Skip to main content

Advertisement

SpringerLink
Log in

Racial disparities in individual breast cancer outcomes by hormone-receptor subtype, area-level socio-economic status and healthcare resources

  • Epidemiology
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

Abstract

The aim of the study is to determine the influence of area-level socio-economic status and healthcare access in addition to tumor hormone-receptor subtype on individual breast cancer stage, treatment, and mortality among Non-Hispanic (NH)-Black, NH-White, and Hispanic US adults. Analysis was based on 456,217 breast cancer patients in the SEER database from 2000 to 2010. Multilevel and multivariable-adjusted logistic and Cox proportional hazards regression analysis was conducted to account for clustering by SEER registry of diagnosis. NH-Black women had greater area-level access to healthcare resources compared with women of other races. For instance, the average numbers of oncology hospitals per million population in counties with NH-Black, NH-White, and Hispanic women were 8.1, 7.7, and 5.0 respectively; average numbers of medical doctors per million in counties with NH-Black, NH-White, and Hispanic women were 100.7, 854.0, and 866.3 respectively; and average number of Ob/Gyn in counties with NH-Black, NH-White, and Hispanic women was 155.6, 127.4, and 127.3, respectively (all p values <0.001). Regardless, NH-Black women (HR 1.39, 95 % CI 1.36–1.43) and Hispanic women (HR 1.05, 95 % CI 1.03–1.08) had significantly higher breast cancer mortality compared with NH-White women even after adjusting for hormone-receptor subtype, area-level socio-economic status, and area-level healthcare access. In addition, lower county-level socio-economic status and healthcare access measures were significantly and independently associated with stage at presentation, surgery, and radiation treatment as well as mortality after adjusting for age, race/ethnicity, and HR subtype. Although breast cancer HR subtype is a strong, important, and consistent predictor of breast cancer outcomes, we still observed significant and independent influences of area-level SES and HCA on breast cancer outcomes that deserve further study and may be critical to eliminating breast cancer outcome disparities.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Howlader N, Noone AM, Krapcho M, Garshell J, Miller D, Altekruse SF, Kosary CL, Yu M, Ruhl J, Tatalovich Z, Mariotto A, Lewis DR, Chen HS, Feuer EJ, Cronin KA (eds) (2015) SEER cancer statistics review, 1975–2012. Vol based on Nov 2014 SEER data submission. National Cancer Institute, Bethesda

  2. McCarthy AM, Yang J, Armstrong K (2015) Increasing disparities in breast cancer mortality from 1979 to 2010 for US black women aged 20 to 49 years. Am J Public Health 105(Suppl 3):S446–S448. doi:10.2105/AJPH.2014.302297

    Article  PubMed  PubMed Central  Google Scholar 

  3. Aizer AA, Wilhite TJ, Chen MH, Graham PL, Choueiri TK, Hoffman KE, Martin NE, Trinh QD, Hu JC, Nguyen PL (2014) Lack of reduction in racial disparities in cancer-specific mortality over a 20-year period. Cancer 120(10):1532–1539. doi:10.1002/cncr.28617

    Article  PubMed  Google Scholar 

  4. Akinyemiju TF, Soliman AS, Johnson NJ, Altekruse SF, Welch K, Banerjee M, Schwartz K, Merajver S (2013) Individual and neighborhood socioeconomic status and healthcare resources in relation to black–white breast cancer survival disparities. J Cancer Epidemiol 2013:490472. doi:10.1155/2013/490472

    Article  PubMed  PubMed Central  Google Scholar 

  5. Jadav S, Rajan SS, Abughosh S, Sansgiry SS (2015) The role of socioeconomic status and health care access in breast cancer screening compliance among hispanics. J Public Health Manag Pract 21(5):467–476. doi:10.1097/PHH.0000000000000235

    Article  PubMed  Google Scholar 

  6. Sheppard VB, Oppong BA, Hampton R, Snead F, Horton S, Hirpa F, Brathwaite EJ, Makambi K, Onyewu S, Boisvert M, Willey S (2015) Disparities in breast cancer surgery delay: the lingering effect of race. Ann Surg Oncol 22(9):2902–2911. doi:10.1245/s10434-015-4397-3

    Article  PubMed  Google Scholar 

  7. Akinyemiju TF, Vin-Raviv N, Chavez-Yenter D, Zhao X, Budhwani H (2015) Race/ethnicity and socio-economic differences in breast cancer surgery outcomes. Cancer Epidemiol 39(5):745–751. doi:10.1016/j.canep.2015.07.010

    Article  PubMed  Google Scholar 

  8. Tao L, Gomez SL, Keegan TH, Kurian AW, Clarke CA (2015) Breast cancer mortality in African-American and non-hispanic white women by molecular subtype and stage at diagnosis: a population-based study. Cancer Epidemiol Biomarkers Prev 24(7):1039–1045. doi:10.1158/1055-9965.EPI-15-0243

    Article  CAS  PubMed  Google Scholar 

  9. Parise CA, Caggiano V (2015) The influence of socioeconomic status on racial/ethnic disparities among the ER/PR/HER2 breast cancer subtypes. J Cancer Epidemiol 2015:813456. doi:10.1155/2015/813456

    Article  PubMed  PubMed Central  Google Scholar 

  10. Akinyemiju T, Moore JX, Altekruse SF (2015) Breast cancer survival in African-American women by hormone receptor subtypes. Breast Cancer Res Treat. doi:10.1007/s10549-015-3528-7

    PubMed  Google Scholar 

  11. Boyle P (2012) Triple-negative breast cancer: epidemiological considerations and recommendations. Ann Oncol. doi:10.1093/annonc/mds187

    Google Scholar 

  12. Edge S, Byrd DR, Compton CC, Fritz AG, Greene FL, Trotti A (2011) AJCC cancer staging manual, 7th edn. American Joint Committee on Cancer, Chicago, IL

    Google Scholar 

  13. Howlader N, Altekruse SF, Li CI, Chen VW, Clarke CA, Ries LAG, Cronin KA (2014) US incidence of breast cancer subtypes defined by joint hormone receptor and HER2 status. J Natl Cancer Inst 106(5):1–8. doi:10.1093/jnci/dju055

    Article  Google Scholar 

  14. Ihemelandu CU, Leffall LD, Dewitty RL, Naab TJ, Mezghebe HM, Makambi KH, Adams-Campbell L, Frederick WA (2007) Molecular breast cancer subtypes in premenopausal and postmenopausal African-American women: age-specific prevalence and survival. J Surg Res 143:109–118. doi:10.1016/j.jss.2007.03.085

    Article  CAS  PubMed  Google Scholar 

  15. Ihemelandu CU, Naab TJ, Mezghebe HM, Makambi KH, Siram SM, Leffall LD, DeWitty RL, Frederick WA (2008) Basal cell-like (triple-negative) breast cancer, a predictor of distant metastasis in African American women. Am J Surg 195:153–158. doi:10.1016/j.amjsurg.2007.09.033

    Article  PubMed  Google Scholar 

  16. Newman L (2014) Breast cancer disparities: high-risk breast cancer and African ancestry. Surg Oncol Clin N Am 23:579–592

    Article  PubMed  Google Scholar 

  17. Parise CA, Caggiano V (2014) Breast cancer survival defined by the ER/PR/HER2 subtypes and a surrogate classification according to tumor grade and immunohistochemical biomarkers. J Cancer Epidemiol 2014:11. doi:10.1155/2014/469251

    Article  Google Scholar 

  18. Akinyemiju TF, Pisu M, Waterbor JW, Altekruse SF (2015) Socioeconomic status and incidence of breast cancer by hormone receptor subtype. Springer 4:508. doi:10.1186/s40064-015-1282-2

    Article  Google Scholar 

  19. Feinglass J, Rydzewski N, Yang A (2015) The socioeconomic gradient in all-cause mortality for women with breast cancer: findings from the 1998 to 2006 national cancer data base with follow-up through 2011. Ann Epidemiol 25(8):549–555. doi:10.1016/j.annepidem.2015.02.006

    Article  PubMed  Google Scholar 

  20. Kish JK, Yu M, Percy-Laurry A (2014) Altekruse SF (2014) Racial and ethnic disparities in cancer survival by neighborhood socioeconomic status in Surveillance, Epidemiology, and End Results (SEER) registries. J Natl Cancer Inst Monogr 49:236–243. doi:10.1093/jncimonographs/lgu020

    Article  Google Scholar 

  21. Parise CA, Caggiano V (2013) Disparities in race/ethnicity and socioeconomic status: risk of mortality of breast cancer patients in the California Cancer Registry, 2000–2010. BMC Cancer 13:449. doi:10.1186/1471-2407-13-449

    Article  PubMed  PubMed Central  Google Scholar 

  22. Silber JH, Rosenbaum PR, Clark AS, Giantonio BJ, Ross RN, Teng Y, Wang M, Niknam BA, Ludwig JM, Wang W, Even-Shoshan O, Fox KR (2013) Characteristics associated with differences in survival among black and white women with breast cancer. JAMA 310(4):389–397. doi:10.1001/jama.2013.8272

    Article  CAS  PubMed  Google Scholar 

  23. Shariff-Marco S, Yang J, John EM, Kurian AW, Cheng I, Leung R, Koo J, Monroe KR, Henderson BE, Bernstein L, Lu Y, Kwan ML, Sposto R, Vigen CL, Wu AH, Keegan TH, Gomez SL (2015) Intersection of race/ethnicity and socioeconomic status in mortality after breast cancer. J Community Health 40(6):1287–1299. doi:10.1007/s10900-015-0052-y

    Article  PubMed  Google Scholar 

  24. Roseland ME, Pressler ME, Lamerato LE, Krajenta R, Ruterbusch JJ, Booza JC, Schwartz K, Simon MS (2015) Racial differences in breast cancer survival in a large urban integrated health system. Cancer 121(20):3668–3675. doi:10.1002/cncr.29523

    Article  CAS  PubMed  Google Scholar 

  25. Akinyemiju TF, Soliman AS, Yassine M, Banerjee M, Schwartz K, Merajver S (2012) Healthcare access and mammography screening in Michigan: a multilevel cross-sectional study. Int J Equity Health 11:16. doi:10.1186/1475-9276-11-16

    Article  PubMed  PubMed Central  Google Scholar 

  26. Fan JX, Hanson HA, Zick CD, Brown BB, Kowaleski-Jones L, Smith KR (2014) Geographic scale matters in detecting the relationship between neighbourhood food environments and obesity risk: an analysis of driver license records in Salt Lake County, Utah. BMJ Open 4(8):e005458. doi:10.1136/bmjopen-2014-005458

    Article  PubMed  PubMed Central  Google Scholar 

  27. Subramanian SV, Chen JT, Rehkopf DH, Waterman PD, Krieger N (2006) Comparing individual- and area-based socioeconomic measures for the surveillance of health disparities: a multilevel analysis of Massachusetts births, 1989–1991. Am J Epidemiol 164(9):823–834. doi:10.1093/aje/kwj313

    Article  CAS  PubMed  Google Scholar 

  28. Krieger N, Chen JT, Waterman PD, Rehkopf DH, Subramanian SV (2003) Race/ethnicity, gender, and monitoring socioeconomic gradients in health: a comparison of area-based socioeconomic measures—the public health disparities geocoding project. Am J Public Health 93(10):1655–1671

    Article  PubMed  PubMed Central  Google Scholar 

  29. Diez Roux AV (2002) A glossary for multilevel analysis. J Epidemiol Community Health 56(8):588–594

    Article  CAS  PubMed  Google Scholar 

  30. Howlader N, Altekruse SF, Li CI, Chen VW, Clarke CA, Ries LA, Cronin KA (2014) US incidence of breast cancer subtypes defined by joint hormone receptor and HER2 status. J Natl Cancer Inst 106(5):1–8. doi:10.1093/jnci/dju055

    Article  Google Scholar 

  31. Joslin CE, Brewer KC, Davis FG, Hoskins K, Peterson CE, Pauls HA (2014) The effect of neighborhood-level socioeconomic status on racial differences in ovarian cancer treatment in a population-based analysis in Chicago. Gynecol Oncol 135(2):285–291. doi:10.1016/j.ygyno.2014.08.029

    Article  PubMed  PubMed Central  Google Scholar 

  32. Bristow RE, Powell MA, Al-Hammadi N, Chen L, Miller JP, Roland PY, Mutch DG, Cliby WA (2013) Disparities in ovarian cancer care quality and survival according to race and socioeconomic status. J Natl Cancer Inst 105(11):823–832. doi:10.1093/jnci/djt065

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Gomez DR, Liao KP, Giordano S, Nguyen H, Smith BD, Elting LS (2013) Adherence to national guidelines for antiemesis prophylaxis in patients undergoing chemotherapy for lung cancer: a population-based study. Cancer 119(7):1428–1436. doi:10.1002/cncr.27899

    Article  CAS  PubMed  Google Scholar 

  34. Devoe JE, Baez A, Angier H, Krois L, Edlund C, Carney PA (2007) Insurance + access not equal to health care: typology of barriers to health care access for low-income families. Ann Fam Med 5(6):511–518. doi:10.1370/afm.748

    Article  PubMed  PubMed Central  Google Scholar 

  35. Bristow RE, Chang J, Ziogas A, Campos B, Chavez LR, Anton-Culver H (2015) Sociodemographic disparities in advanced ovarian cancer survival and adherence to treatment guidelines. Obstet Gynecol 125(4):833–842. doi:10.1097/AOG.0000000000000643

    Article  PubMed  Google Scholar 

  36. Hines RB, Barrett A, Twumasi-Ankrah P, Broccoli D, Engelman KK, Baranda J, Ablah EA, Jacobson L, Redmond M, Tu W, Collins TC (2015) Predictors of guideline treatment nonadherence and the impact on survival in patients with colorectal cancer. J Natl Compr Cancer Netw 13(1):51–60

    Google Scholar 

  37. Bristow RE, Chang J, Ziogas A, Anton-Culver H, Vieira VM (2014) Spatial analysis of adherence to treatment guidelines for advanced-stage ovarian cancer and the impact of race and socioeconomic status. Gynecol Oncol 134(1):60–67. doi:10.1016/j.ygyno.2014.03.561

    Article  PubMed  PubMed Central  Google Scholar 

  38. Krieger N, Chen JT, Waterman PD, Soobader MJ, Subramanian SV, Carson R (2002) Geocoding and monitoring of US socioeconomic inequalities in mortality and cancer incidence: does the choice of area-based measure and geographic level matter? The public health disparities geocoding project. Am J Epidemiol 156(5):471–482

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

Dr. Akinyemiju was supported by Grant U54 CA118948 from the NIH. Mr. Moore was supported by Grant R25 CA47888 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.

Author information

Authors and Affiliations

  1. Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA

    Tomi Akinyemiju, Justin Xavier Moore, Akinyemi I. Ojesina & John W. Waterbor

  2. Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL, USA

    Tomi Akinyemiju, Justin Xavier Moore, Akinyemi I. Ojesina & John W. Waterbor

  3. HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA

    Akinyemi I. Ojesina

  4. Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, USA

    Sean F. Altekruse

Authors
  1. Tomi Akinyemiju
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Justin Xavier Moore
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Akinyemi I. Ojesina
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. John W. Waterbor
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sean F. Altekruse
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tomi Akinyemiju.

Ethics declarations

Conflicts of interest

None.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Akinyemiju, T., Moore, J.X., Ojesina, A.I. et al. Racial disparities in individual breast cancer outcomes by hormone-receptor subtype, area-level socio-economic status and healthcare resources. Breast Cancer Res Treat 157, 575–586 (2016). https://doi.org/10.1007/s10549-016-3840-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10549-016-3840-x

Keywords

Search

Navigation