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Integrating Biology and Access to Care in Addressing Breast Cancer Disparities: 25 Years’ Research Experience in the Carolina Breast Cancer Study

  • Breast Cancer Disparities (LA Newman, Section Editor)
  • Published:
Current Breast Cancer Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

To review research on breast cancer mortality disparities, emphasizing research conducted in the Carolina Breast Cancer Study, with a focus on challenges and opportunities for integration of tumor biology and access characteristics across the cancer care continuum.

Recent Findings

Black women experience higher mortality following breast cancer diagnosis, despite lower incidence compared to white women. Biological factors, such as stage at diagnosis and breast cancer subtypes, play a role in these disparities. Simultaneously, social, behavioral, environmental, and access to care factors are important. However, integrated studies of biology and access are challenging and it is uncommon to have both data types available in the same study population. The central emphasis of phase 3 of the Carolina Breast Cancer Study, initiated in 2008, was to collect rich data on biology (including germline and tumor genomics and pathology) and health care access in a diverse study population, with the long-term goal of defining intervention opportunities to reduce disparities across the cancer care continuum.

Summary

Early and ongoing research from CBCS has identified important interactions between biology and access, leading to opportunities to build greater equity. However, sample size, population-specific relationships among variables, and complexities of treatment paths along the care continuum pose important research challenges. Interdisciplinary teams, including experts in novel data integration and causal inference, are needed to address gaps in our understanding of breast cancer disparities.

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References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. DeSantis CE, Fedewa SA, Goding Sauer A, Kramer JL, Smith RA, Jemal A. Breast cancer statistics, 2015: convergence of incidence rates between black and white women. CA Cancer J Clin. 2016;66(1):31–42. https://doi.org/10.3322/caac.21320.

    Article  PubMed  Google Scholar 

  2. DeSantis CE, Siegel RL, Sauer AG, Miller KD, Fedewa SA, Alcaraz KI, et al. Cancer statistics for African Americans, 2016: progress and opportunities in reducing racial disparities. CA Cancer J Clin. 2016;66(4):290–308. https://doi.org/10.3322/caac.21340.

    Article  PubMed  Google Scholar 

  3. National Center for Health Statistics, National Vital Statisitcs System. Table 26. Death rates for malignant neoplasm of breast among females, by race, Hispanic origin and age: United States 2017. Hyattsville, MD: US Department of health and human services, Centers for Disease Control and Prevention; 2017.

  4. Dunnwald LK, Rossing MA, Li CI. Hormone receptor status, tumor characteristics, and prognosis: a prospective cohort of breast cancer patients. Breast Cancer Res. 2007;9(1):R6. https://doi.org/10.1186/bcr1639.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Carey LA, Perou CM, Livasy CA, Dressler LG, Cowan D, Conway K, et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA. 2006;295(21):2492–502. https://doi.org/10.1001/jama.295.21.2492.

    Article  CAS  PubMed  Google Scholar 

  6. Millikan RC, Newman B, Tse CK, Moorman PG, Conway K, Dressler LG, et al. Epidemiology of basal-like breast cancer. Breast Cancer Res Treat. 2008;109(1):123–39. https://doi.org/10.1007/s10549-007-9632-6.

    Article  PubMed  Google Scholar 

  7. Bauer KR, Brown M, Cress RD, Parise CA, Caggiano V. Descriptive analysis of estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and HER2-negative invasive breast cancer, the so-called triple-negative phenotype: a population-based study from the California Cancer Registry. Cancer. 2007;109(9):1721–8. https://doi.org/10.1002/cncr.22618.

    Article  PubMed  Google Scholar 

  8. Morris GJ, Naidu S, Topham AK, Guiles F, Xu Y, McCue P, et al. Differences in breast carcinoma characteristics in newly diagnosed African-American and Caucasian patients: a single-institution compilation compared with the National Cancer Institute’s Surveillance, Epidemiology, and End Results database. Cancer. 2007;110(4):876–84. https://doi.org/10.1002/cncr.22836.

    Article  PubMed  Google Scholar 

  9. Lund MJ, Trivers KF, Porter PL, Coates RJ, Leyland-Jones B, Brawley OW, et al. Race and triple negative threats to breast cancer survival: a population-based study in Atlanta, GA. Breast Cancer Res Treat. 2009;113(2):357–70. https://doi.org/10.1007/s10549-008-9926-3.

    Article  PubMed  Google Scholar 

  10. Daly B, Olopade OI. A perfect storm: how tumor biology, genomics, and health care delivery patterns collide to create a racial survival disparity in breast cancer and proposed interventions for change. CA Cancer J Clin. 2015;65(3):221–38. https://doi.org/10.3322/caac.21271.

    Article  PubMed  Google Scholar 

  11. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490(7418):61–70. doi:https://doi.org/10.1038/nature11412.

  12. Howlader N, Altekruse SF, Li CI, Chen VW, Clarke CA, Ries LA, et al. US incidence of breast cancer subtypes defined by joint hormone receptor and HER2 status. J Natl Cancer Inst. 2014;106(5). https://doi.org/10.1093/jnci/dju055.

  13. Newman B, Moorman PG, Millikan R, Qaqish BF, Geradts J, Aldrich TE, et al. The Carolina Breast Cancer Study: integrating population-based epidemiology and molecular biology. Breast Cancer Res Treat. 1995;35(1):51–60. https://doi.org/10.1007/bf00694745.

    Article  CAS  PubMed  Google Scholar 

  14. Phillips LS, Millikan RC, Schroeder JC, Barnholtz-Sloan JS, Levine BJ. Reproductive and hormonal risk factors for ductal carcinoma in situ of the breast. Cancer Epidemiol Biomark Prev. 2009;18(5):1507–14. https://doi.org/10.1158/1055-9965.epi-08-0967.

    Article  CAS  Google Scholar 

  15. Dunn BK, Agurs-Collins T, Browne D, Lubet R, Johnson KA. Health disparities in breast cancer: biology meets socioeconomic status. Breast Cancer Res Treat. 2010;121(2):281–92. https://doi.org/10.1007/s10549-010-0827-x.

    Article  PubMed  Google Scholar 

  16. Andaya AA, Enewold L, Horner MJ, Jatoi I, Shriver CD, Zhu K. Socioeconomic disparities and breast cancer hormone receptor status. Cancer Causes Control. 2012;23(6):951–8. https://doi.org/10.1007/s10552-012-9966-1.

    Article  PubMed  Google Scholar 

  17. Clegg LX, Reichman ME, Miller BA, Hankey BF, Singh GK, Lin YD, et al. Impact of socioeconomic status on cancer incidence and stage at diagnosis: selected findings from the surveillance, epidemiology, and end results: National Longitudinal Mortality Study. Cancer Causes Control. 2009;20(4):417–35. https://doi.org/10.1007/s10552-008-9256-0.

    Article  PubMed  Google Scholar 

  18. Anderson BM, MacLennan MB, Hillyer LM, Ma DW. Lifelong exposure to n-3 PUFA affects pubertal mammary gland development. Appl Physiol Nutr Metab. 2014;39(6):699–706. https://doi.org/10.1139/apnm-2013-0365.

    Article  CAS  PubMed  Google Scholar 

  19. Krieger N, Kiang MV, Kosheleva A, Waterman PD, Chen JT, Beckfield J. Age at menarche: 50-year socioeconomic trends among US-born black and white women. Am J Public Health. 2015;105(2):388–97. https://doi.org/10.2105/ajph.2014.301936.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Biro FM, Greenspan LC, Galvez MP, Pinney SM, Teitelbaum S, Windham GC, et al. Onset of breast development in a longitudinal cohort. Pediatrics. 2013;132(6):1019–27. https://doi.org/10.1542/peds.2012-3773.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Progress in increasing breastfeeding and reducing racial/ethnic differences—United States, 2000-2008 births. MMWR Morbidity and Mortality Weekly Report. 2013;62(5):77-80.

  22. Chandra A, Martinez GM, Mosher WD, Abma JC, Jones J. Fertility, family planning, and reproductive health of U.S. women: data from the 2002 National Survey of Family Growth. Vital and health statistics Series 23, Data from the National Survey of Family Growth 2005(25):1–160.

  23. McDowell MM, Wang CY, Kennedy-Stephenson J. Breastfeeding in the United States: findings from the national health and nutrition examination surveys, 1999-2006. NCHS Data Brief. 2008(5):1–8.

  24. Racial and ethnic differences in breastfeeding initiation and duration, by state—National Immunization Survey, United States, 2004-2008. MMWR Morbidity and Mortality Weekly Report. 2010;59(11):327–34.

  25. Martin JA, Hamilton BE, Osterman MJ, Curtin SC, Matthews TJ. Births: final data for 2013. National vital statistics reports from the Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System 2015;64(1):1–65.

  26. Daniels K, Mosher WD. Contraceptive methods women have ever used: United States, 1982-2010. National Health Statistics Reports. 2013(62):1–15.

  27. Bethea TN, Rosenberg L, Hong CC, Troester MA, Lunetta KL, Bandera EV, et al. A case–control analysis of oral contraceptive use and breast cancer subtypes in the African American Breast Cancer Epidemiology and Risk Consortium. Breast Cancer Res. 2015;17(1). https://doi.org/10.1186/s13058-015-0535-x.

  28. Flegal KM, Kruszon-Moran D, Carroll MD, Fryar CD, Ogden CL. Trends in obesity among adults in the United States, 2005 to 2014. JAMA. 2016;315(21):2284–91. https://doi.org/10.1001/jama.2016.6458.

    Article  CAS  PubMed  Google Scholar 

  29. Centers for Disease Control and Prevention. National Diabetes Statistics Report. Atlanta, GA: Centers for Disease Control and Prevention. US Dept of Health and Human Services. 2017.

  30. Butler EN, Tse CK, Bell ME, Conway K, Olshan AF, Troester MA. Active smoking and risk of luminal and basal-like breast cancer subtypes in the Carolina Breast Cancer Study. Cancer Causes Control. 2016;27(6):775–86. https://doi.org/10.1007/s10552-016-0754-1.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Williams LA, Olshan AF, Tse CK, Bell ME, Troester MA. Alcohol intake and invasive breast cancer risk by molecular subtype and race in the Carolina Breast Cancer Study. Cancer Causes Control. 2016;27(2):259–69. https://doi.org/10.1007/s10552-015-0703-4.

    Article  PubMed  Google Scholar 

  32. Robinson WR, Tse CK, Olshan AF, Troester MA. Body size across the life course and risk of premenopausal and postmenopausal breast cancer in black women, the Carolina Breast Cancer Study, 1993-2001. Cancer Causes Control. 2014;25(9):1101–17. https://doi.org/10.1007/s10552-014-0411-5.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Allott EH, Tse CK, Olshan AF, Carey LA, Moorman PG, Troester MA. Non-steroidal anti-inflammatory drug use, hormone receptor status, and breast cancer-specific mortality in the Carolina Breast Cancer Study. Breast Cancer Res Treat. 2014;147(2):415–21. https://doi.org/10.1007/s10549-014-3099-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Razzaghi H, Troester MA, Gierach GL, Olshan AF, Yankaskas BC, Millikan RC. Association between mammographic density and basal-like and luminal A breast cancer subtypes. Breast Cancer Research : BCR. 2013;15(5):R76. https://doi.org/10.1186/bcr3470.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Chollet-Hinton L, Anders CK, Tse CK, Bell MB, Yang YC, Carey LA, et al. Breast cancer biologic and etiologic heterogeneity by young age and menopausal status in the Carolina Breast Cancer Study: a case-control study. Breast Cancer Research : BCR. 2016;18(1):79. https://doi.org/10.1186/s13058-016-0736-y.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Bensen JT, Tse CK, Nyante SJ, Barnholtz-Sloan JS, Cole SR, Millikan RC. Association of germline microRNA SNPs in pre-miRNA flanking region and breast cancer risk and survival: the Carolina Breast Cancer Study. Cancer Causes & Control : CCC. 2013;24(6):1099–109. https://doi.org/10.1007/s10552-013-0187-z.

    Article  PubMed  Google Scholar 

  37. Chen F, Chen GK, Stram DO, Millikan RC, Ambrosone CB, John EM, et al. A genome-wide association study of breast cancer in women of African ancestry. Hum Genet. 2013;132(1):39–48. https://doi.org/10.1007/s00439-012-1214-y.

    Article  PubMed  Google Scholar 

  38. Song C, Chen GK, Millikan RC, Ambrosone CB, John EM, Bernstein L, et al. A genome-wide scan for breast cancer risk haplotypes among African American women. PLoS One. 2013;8(2):e57298. https://doi.org/10.1371/journal.pone.0057298.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. O’Brien KM, Cole SR, Engel LS, Bensen JT, Poole C, Herring AH, et al. Breast cancer subtypes and previously established genetic risk factors: a bayesian approach. Cancer Epidemiol Biomarkers Prev. 2014;23(1):84–97. https://doi.org/10.1158/1055-9965.EPI-13-0463.

    Article  CAS  PubMed  Google Scholar 

  40. Family L, Bensen JT, Troester MA, Wu MC, Anders CK, Olshan AF. Single-nucleotide polymorphisms in DNA bypass polymerase genes and association with breast cancer and breast cancer subtypes among African Americans and whites. Breast Cancer Res Treat. 2015;149(1):181–90. https://doi.org/10.1007/s10549-014-3203-4.

    Article  CAS  PubMed  Google Scholar 

  41. Haiman CA, Chen GK, Vachon CM, Canzian F, Dunning A, Millikan RC, et al. A common variant at the TERT-CLPTM1L locus is associated with estrogen receptor-negative breast cancer. Nat Genet. 2011;43(12):1210–4. https://doi.org/10.1038/ng.985.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Palmer JR, Ambrosone CB, Olshan AF. A collaborative study of the etiology of breast cancer subtypes in African American women: the AMBER consortium. Cancer Causes Control. 2014;25(3):309–19. https://doi.org/10.1007/s10552-013-0332-8.

    Article  PubMed  Google Scholar 

  43. Sun X, Nichols HB, Robinson W, Sherman ME, Olshan AF, Troester MA. Post-diagnosis adiposity and survival among breast cancer patients: influence of breast cancer subtype. Cancer Causes Control. 2015;26(12):1803–11. https://doi.org/10.1007/s10552-015-0673-6.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Sun X, Nichols HB, Tse CK, Bell MB, Robinson WR, Sherman ME, et al. Association of parity and time since last birth with breast cancer prognosis by intrinsic subtype. Cancer Epidemiol Biomark Prev. 2016;25(1):60–7. https://doi.org/10.1158/1055-9965.epi-15-0864.

    Article  Google Scholar 

  45. O’Brien KM, Cole SR, Tse CK, Perou CM, Carey LA, Foulkes WD, et al. Intrinsic breast tumor subtypes, race, and long-term survival in the Carolina Breast Cancer Study. Clin Cancer Res. 2010;16(24):6100–10. https://doi.org/10.1158/1078-0432.ccr-10-1533.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Geiss GK, Bumgarner RE, Birditt B, Dahl T, Dowidar N, Dunaway DL, et al. Direct multiplexed measurement of gene expression with color-coded probe pairs. Nat Biotechnol. 2008;26(3):317–25. https://doi.org/10.1038/nbt1385.

    Article  CAS  PubMed  Google Scholar 

  47. Malkov VA, Serikawa KA, Balantac N, Watters J, Geiss G, Mashadi-Hossein A, et al. Multiplexed measurements of gene signatures in different analytes using the Nanostring nCounter Assay System. BMC Res Notes. 2009;2:80. https://doi.org/10.1186/1756-0500-2-80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Allott EH, Cohen SM, Geradts J, Sun X, Khoury T, Bshara W, et al. Performance of three-biomarker immunohistochemistry for intrinsic breast cancer subtyping in the AMBER consortium. Cancer Epidemiol Biomark Prev. 2016;25(3):470–8. https://doi.org/10.1158/1055-9965.epi-15-0874.

    Article  CAS  Google Scholar 

  49. •• Troester MA, Sun X, Allott EH, Geradts J, Cohen SM, Tse CK, et al. Racial differences in PAM50 subtypes in the Carolina Breast Cancer Study. J Natl Cancer Inst. 2018;110(2). https://doi.org/10.1093/jnci/djx135Using RNA expression data, this analysis classified breast cancer PAM50 subtype in a population-based sample. Multi-gene assays showed racial disparities in frequency of basal-like breast cancer and implicate differences in tumor biology as an important contributor to mortality disparities among both younger and older black patients with HR-positive/HER2-negative disease.

  50. Conway K, Edmiston SN, May R, Kuan PF, Chu H, Bryant C, et al. DNA methylation profiling in the Carolina Breast Cancer Study defines cancer subclasses differing in clinicopathologic characteristics and survival. Breast Cancer Res. 2014;16(5):450. https://doi.org/10.1186/s13058-014-0450-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Hair BY, Troester MA, Edmiston SN, Parrish EA, Robinson WR, Wu MC, et al. Body mass index is associated with gene methylation in estrogen receptor-positive breast tumors. Cancer Epidemiol Biomark Prev. 2015;24(3):580–6. https://doi.org/10.1158/1055-9965.epi-14-1017.

    Article  CAS  Google Scholar 

  52. Couture HD, Williams LA, Geradts J, Nyante SJ, Butler EN, Marron JS, et al. Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype. NPJ Breast Cancer. 2018;4:30. https://doi.org/10.1038/s41523-018-0079-1.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Benefield HC, Zabor EC, Shan Y, Allott EH, Begg CB, Troester MA. Evidence for etiologic subtypes of breast cancer in the Carolina Breast Cancer Study. Cancer Epidemiol Biomark Prev. 2019;28(11):1784–91. https://doi.org/10.1158/1055-9965.epi-19-0365.

    Article  CAS  Google Scholar 

  54. DeSantis CE, Miller KD, Goding Sauer A, Jemal A, Siegel RL. Cancer statistics for African Americans, 2019. CA Cancer J Clin. 2019;69(3):211–33. https://doi.org/10.3322/caac.21555.

    Article  PubMed  Google Scholar 

  55. White A, Thompson TD, White MC, Sabatino SA, de Moor J, Doria-Rose PV, et al. Cancer screening test use—United States, 2015. MMWR Morb Mortal Wkly Rep. 2017;66(8):201–6. https://doi.org/10.15585/mmwr.mm6608a1.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Jewett PI, Gangnon RE, Elkin E, Hampton JM, Jacobs EA, Malecki K, et al. Geographic access to mammography facilities and frequency of mammography screening. Ann Epidemiol. 2018;28(2):65–71.e2. https://doi.org/10.1016/j.annepidem.2017.11.012.

    Article  PubMed  Google Scholar 

  57. Haas JS, Earle CC, Orav JE, Brawarsky P, Keohane M, Neville BA, et al. Racial segregation and disparities in breast cancer care and mortality. Cancer. 2008;113(8):2166–72. https://doi.org/10.1002/cncr.23828.

    Article  PubMed  Google Scholar 

  58. Porter P. “Westernizing” women’s risks? Breast cancer in lower-income countries. N Engl J Med. 2008;358(3):213–6. https://doi.org/10.1056/NEJMp0708307.

    Article  CAS  PubMed  Google Scholar 

  59. Sihto H, Lundin J, Lehtimaki T, Sarlomo-Rikala M, Butzow R, Holli K, et al. Molecular subtypes of breast cancers detected in mammography screening and outside of screening. Clinical Cancer Res. 2008;14(13):4103–10. https://doi.org/10.1158/1078-0432.ccr-07-5003.

    Article  CAS  Google Scholar 

  60. Kirsh VA, Chiarelli AM, Edwards SA, O’Malley FP, Shumak RS, Yaffe MJ, et al. Tumor characteristics associated with mammographic detection of breast cancer in the Ontario Breast Screening Program. J Natl Cancer Inst. 2011;103(12):942–50. https://doi.org/10.1093/jnci/djr138.

    Article  PubMed  Google Scholar 

  61. Caldarella A, Puliti D, Crocetti E, Bianchi S, Vezzosi V, Apicella P, et al. Biological characteristics of interval cancers: a role for biomarkers in the breast cancer screening. J Cancer Res Clin Oncol. 2013;139(2):181–5. https://doi.org/10.1007/s00432-012-1304-1.

    Article  CAS  PubMed  Google Scholar 

  62. Houssami N, Hunter K. The epidemiology, radiology and biological characteristics of interval breast cancers in population mammography screening. NPJ Breast Cancer. 2017;3:12. https://doi.org/10.1038/s41523-017-0014-x.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Johnson K, Zackrisson S, Rosso A, Sartor H, Saal LH, Andersson I, Lång K Tumor characteristics and molecular subtypes in breast cancer screening with digital breast tomosynthesis: the Malmo Breast Tomosynthesis Screening Trial. Radiology 2019;293(2):273–281. doi:https://doi.org/10.1148/radiol.2019190132.

  64. Li J, Ivansson E, Klevebring D, Tobin NP, Lindstrom LS, Holm J, et al. Molecular differences between screen-detected and interval breast cancers are largely explained by PAM50 subtypes. Clinical Cancer Research : an official journal of the American Association for Cancer Research. 2017;23(10):2584–92. https://doi.org/10.1158/1078-0432.ccr-16-0967.

    Article  Google Scholar 

  65. • Puvanesarajah S, Nyante SJ, Kuzmiak CM, Chen M, Tse CK, Sun X, et al. PAM50 and risk of recurrence scores for interval breast cancers. Cancer Prev Res (Phila). 2018;11(6):327–36. https://doi.org/10.1158/1940-6207.capr-17-0368This study examined the association of mode of detection with cancer characteristics (clinical, IHC, and genomic) and stratified analyses on mammographic density and race. Interval cancers were less likely, whereas screen-detected cancers were more likely, to have non-luminal A subtype.

    Article  Google Scholar 

  66. Chen Y, Susick L, Davis M, Bensenhaver J, Nathanson SD, Burns J, et al. Evaluation of triple-negative breast cancer early detection via mammography screening and outcomes in African American and white American patients. JAMA Surg. 2020. https://doi.org/10.1001/jamasurg.2019.6032.

  67. Killelea BK, Chagpar AB, Bishop J, Horowitz NR, Christy C, Tsangaris T, et al. Is there a correlation between breast cancer molecular subtype using receptors as surrogates and mammographic appearance? Ann Surg Oncol. 2013;20(10):3247–53. https://doi.org/10.1245/s10434-013-3155-7.

    Article  PubMed  Google Scholar 

  68. Boisserie-Lacroix M, Bullier B, Hurtevent-Labrot G, Ferron S, Lippa N, Mac GG. Correlation between imaging and prognostic factors: molecular classification of breast cancers. Diag Interv Imag. 2014;95(2):227–33. https://doi.org/10.1016/j.diii.2013.12.013.

    Article  CAS  Google Scholar 

  69. Richards MA, Westcombe AM, Love SB, Littlejohns P, Ramirez AJ. Influence of delay on survival in patients with breast cancer: a systematic review. Lancet. 1999;353(9159):1119–26.

    Article  CAS  PubMed  Google Scholar 

  70. George P, Chandwani S, Gabel M, Ambrosone CB, Rhoads G, Bandera EV, et al. Diagnosis and surgical delays in African American and white women with early-stage breast cancer. J Women's Health (Larchmt). 2015;24(3):209–17. https://doi.org/10.1089/jwh.2014.4773.

    Article  Google Scholar 

  71. Gorin SS, Heck JE, Cheng B, Smith SJ. Delays in breast cancer diagnosis and treatment by racial/ethnic group. Arch Intern Med. 2006;166(20):2244–52. https://doi.org/10.1001/archinte.166.20.2244.

    Article  PubMed  Google Scholar 

  72. Smith EC, Ziogas A, Anton-Culver H. Delay in surgical treatment and survival after breast cancer diagnosis in young women by race/ethnicity. JAMA Surgery. 2013;148(6):516–23. https://doi.org/10.1001/jamasurg.2013.1680.

    Article  PubMed  Google Scholar 

  73. Polverini AC, Nelson RA, Marcinkowski E, Jones VC, Lai L, Mortimer JE, et al. Time to treatment: measuring quality breast cancer care. Ann Surg Oncol. 2016;23(10):3392–402. https://doi.org/10.1245/s10434-016-5486-7.

    Article  PubMed  Google Scholar 

  74. Halpern MT, Schrag D. Effects of state-level Medicaid policies and patient characteristics on time to breast cancer surgery among Medicaid beneficiaries. Breast Cancer Res Treat. 2016;158(3):573–81. https://doi.org/10.1007/s10549-016-3879-8.

    Article  PubMed  Google Scholar 

  75. McGee SA, Durham DD, Tse CK, Millikan RC. Determinants of breast cancer treatment delay differ for African American and White women. Cancer Epidemiol Biomark Prev. 2013;22(7):1227–38. https://doi.org/10.1158/1055-9965.epi-12-1432.

    Article  Google Scholar 

  76. Wheeler SB, Carpenter WR, Peppercorn J, Schenck AP, Weinberger M, Biddle AK. Structural/organizational characteristics of health services partly explain racial variation in timeliness of radiation therapy among elderly breast cancer patients. Breast Cancer Res Treat. 2012;133(1):333–45. https://doi.org/10.1007/s10549-012-1955-2.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Gold HT, Thwin SS, Buist DS, Field TS, Wei F, Yood MU, et al. Delayed radiotherapy for breast cancer patients in integrated delivery systems. Am J Manag Care. 2009;15(11):785–9.

    PubMed  PubMed Central  Google Scholar 

  78. Chavez-MacGregor M, Clarke CA, Lichtensztajn DY, Giordano SH. Delayed initiation of adjuvant chemotherapy among patients with breast cancer. JAMA Oncol. 2016;2(3):322–9. https://doi.org/10.1001/Jamaoncol.2015.3856.

    Article  PubMed  PubMed Central  Google Scholar 

  79. Nurgalieva ZZ, Franzini L, Morgan RO, Vernon SW, Liu CC, Du XL. Impact of timing of adjuvant chemotherapy initiation and completion after surgery on racial disparities in survival among women with breast cancer. Med Oncol. 2013;30(1):419. https://doi.org/10.1007/s12032-012-0419-1.

    Article  CAS  PubMed  Google Scholar 

  80. Hershman D, McBride R, Jacobson JS, Lamerato L, Roberts K, Grann VR, et al. Racial disparities in treatment and survival among women with early-stage breast cancer. J Clin Oncol. 2005;23(27):6639–46. https://doi.org/10.1200/jco.2005.12.633.

    Article  PubMed  Google Scholar 

  81. Fedewa SA, Ward EM, Stewart AK, Edge SB. Delays in adjuvant chemotherapy treatment among patients with breast cancer are more likely in African American and Hispanic populations: a national cohort study 2004-2006. J Clin Oncol. 2010;28(27):4135–41. https://doi.org/10.1200/jco.2009.27.2427.

    Article  PubMed  Google Scholar 

  82. Reeder-Hayes KE, Meyer AM, Dusetzina SB, Liu H, Wheeler SB. Racial disparities in initiation of adjuvant endocrine therapy of early breast cancer. Breast Cancer Res Treat. 2014;145(3):743–51. https://doi.org/10.1007/s10549-014-2957-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Gagliato Dde M, Gonzalez-Angulo AM, Lei X, Theriault RL, Giordano SH, Valero V, et al. Clinical impact of delaying initiation of adjuvant chemotherapy in patients with breast cancer. J Clin Oncol. 2014;32(8):735–44. https://doi.org/10.1200/jco.2013.49.7693.

    Article  PubMed  Google Scholar 

  84. Dunmore C, Plummer P, Regan G, Mattingly D, Jackson S, Millikan R. Re: race and differences in breast cancer survival in a managed care population. J Natl Cancer Inst. 2000;92(20):1690–1.

    Article  CAS  PubMed  Google Scholar 

  85. Roberts MC, Weinberger M, Dusetzina SB, Dinan MA, Reeder-Hayes KE, Carey LA, et al. Racial variation in the uptake of Oncotype DX testing for early-stage breast cancer. J Clin Oncol. 2016;34(2):130–8. https://doi.org/10.1200/JCO.2015.63.2489.

    Article  CAS  PubMed  Google Scholar 

  86. Roberts MC, Weinberger M, Dusetzina SB, Dinan MA, Reeder-Hayes KE, Troester MA, et al. Racial variation in adjuvant chemotherapy initiation among breast cancer patients receiving Oncotype DX testing. Breast Cancer Res Treat. 2015;153(1):191–200. https://doi.org/10.1007/s10549-015-3518-9.

    Article  PubMed  PubMed Central  Google Scholar 

  87. Spencer JC, Reeve BB, Troester MA, Wheeler SB. Factors associated with endocrine therapy non-adherence in breast cancer survivors. Psycho-oncology. 2020;29:647–54. https://doi.org/10.1002/pon.5289.

    Article  PubMed  PubMed Central  Google Scholar 

  88. • Wheeler SB, Spencer J, Pinheiro LC, Murphy CC, Earp JA, Carey L, et al. Endocrine therapy nonadherence and discontinuation in black and white women. J Natl Cancer Inst. 2019;111(5):498–508. https://doi.org/10.1093/jnci/djy136This study assessed endocrine therapy use by race, including behavioral predictors. Black women with HR+ breast cancers were more likely to be nonadherent to ET, but were not more likely to discontinue. Major predictors of nonadherence included differential risk perceptions and a lack of shared treatment decision-making.

    Article  PubMed  Google Scholar 

  89. Pinheiro LC, Wheeler SB, Reeder-Hayes KE, Samuel CA, Olshan AF, Reeve BB. Investigating associations between health-related quality of life and endocrine therapy underuse in women with early-stage breast cancer. J Oncol Pract. 2017;13(5):e463–e73. https://doi.org/10.1200/jop.2016.018630.

    Article  PubMed  PubMed Central  Google Scholar 

  90. Wheeler SB, Kohler RE, Reeder-Hayes KE, Goyal RK, Lich KH, Moore A, et al. Endocrine therapy initiation among Medicaid-insured breast cancer survivors with hormone receptor-positive tumors. J Cancer Surviv. 2014;8(4):603–10. https://doi.org/10.1007/s11764-014-0365-3.

    Article  PubMed  PubMed Central  Google Scholar 

  91. Livaudais JC, Hershman DL, Habel L, Kushi L, Gomez SL, Li CI, et al. Racial/ethnic differences in initiation of adjuvant hormonal therapy among women with hormone receptor-positive breast cancer. Breast Cancer Res Treat. 2012;131(2):607–17. https://doi.org/10.1007/s10549-011-1762-1.

    Article  CAS  PubMed  Google Scholar 

  92. Roberts MC, Wheeler SB, Reeder-Hayes K. Racial/ethnic and socioeconomic disparities in endocrine therapy adherence in breast cancer: a systematic review. Am J Public Health. 2015;105(Suppl 3):e4–e15. https://doi.org/10.2105/ajph.2014.302490.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Lund MJ, Brawley OP, Ward KC, Young JL, Gabram SS, Eley JW. Parity and disparity in first course treatment of invasive breast cancer. Breast Cancer Res Treat. 2008;109(3):545–57. https://doi.org/10.1007/s10549-007-9675-8.

    Article  PubMed  Google Scholar 

  94. Camacho FT, Tan X, Alcala HE, Shah S, Anderson RT, Balkrishnan R. Impact of patient race and geographical factors on initiation and adherence to adjuvant endocrine therapy in Medicare breast cancer survivors. Medicine. 2017;96(24):e7147. https://doi.org/10.1097/md.0000000000007147.

    Article  PubMed  PubMed Central  Google Scholar 

  95. Press DJ, Ibraheem A, Dolan ME, Goss KH, Conzen S, Huo D. Racial disparities in omission of Oncotype DX but no racial disparities in chemotherapy receipt following completed Oncotype DX test results. Breast Cancer Res Treat. 2018;168(1):207–20. https://doi.org/10.1007/s10549-017-4587-8.

    Article  PubMed  Google Scholar 

  96. Anderson WF, Chatterjee N, Ershler WB, Brawley OW. Estrogen receptor breast cancer phenotypes in the surveillance, epidemiology, and end results database. Breast Cancer Res Treat. 2002;76(1):27–36.

    Article  CAS  PubMed  Google Scholar 

  97. Smith-Bindman R, Miglioretti DL, Lurie N, Abraham L, Barbash RB, Strzelczyk J, et al. Does utilization of screening mammography explain racial and ethnic differences in breast cancer? Ann Intern Med. 2006;144(8):541–53.

    Article  PubMed  Google Scholar 

  98. Howlader N NA, Krapcho M, Miller D, Bishop K, Altekruse SF, Kosary CL, Yu M, Ruhl J, Tatalovich Z, Mariotto A, Lewis DR, Chen HS, Feuer EJ, Cronin KA (eds). SEER Cancer Statistics Review, 1975–2013. National Cancer Institute, Bethesda, MD. http://seer.cancer.gov/csr/1975_2013/, based on November 2015 SEER data submission, posted to the SEER web site, April 2016.

  99. Chen VW, Correa P, Kurman RJ, Wu XC, Eley JW, Austin D, et al. Histological characteristics of breast carcinoma in blacks and whites. Cancer Epidemiol Biomarkers Prev. 1994;3(2):127–35.

    CAS  PubMed  Google Scholar 

  100. Porter PL, Lund MJ, Lin MG, Yuan X, Liff JM, Flagg EW, et al. Racial differences in the expression of cell cycle-regulatory proteins in breast carcinoma. Cancer. 2004;100(12):2533–42. https://doi.org/10.1002/cncr.20279.

    Article  PubMed  Google Scholar 

  101. Barnholtz-Sloan JS, Shetty PB, Guan X, Nyante SJ, Luo J, Brennan DJ, et al. FGFR2 and other loci identified in genome-wide association studies are associated with breast cancer in African-American and younger women. Carcinogenesis. 2010;31(8):1417–23. https://doi.org/10.1093/carcin/bgq128.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Bhattacharya A, Garcia-Closas M, Olshan AF, Perou CM, Troester MA, Love MI. A framework for transcriptome-wide association studies in breast cancer in diverse study populations. Genome Biol. 2020;21(1):42. https://doi.org/10.1186/s13059-020-1942-6.

    Article  PubMed  PubMed Central  Google Scholar 

  103. Hair BY, Hayes S, Tse CK, Bell MB, Olshan AF. Racial differences in physical activity among breast cancer survivors: implications for breast cancer care. Cancer. 2014;120(14):2174–82. https://doi.org/10.1002/cncr.28630.

    Article  PubMed  Google Scholar 

  104. Pinheiro LC, Samuel CA, Reeder-Hayes KE, Wheeler SB, Olshan AF, Reeve BB. Understanding racial differences in health-related quality of life in a population-based cohort of breast cancer survivors. Breast Cancer Res Treat. 2016;159(3):535–43. https://doi.org/10.1007/s10549-016-3965-y.

    Article  PubMed  PubMed Central  Google Scholar 

  105. • Pinheiro LC, Tan X, Olshan AF, Wheeler SB, Reeder-Hayes KE, Samuel CA, et al. Examining health-related quality of life patterns in women with breast cancer. Qual Life Res. 2017;26(7):1733–43. https://doi.org/10.1007/s11136-017-1533-5This study identified subgroups of women with breast cancer who experience different health-related quality of life patterns during treatment and survivorship. Findings suggest that age, race, comorbid conditions and modifiable patient-level factors such as smoking and obesity can identify women at risk for experiencing poor health-related quality of life patterns.

    Article  PubMed  PubMed Central  Google Scholar 

  106. •• Wheeler SB, Spencer JC, Pinheiro LC, Carey LA, Olshan AF, Reeder-Hayes KE. Financial impact of breast cancer in black versus white women. J Clin Oncol. 2018;36(17):1695–701. https://doi.org/10.1200/jco.2017.77.6310This study examined racial variation in the financial impact of cancer. Findings showed that black women with breast cancer experience disproportionate financial strain which may contribute to higher stress, lower treatment compliance, and worse outcomes by race.

    Article  PubMed  PubMed Central  Google Scholar 

  107. DeSantis CE, Ma J, Gaudet MM, Newman LA, Miller KD, Goding Sauer A, et al. Breast cancer statistics, 2019. CA Cancer J Clin. 2019;69(6):438–51. https://doi.org/10.3322/caac.21583.

    Article  PubMed  Google Scholar 

  108. Runowicz CD, Leach CR, Henry NL, Henry KS, Mackey HT, Cowens-Alvarado RL, et al. American Cancer Society/American Society of Clinical Oncology breast cancer survivorship care guideline. CA Cancer J Clin. 2016;66(1):43–73. https://doi.org/10.3322/caac.21319.

    Article  PubMed  Google Scholar 

  109. Gotay CC, Pagano IS. Assessment of Survivor Concerns (ASC): a newly proposed brief questionnaire. Health Qual Life Outcomes. 2007;5:15. https://doi.org/10.1186/1477-7525-5-15.

    Article  PubMed  PubMed Central  Google Scholar 

  110. Hodgkinson K, Butow P, Hunt GE, Pendlebury S, Hobbs KM, Lo SK, et al. The development and evaluation of a measure to assess cancer survivors’ unmet supportive care needs: the CaSUN (Cancer Survivors' Unmet Needs measure). Psycho-oncology. 2007;16(9):796–804. https://doi.org/10.1002/pon.1137.

    Article  CAS  PubMed  Google Scholar 

  111. Hibbard JH, Mahoney ER, Stockard J, Tusler M. Development and testing of a short form of the patient activation measure. Health Serv Res. 2005;40(6 Pt 1):1918–30. https://doi.org/10.1111/j.1475-6773.2005.00438.x.

    Article  PubMed  PubMed Central  Google Scholar 

  112. Lopez de Maturana E, Pineda S, Brand A, Van Steen K, Malats N. Toward the integration of Omics data in epidemiological studies: still a “long and winding road”. Genet Epidemiol. 2016;40(7):558–69. https://doi.org/10.1002/gepi.21992.

    Article  PubMed  Google Scholar 

  113. Emerson MA, Golightly YM, Tan X, Aiello AE, Reeder-Hayes KE, Olshan AF, et al. Integrating access to care and tumor patterns by race and age in the Carolina Breast Cancer Study, 2008-2013. Cancer Causes Control. 2020;31:221–30. https://doi.org/10.1007/s10552-019-01265-0.

    Article  PubMed  PubMed Central  Google Scholar 

  114. DeSantis C, Jemal A, Ward E. Disparities in breast cancer prognostic factors by race, insurance status, and education. Cancer Causes Control. 2010;21(9):1445–50. https://doi.org/10.1007/s10552-010-9572-z.

    Article  PubMed  Google Scholar 

  115. Akinyemiju TF, Pisu M, Waterbor JW, Altekruse SF. Socioeconomic status and incidence of breast cancer by hormone receptor subtype. Springerplus. 2015;4:508. https://doi.org/10.1186/s40064-015-1282-2.

    Article  PubMed  PubMed Central  Google Scholar 

  116. Sineshaw HM, Gaudet M, Ward EM, Flanders WD, Desantis C, Lin CC, et al. Association of race/ethnicity, socioeconomic status, and breast cancer subtypes in the National Cancer Data Base (2010-2011). Breast Cancer Res Treat. 2014;145(3):753–63. https://doi.org/10.1007/s10549-014-2976-9.

    Article  PubMed  Google Scholar 

  117. Messer LC, Laraia BA, Kaufman JS, Eyster J, Holzman C, Culhane J, et al. The development of a standardized neighborhood deprivation index. J Urban Health. 2006;83(6):1041–62. https://doi.org/10.1007/s11524-006-9094-x.

    Article  PubMed  PubMed Central  Google Scholar 

  118. Palumbo A, Michael Y, Hyslop T. Latent class model characterization of neighborhood socioeconomic status. Cancer Causes Control. 2016;27(3):445–52. https://doi.org/10.1007/s10552-015-0711-4.

    Article  PubMed  PubMed Central  Google Scholar 

  119. Chebli P, Lemus J, Avila C, Pena K, Mariscal B, Merlos S, et al. Multilevel determinants of financial toxicity in breast cancer care: perspectives of healthcare professionals and Latina survivors. Support Care Cancer. 2019. https://doi.org/10.1007/s00520-019-05119-y.

  120. Freedman RA, Revette AC, Hershman DL, Silva K, Sporn NJ, Gagne JJ, et al. Understanding breast cancer knowledge and barriers to treatment adherence: a qualitative study among breast cancer survivors. BioRes Open Access. 2017;6(1):159–68. https://doi.org/10.1089/biores.2017.0028.

    Article  PubMed  PubMed Central  Google Scholar 

  121. Warner ET, Gomez SL. Impact of neighborhood racial composition and metropolitan residential segregation on disparities in breast cancer stage at diagnosis and survival between black and white women in California. J Community Health. 2010;35(4):398–408. https://doi.org/10.1007/s10900-010-9265-2.

    Article  PubMed  PubMed Central  Google Scholar 

  122. •• Cheng AC, Levy MA. Measures of treatment workload for patients with breast cancer. JCO Clinical Cancer Informatics. 2019;3:1–10. https://doi.org/10.1200/cci.18.00122This study developed measures of patient treatment workload derived from electronic health record data. The findings showed that these treatment workload measures, including time spent in clinic and commuting time and costs, capture an important dimension in the experience of patients with cancer.

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Acknowledgments

The authors wish to acknowledge Beth Newman and Bob Millikan, the initial PIs for CBCS phases 1 and 2/3, respectively, who made seminal contributions to the design of the study. We are also grateful to the Carolina Breast Cancer Study participants and staff. Research reported in this publication was supported by a Specialized Program of Research Excellence (SPORE) in breast cancer (P50 CA058223), an award from the Susan G. Komen Foundation (OGUNC1202), the North Carolina University Cancer Research Fund, and a Cancer Center Support Grant (P30 CA016086).

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  1. Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Marc A. Emerson, Marina R. Sweeney, Andrew F. Olshan & Melissa A. Troester

  2. Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Marc A. Emerson, Katherine E. Reeder-Hayes, Heather J. Tipaldos, Mary E. Bell, Lisa A. Carey, H. Shelton Earp, Andrew F. Olshan & Melissa A. Troester

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Emerson, M.A., Reeder-Hayes, K.E., Tipaldos, H.J. et al. Integrating Biology and Access to Care in Addressing Breast Cancer Disparities: 25 Years’ Research Experience in the Carolina Breast Cancer Study. Curr Breast Cancer Rep 12, 149–160 (2020). https://doi.org/10.1007/s12609-020-00365-0

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