Racial Differences in Follow-up of Abnormal Mammography Findings Among Economically Disadvantaged Women

Abstract

Background

In the United States and particularly South Carolina, African-American women suffer disproportionately higher mortality rates than do European-American women. The timeliness of patient adherence to the follow-up of mammographic abnormalities may influence prognosis and survival. Consequently, the purpose of the present investigation was to examine racial differences in the completion and completion time of a diagnostic work-up following a finding of a suspicious breast abnormality.

Methods

Study participants of the Best Chance Network, a state-wide service program that provides free mammography screenings to economically disadvantaged and medically underserved women, were included in the study. Racial differences in tumor characteristics and adherence to recommended work-up were tested using Chi-square and t-tests. Logistic and Cox regression modeling was used to assess the relationship between work-up completion and other factors among African-American and European-American women.

Results

Completion of the work-up was associated with the number of previous procedures and income, with no significant differences noted by race. The amount of time to completion of the work-up was influenced by previous procedures, income, and race. After accounting for completion time, African-American women were 12% less likely than European-American women to complete the recommended work-up (HR=0.88, p-value=0.01).

Conclusion

This study established a racial disparity in the time to completion of a diagnostic work-up among Best Chance Network participants. These findings highlight the importance of understanding factors associated with delays and adherence in completion of recommended work-up when breast abnormalities are detected in mammograms.

Introduction

It is well established that African-American women suffer disproportionately higher mortality rates from breast cancer than do their European-American counterparts (1–3). Previous research has done little to explain why African-American women present at much younger ages, with more aggressive disease (4–7), and experience much higher breast cancer mortality rates than their European-American counterparts(4–9). Factors related to access to screening and treatment explain only part of the excess variability (2;10–12). Many important gaps in our knowledge must be filled before we can devise the best strategies to reduce these racial disparities in breast cancer.

The disparities observed on the national level are even more striking when we focus on outcomes in South Carolina. In 2000, breast cancer incidence rates were lower than the national rates for South Carolinian women; 11% lower for European-American women and 8% lower for African-American women (1;13). However, while mortality rates for European-American women in South Carolina were 7% lower than the national US mortality rate, they were 29% higher for African-American women in South Carolina (1;13). Preliminary work in this South Carolina population have found that even at the same stage and tumor size, breast cancers in African-American women tend to be more aggressive than those in European-American women (14).

Numerous studies have shown that early detection (from methods including mammography, self-breast exams, and clinical breast exams) is one of the best ways to improve a woman’s prognosis of breast cancer (9;15–19). Not only may a woman’s prognosis of breast cancer be improved by early detection, but prognosis also may be influenced by the timeliness of a patient adhering to recommended follow-up when a breast abnormality is found (20). Patient adherence to follow-up recommendations is most likely multi-faceted. Previous research has found that socioeconomic and demographic characteristics, and certain attitudes or misconceptions about cancer are associated with delayed or incomplete follow-up (21–25). Such attitudes are common among low-income, minority, and under- or uninsured populations (17;26). Furthermore, research has shown that, compared to European-American women, African-American women experience significantly longer time intervals from an abnormal mammogram to diagnostic testing or are less likely to comply with recommended diagnostic follow-up exams within six months of an abnormal mammogram (27–29).

South Carolina’s National Breast and Cervical Cancer Early Detection Program (NBCCEDP) offers an ideal opportunity to study the relationship between race and mammography follow-up in a population that is economically disadvantaged. The NBCCEDP is a nationwide program to help uninsured or underinsured women gain access to screening services for the early detection of breast cancer. South Carolina’s NBCCEDP, commonly called the Best Chance Network, provides free mammography and cervical screenings to women aged 47 to 64 years who do not have health insurance or for whom insurance pays for hospital care only, and who are at or below 200% of federal poverty guidelines. Reflecting South Carolina’s demographics, the Best Chance Network enrolls a population which is approximately 60% African American, and the majority of whom reside in a county classified as rural by the United States Census Bureau. The purpose of this investigation was to examine the relationship between race, compliance, and total time of follow-up of suspicious breast abnormalities among women participating in the Best Chance Network.

Methods

Since the research investigation utilized de-identified data collected for non-research purposes, an exemption of approval from an Institutional Review Board was granted by the University of South Carolina Office of Research.

Study Participants

Subjects for this investigation were the Best Chance Network (BCN) participants. From its inception in 1992 until June 30, 2005, the Best Chance Network performed more than 50,000 mammography screenings. The BCN is implemented through the South Carolina Department of Health and Environmental Control and funded by the Centers for Disease Control and Prevention. The program provides services for underserved women aged 47–64 years, who are at or below 200 percent of the Federal poverty level, and do not have insurance or have insurance that covers only hospital care. The BCN provides screening services, such as mammograms and clinical breast exams, diagnostic procedures, case management, and community education on breast cancer and early detection. Eligible women are recruited into the BCN through active in-reach efforts through primary care providers from federally qualified health centers; outreach through the American Cancer Society, South-Atlantic Division; and various media mechanisms. The BCN serves South Carolinian women through outreach workers throughout the entire state. The BCN is a network of public and private partnerships and comprises more than 250 health care providers: including federally-funded primary care centers in the SC Primary Health Care Association; private physicians, including surgeons and gynecologists; laboratories, university-sponsored clinics, free clinics, regional medical centers and radiology facilities providing screening and follow-up services. Community partners include over 800 volunteers, many of whom are members of local task forces who assist in referring women to screening sites. Per BCN protocol, all participants with a breast abnormality are provided case management services which work with the participant to help her receive all diagnostic services within 60 days. Breast diagnostic work-up is covered by the BCN program.

As per the standard of care, films from all women undergoing screening mammography were classified according to the Breast Imaging Reporting and Data System (BI-RADS™)(30). Coding definitions are: 1-“negative”; 2-“benign”; 3-“probably benign”; 4-“suspicious for malignancy”; and 5-“highly suggestive of malignancy”. Subjects were included in analyses if they were African American or European American and their BI-RADS™ rating was either a 4 or 5 (n=1630), indicating a need for further diagnostic procedures. The BCN protocol does not require diagnostic work-up for a BI-RADS rating of 3. The recommended follow-up time for this category is 3 – 6 months. As such, women with this BI-RAD rating were excluded from the analysis. The study sample consisted of 729 African-American women and 901 European-American women. A retrospective cohort study design was utilized to ascertain if additional diagnostic procedures including mammographic views, ultrasound, or biopsy were undertaken. For women with a pathologically diagnosed breast carcinoma, we retrieved additional information such as tumor histology, behavior, stage, and size (n=407). Among women who underwent a breast biopsy, 187 were European American and 220 were African American.

Covariates

Women were considered to have complete follow-up if their recommended work-up was recorded as complete by the Best Chance Network. As per Best Chance Network guidelines, a complete work-up indicates that the diagnostic testing is complete, and that final diagnosis (whether benign or malignant) and date of final diagnosis are known. For those diagnosed with breast cancer, stage at diagnosis and tumor size also were recorded at the time of final diagnosis. An incomplete work-up was defined as a curtailed planned work-up, pending work-up, refused work-up, or if the woman was lost to follow-up. If a woman severed her relationship with the Best Chance Network program and had her diagnostic work-up performed by another provider, her work-up was defined as refused. A woman was considered lost to follow-up if she died, moved before her work-up started, or when tracking efforts were attempted but failed. The date, at which this determination was made, was used for our analyses.

Total yearly family income, insurance status, previous mammogram and breast symptoms were self-reported at the time of the woman’s visit with the Best Chance Network. Breast symptoms included a lump, bloody nipple discharge, dimpling, ulceration, or inflammation of the skin. Diagnostic procedures included additional mammographic views, repeated clinical breast exams or surgical consultations, breast ultrasounds, breast biopsy or lumpectomies, fine needle aspirations, and other procedures such as stereotactic localization, magnetic resonance imaging, and metastatic work-up such as a bone survey.

Tumor size, stage, and behavior were reported for women with a diagnosis of breast cancer. Tumor size was categorized into the following groups: 0 to 1 centimeter (cm), 1 to 2 cm, 2 to 5 cm, greater than 5 cm, and unknown. Tumor stage was reported according to the American Joint Committee on Cancer (AJCC)(31). Tumor behavior was defined as either in-situ or invasive.

Statistical Methods

Descriptive statistics, stratified by race, were calculated for all demographic and breast screening variables. Differences between African-American and European-American women were analyzed using the χ² test for categorical measures and a t-test for continuous measures. All p-values were two-tailed and significance was assessed at α= 0.05 Type I error rate.

Logistic regression was conducted to model the relationship between race and whether recommended workup was completed. Other covariates included in these models were age, healthcare provider, number of procedures, income, and insurance type. Because there were a finite number of mammography providers, we had to consider the possibility of correlation among observations within the provider variable. After investigating several parametric structures for within-provider correlation, all testing concluded that the pooled model was the most appropriate approach where inference adjusted for possible within-provider correlation using the empirical (modified sandwich) variance estimator (32).

Kaplan-Meier survival curves were compared using the log-rank test for equality. Cox proportional hazard modeling was the primary statistical method used for analysis of follow-up time. Those women with incomplete work-ups were categorized as censored observations. Two measures of time, the number of days between the first mammogram and the date that the status of the work-up was finalized and the number of days between the first clinical breast exam and the date that the status was finalized, were analyzed in this investigation. For women who completed their work-up, the date that the status was finalized corresponds to the date of a final diagnosis (either benign or malignant). A final diagnosis was documented only after the individual had completed all recommended diagnostic procedures including additional mammographic views, ultrasound, and biopsy (if recommended). For those women with incomplete work-up, the date corresponds to the date when their status (incomplete, refused, lost-to-follow up, or pending) was assessed.

As in our logistic models, we evaluated the possible correlation of repeated observations within each mammography provider for our estimated Cox models. Further testing indicated that the pooled (independence) Cox regression model was the most appropriate method (33). The proportional hazards assumption was tested and the assumption was not violated for the main predictor variable of race (p-value = 0.11).

Results

Study population characteristics are displayed in Table 1. The mean age of the women was 52 years old and was not significantly different between African-American and European-American women. However, income levels varied by race, with African-American women having a mean income of $1,294 less than European-American women (p=0.0003). African-American women were also less likely to have insurance as compared to their European-American counterparts. The majority of women did not experience breast symptoms at the time of their appointment. African-American women were more likely to have an abnormal clinical breast exam than European-American women. For both groups of women, 91% had completed follow-up of abnormal breast findings. Additionally, there was not a significant difference in the number of diagnostic procedures performed or in the number of previous mammograms performed between African-American and European-American women.

Table 1.

Demographic Characteristics of the Study Population According to Race: Best Chance Network

	African American (n = 729)	European American (n = 901)
	% (Number) Mean (SD)	% (Number) Mean (SD)	p-value*
Demographic Characteristics
Income*	$5,887.60 ($6,838.50)	$7,181.50 ($7,706.00)	0.0003
Age at diagnosis	52 (9.3)	52 (10.18)	0.46
Breast Symptoms
Yes	20 (184)	24 (174)	0.089
No	77 (695)	75 (545)
Unknown	3 (10)	1 (10)
Clinical Breast Exam Result
Normal	51 (463)	45 (329)	0.04
Abnormal	44 (396)	50 (363)
Not needed	5 (42)	5 (37)
Previous Mammogram
Yes	52 (471)	48 (352)	0.27
No	46 (413)	50 (362)
Unknown	2 (17)	2 (15)
Status of Mammography Final Diagnosis
Work-up complete	91 (817)	91 (662)	0.93
Refused, pending, incomplete	9 (84)	9 (67)
Insurance Status**
None	78 (701)	73 (527)	0.008
Hospitalization only	6 (51)	5 (37)
Unreported	16 (149)	22 (165)
Number of procedures
0	7 (48)	7 (64)	0.28
1	48 (354)	44 (396)
2	29 (215)	33 (300)
3	12 (86)	13 (119)
>4	4 (26)	3 (22)
Final Diagnosis
In Situ	4 (40)	5 (38)	0.73
Invasive	20 (180)	20 (149)
Breast cancer not diagnosed/unknown	76 (681)	75 (542)

^*p < 0.05 based on t-test test or chi-square test as appropriate between African American and European American

The clinical characteristics of those women who were diagnosed with breast cancer within the Best Chance Network are shown in Table 2. Among women diagnosed with breast cancer, there was not a difference between African-American and European-American women with regard to tumor size, tumor stage, or tumor behavior. For both groups, there was a larger percentage of tumors greater than 2 centimeters and less than 5 centimeters and the tumors were more likely to be invasive than in-situ.

Table 2.

Clinical Characteristics of Women Diagnosed with Breast Cancer According to Race: Best Chance Network

	African American (n = 220)	European American (n = 187)
	% (Number)	% (Number)	p-value*
Clinical Characteristics
Tumor Size
0 to 1 cm	8 (18)	8 (15)	0.54
>1 to 2 cm	20 (43)	22 (42)
>2 to 5 cm	30 (65)	29 (54)
>5 cm	15 (33)	10 (18)
Unknown	27 (61)	31 (58)
Tumor Behavior
In-situ	18 (40)	20 (38)	0.58
Invasive	82 (180)	80 (149)
Tumor Stage
Stage I/Local	23 (50)	21 (39)	0.90
Stage II, III/Regional	44 (98)	48 (90)
Stage IV/Distant	4 (9)	4 (8)
Unknown	29 (63)	27 (50)

^*p < 0.05 based on chi-square test between African American and European American

The relationship between the various covariates available and overall completion of recommended work-up is displayed in Table 3. Regression analyses showed that a complete work-up was associated with the number of previous procedures and income, but was not significantly associated with age, type of insurance, or race. Women with one previous procedure were over three times more likely to complete their recommended follow-up as compared to women not having previous procedures (95% CI: 1.71, 6,27). For each doubling of income, the odds of completing the work-up increased by 10% (95% CI: 1.03, 1.19).

Table 3.

Multivariate Logistic Analyses of Factors Influencing Complete Recommended Workup^*

Variable	Incomplete Work-up	Complete Work-up	Relative Risk (CI) †
Age	151	1479	0.98 (0.95, 1.01)
Income	151	1479	1.10 (1.03, 1.19)
Number of procedures
1	141	721	1.00
2 or more	10	758	3.28 (1.71, 6.27)
Insurance
No insurance	92	1136	1.00
Hospital only Insurance	59	343	0.51 (0.20, 1.30)
Race‡
EA	84	817	1.00
AA	67	662	1.29 (0.65, 2.55)

^*Time was measured as the number of days between the first mammogram and the date of final diagnosis.

^†CI: Confidence Interval

^‡Race described as EA = European American; AA = African American

The Kaplan Meier curves comparing the number of days between the first mammogram and the date of final status by race are depicted in Figure 1. The graph of the time estimates for race showed little difference between African-American and European-American women, although the log-rank test for equality of survival functions was marginally significant (p-value=0.056). The median work-up time from the first mammogram to the final status was 34 days for African-American women and 28 days for European-American women.

Figure 1.

The Kaplan Meier curves of the time (in days) between the first clinical breast exam and the date of final status are depicted in Figure 2. Interestingly, we noted a significant difference in the time to work-up completion between African-American and European-American women (median time = 44 days for African Americans and 40 days for European Americans, p-value=0.02).

Figure 2.

Table 4 contains the Cox Hazard analysis of factors influencing time to completion of the recommended work-up. In this analysis, time was measured as the number of days between the first mammogram and the date that final status was determined. Cox analyses suggested that after adjusting for age, income, number of previous procedures, and insurance, African-American women were 11% less likely to complete their work-up than European-American women (p-value=0.09). In addition, results indicated that for each previous procedure women were 30% more likely to complete the work-up (p-value<0.0001). With each doubling of income, the likelihood of completing the recommended work-up was 1.01 times higher (p-value=0.017). Women with insurance were 1.11 times more likely to complete the recommended work-up as compared to women without insurance or hospitalization insurance only (p-value=0.05). Age was not significantly associated with completion of the work-up.

Table 4.

Survival Analysis of Factors Influencing Completion of Recommended Workup From First Mammogram

Variable	Incomplete Work-up	Complete Work-up	Hazard Ratio (CI)*
Age	151	1479	1.00 (0.99, 1.01)
Income	151	1479	1.01 (1.00, 1.02)
Number of procedures
1	141	721	1.00
2 or more	10	758	1.29 (1.21, 1.39)
Insurance
No insurance	92	1136	1.00
Hospital only Insurance	59	343	1.11 (0.99, 1.24)
Race†
EA	84	817	1.00
AA	67	662	0.89 (0.77, 1.02)

^*CI: Confidence Interval

^†Race described as EA = European American; AA = African American

Table 5 contains results from the Cox analysis of factors influencing time to completion of recommended work-up when time was assessed from clinical breast exam to the date that status of the work-up was finalized. Analyses indicated that, after adjusting for age, income, number of previous procedures, and insurance, African-American women were 12% less likely to complete their work-up than European-American women (p-value=0.01). In addition, these results indicate that women having more than one previous procedure were 32% more likely to complete the work-up (p-value<0.0001) than women who had no previous procedures. Age, income, and insurance status were not significantly associated with completion of the work-up.

Table 5.

Survival Analysis of Factors Influencing Completion of Recommended Workup from First Clinical Breast Examination

Variable	Incomplete Work-up	Complete Work-up	Hazard Ratio (CI)*
Age	151	1479	0.99 (0.95, 1.00)
Income	151	1479	1.01 (1.99, 1.02)
Number of procedures
1	141	721	1.00
2 or more	10	758	1.32 (1.25, 1.39)
Insurance
No insurance	92	1136	1.00
Hospital only Insurance	59	343	1.07 (0.94, 1.22)
Race†
EA	84	817	1.00
AA	67	662	0.88 (0.79, 0.97)

^*CI: Confidence Interval

^†Race described as EA = European American; AA = African American

Discussion

Among economically-disadvantaged women, race was not significantly associated with overall completion of mammographic work-up. However, we did find evidence for racial disparities in the time between the first abnormal clinical breast examination and determination of final status. After accounting for time, African-American women were significantly less likely to complete their mammographic work-up than European-American women.

Interestingly, when time was measured in the number of days between the mammogram and the date of final status, a significant effect of race was no longer evident. Because the clinical breast examination typically precedes the diagnostic mammogram, these findings suggest that the racial differences may occur early in the process. Although the exact protocol will vary according to the clinical site where the patient receives care, the clinical breast examination usually will be completed by a different provider than the provider of the mammographic services. Consequently, structural and environmental factors that could affect the time between the clinical breast exam and the mammogram are communication to the patient by the provider, lengthy scheduling delays, proximity of the mammography clinic to the patient (which could be especially pertinent in a rural setting), and availability of transportation (23;34–38). Conceptualizing these factors in light of the racial differences that we found suggest several interesting areas for further research (24;24;38–40). Diagnostic delays also may be a result, in part, of deficits in the patient-provider relationship. Patient trust in the provider has been shown to be positively correlated with willingness to seek care and adhere to treatment recommendations (41). Furthermore, a lack of a usual provider is associated with inadequate follow-up after an abnormal mammogram (42). It has been noted that physician perceptions tended to be more negative regarding lower-income and minority women compared to higher-income and non-minority women (37;41;43). Therefore, African-American women may not adhere to recommendations concerning breast abnormalities because of a lack of trust with their health care provider or a lack of a consistent provider due to lower socioeconomic status. It is puzzling to find that even in the population where all services are provided free of charge, income influences a woman’s adherence to recommended follow-up. While the BCN does provide all diagnostic services, up until 2000 there were no provisions for no-cost services once a woman was diagnosed with a breast malignancy. Consequently, this may have influenced a woman’s decision to follow up after a doctor’s recommendation because of her inability to pay or her fear about paying for additional medical services should she be diagnosed with breast cancer. This is consistent with literature showing that numerous socioeconomic factors are associated with delayed follow-up of an abnormal mammogram or clinical breast exam including: low household income, other cost issues, and transportation problems (21–24;34;40;44–51).

Delayed follow-up of breast abnormalities could result in detecting the breast cancer at a later stage, thus influencing a woman’s prognosis and mortality of the disease. Richards and colleagues found in a meta-analysis that a delayed diagnosis of breast cancer of as little as 3 months was associated with lower survival than those with prompt follow-up (52). Likewise, they found that three- to six-month delays were clearly associated with increased tumor size, advanced disease stage, and poorer long-term prognosis.

In a previous investigation, our research team examined the effect of delayed diagnosis on mortality in the Best Chance Network(53). With this investigation, one of the intervals examined was the time between the suspicious mammogram or CBE and breast cancer diagnosis. Interestingly, we found no significant association between the diagnosis interval and mortality nor any significant interaction between race and the diagnosis interval. Combined with our findings, this suggests that future studies should focus on the time period between clinical breast examination and mammography.

As with any epidemiological investigation, our study had some limitations worth noting. Data elements from the NBCCEDP are dictated by the Centers for Disease Control and Prevention. While we had a wealth of information with which to work, we did not have information about beliefs about screening, health literacy, patient-provider communication and relationship, or system failures. This information would be useful to collect in future studies in order to provide a more comprehensive analysis of our findings. In addition, due to small cell sizes, we were forced to collapse the outcome variable ‘status of the work-up’ from 4 to 2 levels (refused, lost-to-follow-up, or pending were condensed to incomplete). This may have led to possible misclassification bias as the factors associated with a refusal, loss to follow-up, or pending work-up may be different. Nevertheless, one would expect such misclassification of the outcome to bias the findings toward the null value thereby strengthening the claim of a true association based on the observed relationship between race and time between the first CBE and date of final status.

This research study has many strengths. The Best Chance Network targets rural, medically underserved women of South Carolina, serving a population that is approximately 70% African-American. Hence, we were able to study a population that is chronically under-represented in the scientific literature. In addition, because the Best Chance Network is a state-wide program, we were able to follow women over time regardless of where they may have received treatment, thus minimizing losses to follow-up (e.g., a woman would not be lost upon moving to another city). Due to the cohort design of the program and our study, we were able to account for past screening history in the investigation, which does appear to affect the time to completion of the diagnostic work-up.

In conclusion, we found evidence for a racial disparity in the time to completion of a diagnostic work-up among low-income women enrolled in South Carolina’s NBCCEDP, the Best Chance Network. Given the target population of the BCN, we believe that these results are particularly applicable to economically disadvantaged AA women living in rural areas. The finding that no disparities existed in the overall completion of the work-up are also an encouraging evaluation of the NBCCEDP, because it suggests that the program is making progress toward eliminating racial disparities in breast cancer and offer areas for strengthening (i.e., in decreasing the total time interval). Overall, these findings highlight the importance of understanding factors associated with these delays. In addition, they suggest several areas for potential policy changes such as additional support to the BCN program to allow the expansion of services. Improving patient adherence to follow-up recommendations and decreasing the time lag between the detection of breast abnormalities and the date of completion may decrease breast cancer mortality rates.