (39)  
 Designation  0.0104  0.0536 
  Not a breast center of excellence 433 (28)  480 (35)  
  Breast center of excellence 228 (19)  257 (28)  
 University-based  0.0188  0.0069 
  No 485 (27)  545 (35)  
  Yes 189 (19)  205 (25)  
 Reliance on dedicated radiologists  0.0026  0.0017 
  None 122 (35)  137 (42)  
  Partial 248 (24)  475 (32)  
  Sole reliance 128 (19)  138 (25)  
Tumor aggressiveness factors 
 ER/PR status  0.00006  0.0011 
  Either or both positive 413 (22)  461 (30)  
  Double negative 88 (42)  96 (47)  
 Histologic grade (1, 2, 3)  0.0018  0.0020 
  Low 119 (17)  129 (23)  
  Moderate 212 (21)  237 (30)  
  High 187 (32)  209 (39)  

aP values for these 2 variables and for all binary variables are from a general χ2 test, whereas P values for the remaining ordered variables are from a test for trend via logistic regression. P > 0.15 is suppressed.

Table 3.

Comparison of nested multivariable models of symptomatic awareness despite a recent screen in the BCCC study (2005–2008)

SADRS
Within the past yearWithin the past 2 years
nPanPa
Type 1 analysis 
 Add socioeconomic factorsb 453 0.9671 503 0.9262 
 Add facility characteristicsc 453 0.0498 503 0.0147 
 Add tumor aggressiveness factorsd 453 0.0001 503 0.0003 
Type 3 analysis 
 Remove socioeconomic factors 453 0.9270 503 0.8776 
 Remove facility characteristics 453 0.0606 503 0.0116 
 Remove tumor aggressiveness factors 453 0.0002 503 0.0005 
SADRS
Within the past yearWithin the past 2 years
nPanPa
Type 1 analysis 
 Add socioeconomic factorsb 453 0.9671 503 0.9262 
 Add facility characteristicsc 453 0.0498 503 0.0147 
 Add tumor aggressiveness factorsd 453 0.0001 503 0.0003 
Type 3 analysis 
 Remove socioeconomic factors 453 0.9270 503 0.8776 
 Remove facility characteristics 453 0.0606 503 0.0116 
 Remove tumor aggressiveness factors 453 0.0002 503 0.0005 

aFrom a χ2 likelihood ratio test comparing 2 nested models. P > 0.15 is suppressed.

bIndividual-level income and education and census tract disadvantage and affluence.

cStatus as DSH and as a breast imaging center of excellence, reliance on dedicated breast radiologists.

dTumor grade and ER/PR status.

To assess potential mediation of ethnic disparities in SADRS by socioeconomic, tumor biologic or healthcare facility characteristics, we compared rescaled coefficients for these selected domains of interest using the method described by Karlson and Holm (Table 4; ref. 21). To model variation in quality across facilities in a more granular fashion, we modeled individual facilities as fixed effects, after collapsing several facilities with small numbers of breast cancers into a single group, resulting in a variable with 39 groups. All analyses were conducted using SAS version 9 (SAS Institute) and Stata statistical software, version 13 (Stata Corp), and all tests were 2-sided with a threshold for significance of 0.05.

Table 4.

Proportionate reduction in the racial/ethnic disparity in symptomatic awareness despite a recent screen

Symptomatic awareness despite a recent screen
Within the past year (n = 453)Within the past 2 years (n = 503)
DomainsProportionateaPbProportionateaPb
Domains modeled one at a time 
 Socioeconomic status 4% 0.837 −2% 0.719 
 Facility characteristics 22% 0.15 24% 0.09 
 Individual facilityc 42% 0.199 55% 0.05 
 Tumor aggressiveness 26% 0.005 18% 0.02 
Domains modeled together 45% 0.01 39% 0.01 
 Facility characteristics 21%  23%  
 Tumor aggressiveness 24%  16%  
Domains modeled together 61% 0.09 70% 0.02 
 Individual facilityc 31%  50%  
 Tumor aggressiveness 30%  20%  
Symptomatic awareness despite a recent screen
Within the past year (n = 453)Within the past 2 years (n = 503)
DomainsProportionateaPbProportionateaPb
Domains modeled one at a time 
 Socioeconomic status 4% 0.837 −2% 0.719 
 Facility characteristics 22% 0.15 24% 0.09 
 Individual facilityc 42% 0.199 55% 0.05 
 Tumor aggressiveness 26% 0.005 18% 0.02 
Domains modeled together 45% 0.01 39% 0.01 
 Facility characteristics 21%  23%  
 Tumor aggressiveness 24%  16%  
Domains modeled together 61% 0.09 70% 0.02 
 Individual facilityc 31%  50%  
 Tumor aggressiveness 30%  20%  

aProportionate reduction in the ethnic disparity in symptomatic awareness despite a recent screen, based on the method of rescaled coefficients.

bP value from a test of difference between the reduced model and the full model containing all mediators of interest. P > 0.15 is suppressed.

cIndicator variables for individual mammogram facilities. All models were adjusted for age at diagnosis as a continuous variable.

Distribution of patient characteristics

The final sample for analysis included 750 patients with data on SADRS within 2 years, and a subset of 674 patients had data with respect to SADRS within 1 year.

Stage at diagnosis and SADRS among recently screened patients

As expected, patients reporting SADRS in the past 1 or 2 years were 43 and 42 percentage points more likely to be diagnosed at a later stage than screen-detected patients, respectively (P < 0.0001). After excluding in situ breast cancers, patients reporting SADRS in the past 1 or 2 years were 41 and 40 percentage points more likely to be diagnosed at a later stage than screen-detected patients, respectively (P < 0.0001).

Racial/ethnic differences in patient, facility, and tumor aggressiveness factors

Compared with non-Hispanic white patients, non-Hispanic black and Hispanic patients were more likely to be of lower socioeconomic status (less likely to be privately insured, less income and education, and more likely to live in more disadvantaged and less affluent census tracts; Table 1). Racial and ethnic minorities were also more likely to be screened at DSH and public facilities and less likely to be screened at breast imaging centers of excellence, university-based facilities, or at facilities with dedicated breast radiologists. Racial and ethnic minorities were also more likely to be diagnosed with more aggressive-appearing ER/PR-negative and higher-grade tumors (Table 1). Breast density was available from medical records for 475 patients, and there were no differences in the distribution of breast density by race/ethnicity (P = 0.944).

Patient, facility, and tumor aggressiveness factors as predictors of SADRS

There were significant differences in SADRS by race/ethnicity, age, tumor biology, and facility characteristics (Table 2). We discuss results relative to SADRS within the past 2 years, but the trends were similar with respect to SADRS within the past year. In this population of recently screened patients, non-Hispanic black and Hispanic patients were more likely than non-Hispanic whites to report SADRS (36% and 42% vs. 25%, respectively, P = 0.0004). Greater breast density was positively associated with SADRS, and earlier age at diagnosis, ER/PR-negative, and higher-grade disease were each positively associated with SADRS. Women screened in lower resourced institutions (DSH, non–university-based, not designated as a breast imaging center of excellence, or facilities without dedicated breast radiologists) were more likely to report SADRS compared with women seen in higher resourced institutions. Patients with higher incomes were less likely to report SADRS, but education and health insurance were not associated with SADRS (Table 2).

Multivariable nested models of SADRS

In type 1 and 3 analyses, we grouped the socioeconomic, tumor aggressiveness, and facility characteristics into separate domains and conducted likelihood ratio tests for nested models. The tumor aggressiveness domain was retained as a significant predictor of SADRS in both type 1 and 3 analyses for SADRS within the past 1 or 2 years. The facility characteristics domain was retained in both type 1 and 3 analyses for SADRS within the past 2 years. For SADRS within the past 1 year, the facility characteristics domain was retained in type 1 analysis (P = 0.0498) and marginally retained in type 3 analysis (P = 0.0606; Table 3).

Proportionate reduction in the racial and racial/ethnic disparity in SADRS

In age-adjusted models of the racial/ethnic disparity in SADRS within the past 1 or 2 years, inclusion of socioeconomic variables did not affect the estimated disparity. Inclusion of facility characteristics marginally accounted for nearly one fourth (22% and 24%) of the disparity in SADRS within the past 1 or 2 years, respectively (Table 4). When we replaced facility characteristics with indicator variables for each separate facility, facility differences accounted for 42% (P = 0.199) and 55% (P = 0.048) of the disparity, respectively. Inclusion of tumor aggressiveness factors (ER/PR status and grade) significantly reduced the disparity by 26% (P = 0.005) and 18% (P = 0.02), respectively. Inclusion of both facility characteristics and tumor aggressiveness factors reduced the racial/ethnic disparity by 45% and 39% (P = 0.01 for both). When we replaced facility characteristics with indicator variables for each separate facility, facility differences and tumor aggressiveness factors reduced the racial/ethnic disparity by 61% (P = 0.09) and 70% (P = 0.02), respectively (Table 4).

In a sample of patients with breast cancer who reported having received a screening mammogram within 1 or 2 years of their breast cancer detection, non-Hispanic black and Hispanic women were more likely than non-Hispanic whites to report symptomatic awareness which prompted the detection of their breast cancer. Both tumor biologic factors and healthcare facility characteristics were associated with SADRS, and tumor biologic factors and healthcare facility characteristics together accounted for roughly two-thirds of the racial/ethnic disparity in SADRS. The definition of SADRS used here is similar to the definition of interval breast cancer except that our results are based on patient self-reports, whereas interval breast cancer is typically defined from medical records or other sources of documentation. Here, patients reported how they came to discover their breast cancer and their mammography use before becoming aware of the problem later diagnosed as breast cancer. In addition to a missed finding on a screening mammogram, SADRS could be the result of an abnormal screening mammogram finding in a woman who did not receive appropriate diagnostic follow-up and which subsequently evolved into a symptomatic breast cancer. This second possibility distinguishes SADRS from interval breast cancer: the definition of SADRS used in the present study is broader and encompasses both interval breast cancer and symptomatic breast cancer developing as a result of delayed diagnostic follow-up.

Prior comparisons of symptomatic versus screen-detected breast cancers have often included both women with a recent prior screening history and women without a recent prior history, and these studies are not directly comparable to ours (10–12, 22–27). Several studies have examined the disparities with respect to interval breast cancer as an outcome on either tumor biologic factors or healthcare quality factors (13, 14, 28–32), but none of these studies provided a comprehensive picture of the multiple factors contributing to the disparity in symptomatic detection. These studies used a more rigorous definition of interval breast cancer, based on documented screening mammogram dates and results, than our definition of SADRS that relied on patient reported mode of detection and timing of prior screening imaging. Therefore, we need to carefully consider the potential impact of self-report biases/errors on our associations with SADRS.

Breast cancer that is diagnosed in younger women tends to be more aggressive and more likely to evade detection with screening mammography than in older women (14, 30). In our sample of recently screened patients, as expected, SADRS was more likely in younger women. Likewise, tumor characteristics associated with aggressiveness of disease appeared to influence mode of detection in our study. Patients with ER/PR-negative or high-grade tumors were more likely to report SADRS than patients with ER/PR-positive and lower grade tumors. Similarly, patients in our study with heterogeneously or extremely dense breasts were more likely to report SADRS than patients with fatty or scattered fibroglandular breasts. This finding is consistent with what has been previously reported in other studies examining the role of breast density on cancers occurring between screens (interval cancer; refs. 32–34).

We also found that factors associated with quality of screening appear to influence mode of detection among screened patients. Prior studies have found associations between radiologist characteristics, practice characteristics, image characteristics, patient characteristics, and likelihood of interval cancer/mammography accuracy (5, 28, 35–39). Screening performance can depend on whether facilities offer screening alone versus screening and diagnostic mammograms or multimodality screening and diagnosis, the extent to which facilities rely on breast imaging specialists, and frequency of audit reviews (35–39).

We used 4 variables to model healthcare quality associated with SADRS, and these were each associated with SADRS in the expected direction. Patients screened at sites that relied on dedicated radiologists, that were breast imaging centers of excellence, and that were not DSH facilities were each less likely to report SADRS. Together, these variables accounted for about one fourth of the racial/ethnic disparity ion SADRS. When we modeled variation in healthcare quality in a more detailed manner by using individual facility indicators, facility variation appeared to account for about half of the racial/ethnic disparity in SADRS.

Prior studies conducted in Chicago suggest the existence of a differential access to quality mammography services between minority women and non-Hispanic white women. In a study assessing the distribution of mammography services by race/ethnicity and health insurance in Chicago, minority women were less likely than non-Hispanic whites to obtain mammograms at university-based facilities, at facilities that relied exclusively on breast imaging specialists, and at facilities where digital mammography was available (15). Previous analyses of a small subsample of patients from the current study found that nearly half of prior screening mammogram images that were originally interpreted as normal showed some evidence of a potentially missed cancer, that is, an actionable lesion in the same breast and quadrant as the subsequently diagnosed breast cancer (16). Our results are consistent with these findings and could offer some insight into the outcome disparities in breast cancer in Chicago.

Method of detection and timing of the most recent prior mammogram were both self-reported. We went to great lengths to get accurate self-reports of method of detection through careful design of the question based on prior cognitive interviews and by allowing for a range of possibilities for how a patient might become aware of the problem later diagnosed as breast cancer. We attempted to limit any tendency for overreporting of screen detection due to socially desirable reasons by asking first about whether the problem was discovered by the patient, her partner, or her doctor via clinical breast examination, before mentioning potential discovery through mammography or other imaging modalities. The definition of a recent prior screening mammogram was also based on self-reports; thus, forward-telescoping of the date of most recent screening examination likely caused some women without a recent prior mammogram to be included in the definition of SADRS. If this process was nondifferential with respect to characteristics examined, it would tend to attenuate associations observed. However, if, as prior research suggests, ethnic minorities were more likely than non-Hispanic whites to forward-telescope prior mammography (40–42), then any estimated disparity would tend to be inflated. However, the apparent mediation of the disparity in SADRS by tumor aggressiveness variables (abstracted from medical records) and facility characteristics suggest that at least part of the disparity is real and is due to differences in these domains.

To our knowledge this is the first study to examine socioeconomic status, facility characteristics and tumor biology and their potential role in mediating a racial and ethnic disparity in screen detection of breast cancer. Our results implicate both facility resources and tumor aggressiveness in SADRS in explaining the racial/ethnic disparity in SADRS in this study. Results suggest that elimination of inequities in access to high-quality mammography screening would reduce the racial/ethnic disparity in symptomatic breast cancer among screened women by as much as half.

Regular, high-quality mammography is even more important for patients at greater risk for more aggressive forms of breast cancer (e.g., racial/ethnic minorities), as tumors in these women are harder to detect and more likely to arise as interval breast cancer or SADRS. Racial/ethnic minorities are also more likely to be screened at lower resource facilities that may be associated with increased SADRS. Factors potentially amenable to improvement are largely those related to quality of mammography and they include encouraging facilities to recruit breast imaging specialists and breast focused radiologists, requiring rigorous auditing as part of the Mammography Quality Standards Act, and mammography-focused continuing education for mammography technologists and radiologists. MQSA inspects mammogram images only once every 3 years and only a small sample of images that are handpicked in advance by the facility. Lower performing institutions might be able to pass image quality inspection regardless of actual practice, and these might serve a disproportionate share of ethnic minority patients. Illinois recently became the first state in the nation to implement a statewide mammography quality surveillance program tied to increased Medicaid reimbursement, with the goal of improving the quality of mammography and timeliness of follow-up (43).

Differences in facility characteristics accounted for much of the disparity in symptomatic breast cancer among recently screened patients, and a more equitable distribution of high-quality screening would reduce this disparity. At the same time, the tendency for more aggressive breast cancer in non-Hispanic black and Hispanic patients resulted in a roughly equal contribution to explaining the disparity. Our results suggest that even if a more equitable distribution of high-quality screening were available, a substantial disparity would remain in symptomatic breast cancer among recently screened patients.

No potential conflicts of interest were disclosed.

Conception and design: M. Mortel, G.H. Rauscher

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): A.M. Murphy, R.B. Warnecke

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): M. Mortel, G.H. Rauscher, A.M. Murphy, R.B. Warnecke

Writing, review, and/or revision of the manuscript: M. Mortel, G.H. Rauscher, A.M. Murphy, K. Hoskins, R.B. Warnecke

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): M. Mortel, A.M. Murphy, R.B. Warnecke

The authors thank the Illinois women diagnosed with breast cancer whose information was reported to the Illinois State Cancer Registry, thereby making this research possible.

This work was supported by two grants from the National Cancer Institute at the NIH to the University of Illinois at Chicago to G.H. Rauscher (grants 1P50CA106743 and 2P50CA106743) and the Agency for Health Research and Quality to G.H. Rauscher (grant 1-R01 HS018366-01A1).

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.

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