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Black–white differences in receipt and completion of adjuvant chemotherapy among breast cancer patients in a rural region of the US

  • Epidemiology
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An Invited Commentary to this article was published on 08 March 2012

Abstract

Recent breast cancer treatment studies conducted in large urban settings have reported racial disparities in the appropriate use of adjuvant chemotherapy. This article presents the first focused evaluation of black–white differences in receipt and completion of chemotherapy for breast cancer in a primarily rural region of the United States. We performed chart abstraction on initial therapy received by 868 women diagnosed with Stages I, IIA, IIB, or IIIA breast cancer in 2001–2003 in southwest Georgia (SWGA). For chemotherapy, information collected included treatment plan, dates of delivery, concordance between therapy planned and received, and date and reasons for end of treatment. The patient’s age at diagnosis, race, marital status, insurance coverage, hormone receptor status, comorbidities, socioeconomic status, urban/rural status, treatment site, and distance to the site were also collected. Following univariate analyses, we used multivariable logistic regression modeling to examine the impact of race on the likelihood of (1) receiving chemotherapy and (2) completing planned chemotherapy. For patients terminating chemotherapy prematurely, the reasons were documented. The results showed that the unadjusted black–white difference in receipt of chemotherapy (48.3 vs. 36.0%) was significant, but in the multivariable analysis the black–white odds ratio (OR = 1.18) was not. While the unadjusted black–white difference (92.0 vs. 87.8%) in completing chemotherapy was not significant, in multivariable models black race was positively associated with completing care (p ranging from 0.032 to 0.087 and OR, correspondingly, from 2.16 to 2.64). The impact of race on completing chemotherapy was influenced by marital status, with a significant black–white difference for patients not married (OR = 4.67), but no difference for those married (OR = 1.06). We find compelling racial differences in this largely rural region—with black breast cancer patients receiving or completing chemotherapy at rates that equal or exceed white patients. Further investigation is warranted, both in SWGA and in other rural regions.

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Notes

  1. The 33 counties comprising SWGA had a census-estimated population near the time of this study of about 724,000. About 82% of SWGA residents live in non-metropolitan areas. The median household income is about 72% of the U.S. average, and about 21% of the population lives below the Federal poverty line, compared with 12.4% nationally. About 38% of the population is African-American [15].

  2. While characterizations of invasive “early stage” breast cancer vary in the literature, with some papers including only stages I and II, the definition here is consistent with current National Cancer Institute terminology (http://www.cancer.gov/dictionary?expand=E). Throughout, we combine stages IIA and IIB into a single stage II, given sample size constraints.

  3. These study sites and their approximate total annual case volume (all cancer types) during the study period are as follows: Phoebe Cancer Center in Albany, 1,000–1,100; Pearlman Cancer Center at South Georgia Medical Center in Valdosta, 400–600; Singletary Oncology Center at Archbold Medical Center in Thomasville, 400–600; and Tift Regional Oncology Center at Tift Medical Center in Tifton, 300–400 [16]. During the study period, the nearest National Cancer Institute-designated cancer center was at least 180 miles away for virtually any SWGA resident.

  4. The Southwest Georgia Cancer Coalition, based in Albany, assisted Emory University investigators in developing effective working relationships with the four cancer centers. The fifth study team was managed by the GCCR Regional Coordinator for Southwest Georgia.

  5. Specifically, we adhered to Harrell’s recommendation that for models with a binary response variable, the number of predictors should generally not exceed m/10, where m = min (N 1, N 2), and N 1 and N 2 are the marginal frequencies of the binary outcome [18].

  6. Because the patient’s distance from her home to primary site of treatment may be regarded as an important attribute of the site itself, we estimated alternative versions of the model that excluded, in turn, the distance variables and the site-of-care variables. The results (available from the authors upon request) confirmed the robustness of the model reported in Table 2. The site-of-care variables remained significant when distance was omitted; the distance variables remained insignificant when the site-of-care variables were omitted; and the statistical performance of the other variables in these model variants were consistent with the results in Table 2. The persistence of this site-of-care effect, after controlling for multiple patient-level factors, is noteworthy and suggests that the style of medical oncology practice may have differed systematically across these CoC-approved cancer centers during the 2001–2003. However, the fact that only four cancer centers (plus 23 smaller hospitals) are involved inherently limits our ability to generalize about site effects.

  7. For logistic models with interaction terms, SAS 9.2 computes a 95% confidence interval for the odds ratio for the variable of interest in the interaction term (e.g., race), conditional on the assumed value of the other variable in the (two-way) interaction term (e.g., marital status), rather than p values for the individual direct effect and interaction terms included in the regression. See note c in Table 4.

  8. When the 7 primary reasons for termination were collapsed into clinical reasons (3) and other patient-related reasons (4), there was still no significant black-white difference (p = 0.241, using Pearson’s exact test, and p = 0.432 after application of the Yates correction for small expected cell sizes).

  9. Adams et al. [25] found that enrollment rates in the Georgia Medicaid program for women diagnosed with breast cancer increased from 2.8 per 1,000 person-months in the pre-BCCPTA period (January 1999–June 2001) to 4.5 per 1,000 person-months post-BCCPTA (July 2001–December 2005). Georgia’s relatively expansive program provides Medicaid coverage for uninsured women under age 65 regardless of whether they are diagnosed with breast (or cervical) cancer through the CDC’s National Breast and Cervical Cancer Early Detection Program or by non-NBCCEDP providers.

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Acknowledgments

Funding was made possible by cooperative agreement #U48 DP000043 for the Emory Prevention Research Center, from the Centers for Disease Control and Prevention. Additional support was provided by the National Cancer Institute through cancer center support grant 5P30CA138292 to Winship Cancer Institute of Emory University. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention or the National Cancer Institute.

Conflict of interest

In connection with this manuscript, none of the authors has a conflict of interest to disclose.

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Authors and Affiliations

  1. Department of Health Policy and Management, Rollins School of Public Health, Emory University, Atlanta, GA, USA

    Joseph Lipscomb

  2. Winship Cancer Institute of Emory University, Atlanta, USA

    Joseph Lipscomb, Theresa W. Gillespie, Michael Goodman & Kevin C. Ward

  3. Department of Surgery, Woodruff Health Sciences Center, Emory University, Atlanta, USA

    Theresa W. Gillespie

  4. Atlanta VA Medical Center, Decatur, GA, USA

    Joseph Lipscomb & Theresa W. Gillespie

  5. Georgia Center for Cancer Statistics, Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA

    Michael Goodman, A. Blythe Ryerson & Kevin C. Ward

  6. Division of Cancer Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA, USA

    Lisa C. Richardson, Lori A. Pollack & A. Blythe Ryerson

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Correspondence to Joseph Lipscomb.

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Lipscomb, J., Gillespie, T.W., Goodman, M. et al. Black–white differences in receipt and completion of adjuvant chemotherapy among breast cancer patients in a rural region of the US. Breast Cancer Res Treat 133, 285–296 (2012). https://doi.org/10.1007/s10549-011-1916-1

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