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Time to Surgical Treatment and Facility Characteristics as Potential Drivers of Racial Disparities in Breast Cancer Mortality

  • Breast Oncology
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

Black women are more likely to die of breast cancer than White women. This study evaluated the contribution of time to primary surgical management and surgical facility characteristics to racial disparities in breast cancer mortality among both Black and White women.

Methods

The study identified 2224 Black and 3787 White women with a diagnosis with stages I to III breast cancer (2010–2014). Outcomes included time to surgical treatment (> 30 days from diagnosis) and breast cancer mortality. Odds ratios (ORs) and 95% confidence intervals (CIs) associating surgical facility characteristics with surgical delay were computed, and Cox proportional hazards regression was used to compute hazard ratios (HRs) and 95% CIs associating delay and facility characteristics with breast cancer mortality.

Results

Black women were two times more likely to have a surgical delay (OR, 2.15; 95% CI, 1.92–2.41) than White women. Racial disparity in surgical delay was least pronounced among women treated at a non-profit facility (OR, 1.95; 95% CI, 1.70–2.25). The estimated mortality rate for Black women was two times that for White women (HR, 2.00; 95% CI, 1.83–2.46). Racial disparities in breast cancer mortality were least pronounced among women who experienced no surgical delay (HR, 1.81; 95% CI, 1.28–2.56), received surgery at a government facility (HR, 1.31; 95% CI, 0.76–2.27), or underwent treatment at a Commission on Cancer-accredited facility (HR, 1.82; 95% CI, 1.38–2.40).

Conclusions

Black women were more likely to experience a surgical delay and breast cancer death. Persistent racial disparities in breast cancer mortality were observed across facility characteristics except for government facilities.

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References

  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;66:31–42. https://doi.org/10.3322/caac.21320.

    Article  PubMed  Google Scholar 

  2. Aizer AA, Wilhite TJ, Chen M-H, et al. Lack of reduction in racial disparities in cancer-specific mortality over a 20-year period. Cancer. 2014;120:1532–9. https://doi.org/10.1002/cncr.28617.

    Article  PubMed  Google Scholar 

  3. DeSantis CE, Siegel RL, Sauer AG, et al. Cancer statistics for African Americans, 2016: progress and opportunities in reducing racial disparities. CA Cancer J Clin. 2016;66:290–308. https://doi.org/10.3322/caac.21340.

    Article  PubMed  Google Scholar 

  4. DeSantis CE, Ma J, Sauer AG, Newman LA, Jemal A. Breast cancer statistics, 2017, racial disparity in mortality by state. CA Cancer J Clin. 2017;67:439–48. https://doi.org/10.3322/caac.21412.

    Article  PubMed  Google Scholar 

  5. Collin LJ, Jiang R, Ward KC, et al. Racial disparities in breast cancer outcomes in the metropolitan Atlanta area: new insights and approaches for health equity. JNCI Cancer Spectr. 2019. https://doi.org/10.1093/jncics/pkz053.

    Article  PubMed  PubMed Central  Google Scholar 

  6. George P, Chandwani S, Gabel M, et al. Diagnosis and surgical delays in African American and white women with early-stage breast cancer. J Womens Health Larchmt. 2015;24:209–17. https://doi.org/10.1089/jwh.2014.4773.

    Article  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  8. Miller-Kleinhenz JM, Collin LJ, Seidel R, et al. Racial disparities in diagnostic delay among women with breast cancer. J Am Coll Radiol. <AQ4> Published online 16 July 2021:S1546-1440(21)00549–4. Doi:https://doi.org/10.1016/j.jacr.2021.06.019.

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

    Article  PubMed  Google Scholar 

  10. Fedewa SA, Edge SB, Stewart AK, Halpern MT, Marlow NM, Ward EM. Race and ethnicity are associated with delays in breast cancer treatment (2003–2006). J Health Care Poor Underserved. 2011;22:128–41.

    PubMed  Google Scholar 

  11. Bilimoria KY, Ko CY, Tomlinson JS, et al. Wait times for cancer surgery in the United States: trends and predictors of delays. Ann Surg. 2011;253:779–85. https://doi.org/10.1097/SLA.0b013e318211cc0f.

    Article  PubMed  Google Scholar 

  12. McLaughlin JM, Anderson RT, Ferketich AK, Seiber EE, Balkrishnan R, Paskett ED. Effect on survival of longer intervals between confirmed diagnosis and treatment initiation among low-income women with breast cancer. J Clin Oncol. 2012;30:4493–500. https://doi.org/10.1200/JCO.2012.39.7695.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Guller U, Safford S, Pietrobon R, Heberer M, Oertli D, Jain NB. High hospital volume is associated with better outcomes for breast cancer surgery: analysis of 233,247 patients. World J Surg. 2005;29: 994–9; Discussion 999–1000. Doi:https://doi.org/10.1007/s00268-005-7831-z.

  14. Keating NL, Kouri E, He Y, Weeks JC, Winer EP. Racial differences in definitive breast cancer therapy in older women: Are they explained by the hospitals where patients undergo surgery? Med Care. 2009;47:765–73. https://doi.org/10.1097/MLR.0b013e31819e1fe7.

    Article  PubMed  Google Scholar 

  15. Wheeler SB, Reeder-Hayes KE, Carey LA. Disparities in breast cancer treatment and outcomes: biological, social, and health system determinants and opportunities for research. Oncologist. 2013;18:986–93. https://doi.org/10.1634/theoncologist.2013-0243.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Howe HL. NAACCR Guideline for Enhancing Hispanic-Latino Identification: Revised NAACCR Hispanic/Latino Identification Algorithm [NHIA V2].; 2005. <PUB1>

  17. Warren JL, Klabunde CN, Schrag D, Bach PB, Riley GF. Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population. Med Care. 2002;40: IV3–18.

  18. Enewold L, Parsons H, Zhao L, et al. Updated overview of the SEER-Medicare data: enhanced content and applications. JNCI Monogr. 2020;2020:3–13. https://doi.org/10.1093/jncimonographs/lgz029.

    Article  Google Scholar 

  19. Bleicher RJ. Timing and delays in breast cancer evaluation and treatment. Ann Surg Oncol. 2018;25:2829–38. https://doi.org/10.1245/s10434-018-6615-2.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Knoble NB, Alderfer MA, Hossain MJ. Socioeconomic status (SES) and childhood acute myeloid leukemia (AML) mortality risk: analysis of SEER data. Cancer Epidemiol. 2016;44:101–8. https://doi.org/10.1016/j.canep.2016.07.007.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Kish JK, Yu M, Percy-Laurry A, Altekruse SF. Racial and ethnic disparities in cancer survival by neighborhood socioeconomic status in Surveillance, Epidemiology, and End Results (SEER) registries. J Natl Cancer Inst Monogr. 2014;2014:236–43. https://doi.org/10.1093/jncimonographs/lgu020.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Knol MJ, VanderWeele TJ. Recommendations for presenting analyses of effect modification and interaction. Int J Epidemiol. 2012;41:514–20. https://doi.org/10.1093/ije/dyr218.

    Article  PubMed  PubMed Central  Google Scholar 

  23. VanderWeele TJ, Knol MJ. A tutorial on interaction. Epidemiol Methods. 2014;3:33–72. https://doi.org/10.1515/em-2013-0005.

    Article  Google Scholar 

  24. Hosmer DW, Lemeshow S. Confidence interval estimation of interaction. Epidemiology. 1992;3:452–6.

    Article  CAS  Google Scholar 

  25. Starr JR, McKnight B. Assessing interaction in case-control studies: type I errors when using both additive and multiplicative scales. Epidemiology. 2004;15:422–7.

    Article  Google Scholar 

  26. Ward JB, Gartner DR, Keyes KM, Fliss MD, McClure ES, Robinson WR. How do we assess a racial disparity in health? Distribution, interaction, and interpretation in epidemiological studies. Ann Epidemiol. 2019;29:1–7. https://doi.org/10.1016/j.annepidem.2018.09.007.

    Article  PubMed  Google Scholar 

  27. Howards PP, Schisterman EF, Poole C, Kaufman JS, Weinberg CR. Toward a clearer definition of confounding revisited with directed acyclic graphs. Am J Epidemiol. 2012;176:506–11. https://doi.org/10.1093/aje/kws127.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Lash TL. The harm done to reproducibility by the culture of null hypothesis significance testing. Am J Epidemiol. 2017;186:627–35. https://doi.org/10.1093/aje/kwx261.

    Article  PubMed  Google Scholar 

  29. Wasserstein RL, Lazar NA. The ASA Statement on p values: context, process, and purpose. Am Statistician. 2016;70:129–33. https://doi.org/10.1080/00031305.2016.1154108.

    Article  Google Scholar 

  30. Liederbach E, Sisco M, Wang C, et al. Wait times for breast surgical operations, 2003–2011: a report from the National Cancer Database. Ann Surg Oncol. 2015;22:899–907. https://doi.org/10.1245/s10434-014-4086-7.

    Article  PubMed  Google Scholar 

  31. Sheppard VB, Oppong BA, Hampton R, et al. Disparities in breast cancer surgery delay: the lingering effect of race. Ann Surg Oncol. 2015;22:2902–11. https://doi.org/10.1245/s10434-015-4397-3.

    Article  PubMed  Google Scholar 

  32. Khader A, Chang S-C, Santamaria-Barria J, et al. Delay in surgery is associated with axillary upstaging of clinically node negative breast cancer patients. J Surg Oncol. 2021;123:854–65. https://doi.org/10.1002/jso.26332.

    Article  PubMed  Google Scholar 

  33. Wagner JL, Warneke CL, Mittendorf EA, et al. Delays in primary surgical treatment are not associated with significant tumor size progression in breast cancer patients. Ann Surg. 2011;254:119–24. https://doi.org/10.1097/SLA.0b013e318217e97f.

    Article  PubMed  Google Scholar 

  34. Bleicher RJ, Ruth K, Sigurdson ER, et al. Time to surgery and breast cancer survival in the United States. JAMA Oncol. 2016;2:330–9. https://doi.org/10.1001/jamaoncol.2015.4508.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Greenup RA, Obeng-Gyasi S, Thomas S, et al. The effect of hospital volume on breast cancer mortality. Ann Surg. 2018;267:375–81. https://doi.org/10.1097/SLA.0000000000002095.

    Article  PubMed  Google Scholar 

  36. Greenwood BN, Hardeman RR, Huang L, Sojourner A. Physician–patient racial concordance and disparities in birthing mortality for newborns. PNAS. 2020;117:21194–200. https://doi.org/10.1073/pnas.1913405117.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Meghani SH, Brooks JM, Gipson-Jones T, Waite R, Whitfield-Harris L, Deatrick JA. Patient–provider race-concordance: does it matter in improving minority patients’ health outcomes? Ethnicity Health. 2009;14:107–30. https://doi.org/10.1080/13557850802227031.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Zhou J, Enewold L, Zahm SH, et al. Breast conserving surgery versus mastectomy: the influence of comorbidities on choice of surgical operation in the Department of Defense health care system. Am J Surg. 2013;206:393–9. https://doi.org/10.1016/j.amjsurg.2013.01.034.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Simunovic M, Thériault M-E, Paszat L, et al. Using administrative databases to measure waiting times for patients undergoing major cancer surgery in Ontario, 1993–2000. Can J Surg. 2005;48:137–42.

    PubMed  PubMed Central  Google Scholar 

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Acknowledgments

This this work was supported in part by the Cancer Prevention and Control Research program; the Winship Research Informatics shared resources, a core supported by the Winship Cancer Institute of Emory University; and the Komen Foundation (CCR19608510) awarded to Lauren E McCullough. Lindsay J. Collin was supported by TL1TR002540 from the National Center for Advancing Translational Sciences of the National Institutes of Health. Jasmine M. Miller-Kleinhenz was supported NIH/NIGMS (2K12GM000680). The collection of cancer incidence data used in this study was supported by contract HHSN261201800003I, Task Order HHSN26100001 from the NCI and cooperative agreement 5NU58DP003875-04 from the U.S. Centers for Disease Control and Prevention.

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Correspondence to Lindsay J. Collin PhD.

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Collin, L.J., Ross-Driscoll, K., Nash, R. et al. Time to Surgical Treatment and Facility Characteristics as Potential Drivers of Racial Disparities in Breast Cancer Mortality. Ann Surg Oncol 29, 4728–4738 (2022). https://doi.org/10.1245/s10434-022-11720-z

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