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Multilevel contributors to racial and ethnic inequities in the resolution of abnormal mammography results

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Abstract

Purpose

Multiple ecological levels influence racial inequities in the completion of diagnostic testing after receiving abnormal mammography results (diagnostic resolution). Yet, few studies examine more than two ecological levels. We investigated the contributions of county, imaging facility, and patient characteristics on our primary and secondary outcomes, the achievement of diagnostic resolution by (1)Black women and Latinas, and (2) the entire sample. We hypothesized that women of color would be less likely to achieve resolution than their White counterparts, and this relationship would be mediated by imaging facility features and moderated by county characteristics.

Methods

Records for 25,144 women with abnormal mammograms between 2011 and 2019 from the Carolina Mammography Registry were merged with publicly available county data. Diagnostic resolution was operationalized as the percentage of women achieving resolution within 60 days of receiving abnormal results and overall time to resolution and examined using mixed effects logistic regression and Cox proportional hazard models, respectively.

Results

Women of color with abnormal screening mammograms were less likely to achieve resolution within 60 days compared with White women (OR 0.83, CI 0.78–0.89; OR 0.74, CI.60–0.91, respectively) and displayed longer resolution times (HR 0.87, CI 0.84–0.91; HR 0.78, CI 0.68–0.89). Residential segregation had a moderating effect, with Black women in more segregated counties being less likely to achieve resolution by 60 days but lost statistical significance after adjustment. No mediators were discovered.

Conclusion

More work is needed to understand how imaging center and community characteristics impact racial inequities in resolution and resolution in general.

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Data Availability

Study data are available with approval from the data contributing sites and upon request from Dr. Henderson.

References

  1. Islami F, Guerra CE, Minihan A et al (2022) American Cancer Society’s report on the status of cancer disparities in the United States, 2021. CA Cancer J Clin 72(2):112–143. https://doi.org/10.3322/caac.21703

    Article  PubMed  Google Scholar 

  2. Giaquinto AN, Miller KD, Tossas KY, Winn RA, Jemal A, Siegel RL (2022) Cancer statistics for African American/Black People 2022. CA Cancer J Clin. https://doi.org/10.3322/caac.21718

    Article  PubMed  Google Scholar 

  3. Miller KD, Ortiz AP, Pinheiro PS et al (2021) Cancer statistics for the US Hispanic/Latino population, 2021. CA Cancer J Clin 71(6):466–487. https://doi.org/10.3322/caac.21695

    Article  PubMed  Google Scholar 

  4. Serrano-Gomez SJ, Sanabria-Salas MC, Fejerman L (2020) Breast cancer health disparities in Hispanics/Latinas. Curr Breast Cancer Rep 12(3):175–184. https://doi.org/10.1007/s12609-020-00370-3

    Article  PubMed  PubMed Central  Google Scholar 

  5. DeSantis CE, Ma J, Gaudet MM et al (2019) Breast cancer statistics, 2019. CA Cancer J Clin 69(6):438–451. https://doi.org/10.3322/caac.21583

    Article  PubMed  Google Scholar 

  6. Warner ET, Tamimi RM, Hughes ME et al (2012) Time to diagnosis and breast cancer stage by race/ethnicity. Breast Cancer Res Treat 136(3):813–821. https://doi.org/10.1007/s10549-012-2304-1

    Article  PubMed  PubMed Central  Google Scholar 

  7. Neal RD, Tharmanathan P, France B et al (2015) Is increased time to diagnosis and treatment in symptomatic cancer associated with poorer outcomes? Systematic rev Br J Cancer 112(1):S92–S107. https://doi.org/10.1038/bjc.2015.48

    Article  Google Scholar 

  8. DeGroff A, Royalty JE, Howe W et al (2014) When performance management works: a study of the national breast and cervical cancer early detection program: performance management and public health. Cancer 120(S16):2566–2574. https://doi.org/10.1002/cncr.28817

    Article  PubMed  Google Scholar 

  9. Richardson LC, Royalty J, Howe W, Helsel W, Kammerer W, Benard VB (2010) Timeliness of breast cancer diagnosis and initiation of treatment in the national breast and cervical cancer early detection program, 1996–2005. Am J Public Health 100(9):1769

    Article  PubMed  PubMed Central  Google Scholar 

  10. Ashing-Giwa KT, Gonzalez P, Lim JW et al (2010) Diagnostic and therapeutic delays among a multiethnic sample of breast and cervical cancer survivors. Cancer 116(13):3195–3204. https://doi.org/10.1002/cncr.25060

    Article  PubMed  Google Scholar 

  11. Pérez-Stable EJ, Afable-Munsuz A, Kaplan CP et al (2013) Factors influencing time to diagnosis after abnormal mammography in diverse women. J Womens Health 22(2):159–166. https://doi.org/10.1089/jwh.2012.3646

    Article  Google Scholar 

  12. Miller-Kleinhenz JM, Collin LJ, Seidel R et al (2021) Racial disparities in diagnostic delay among women with breast cancer. J Am Coll Radiol 18(10):1384–1393. https://doi.org/10.1016/j.jacr.2021.06.019

    Article  PubMed  PubMed Central  Google Scholar 

  13. Ramirez AG, Pérez-stable EJ, Talavera GA et al (2013) Time to definitive diagnosis of breast cancer in Latina and non-Hispanic white women: the six cities study. Springerplus 2(1):1–9. https://doi.org/10.1186/2193-1801-2-84

    Article  Google Scholar 

  14. Jaiswal K, Hull M, Furniss AL, Doyle R, Gayou N, Bayliss E (2018) Delays in diagnosis and treatment of breast cancer: a safety-net population profile. J Natl Compr Canc Netw 16(12):1451–1457. https://doi.org/10.6004/jnccn.2018.7067

    Article  PubMed  Google Scholar 

  15. Reece JC, Neal EFG, Nguyen P, McIntosh JG, Emery JD (2021) Delayed or failure to follow-up abnormal breast cancer screening mammograms in primary care: a systematic review. BMC Cancer 21:1–14. https://doi.org/10.1186/s12885-021-08100-3

    Article  Google Scholar 

  16. Oluyemi ET, Grimm LJ, Goldman L et al (2023) Rate and timeliness of diagnostic evaluation and biopsy after recall from screening mammography in the national mammography database. J Am Coll Radiol. https://doi.org/10.1016/j.jacr.2023.09.002

    Article  PubMed  Google Scholar 

  17. Rosenberg RD, Haneuse SJ, Geller BM et al (2011) Timeliness of follow-up after abnormal screening mammogram: variability of facilities. Radiology 261(2):404–413

    Article  PubMed  PubMed Central  Google Scholar 

  18. Molina Y, Silva A, Rauscher GH (2015) Racial/ethnic disparities in time to a breast cancer diagnosis: the mediating effects of health care facility factors. Med Care 53(10):872–878

    Article  PubMed  PubMed Central  Google Scholar 

  19. Collin LJ, Gaglioti AH, Beyer KM et al (2021) Neighborhood-level redlining and lending bias are associated with breast cancer mortality in a large and diverse metropolitan area. Cancer Epidemiol Biomark Prev Publ Am Assoc Cancer Res Cosponsored Am Soc Prev Oncol 30(1):53–60. https://doi.org/10.1158/1055-9965.EPI-20-1038

    Article  CAS  Google Scholar 

  20. Mojica CM, Bastani R, Ponce NA, Boscardin WJ (2007) Latinas with abnormal breast findings: patient predictors of timely diagnostic resolution. J Womens Health 16(10):1468–1477. https://doi.org/10.1089/jwh.2006.0324

    Article  Google Scholar 

  21. Nyante SJ, Abraham L, Aiello Bowles EJ et al (2022) Diagnostic mammography performance across racial and ethnic groups in a national network of community-based breast imaging facilities. Cancer Epidemiol Biomarkers Prev 31(7):1324–1333. https://doi.org/10.1158/1055-9965.EPI-21-1379

    Article  PubMed  PubMed Central  Google Scholar 

  22. Plascak JJ, Llanos AA, Pennell ML, Weier RC, Paskett ED (2014) Neighborhood factors associated with time to resolution following an abnormal breast or cervical cancer screening test. Cancer Epidemiol Biomarkers Prev. https://doi.org/10.1158/1055-9965.EPI-14-0348

    Article  PubMed  PubMed Central  Google Scholar 

  23. Fang CY, Tseng M (2018) Ethnic density and cancer: A review of the evidence. Cancer 124(9):1877–1903. https://doi.org/10.1002/cncr.31177

    Article  PubMed  Google Scholar 

  24. Fowler BA (2014) Neighborhood-level influences on delays in diagnostic follow-up from mammography screening in African-American Women: a systematic review. J Womens Health Care. https://doi.org/10.4172/2167-0420.1000151

    Article  Google Scholar 

  25. Krieger N, Wright E, Chen JT, Waterman PD, Huntley ER, Arcaya M (2020) Cancer stage at diagnosis, historical redlining, and current neighborhood characteristics: breast, cervical, lung, and colorectal cancers, massachusetts, 2001–2015. Am J Epidemiol 189(10):1065–1075. https://doi.org/10.1093/aje/kwaa045

    Article  PubMed  PubMed Central  Google Scholar 

  26. Zahnd WE, McLafferty SL (2017) Contextual effects and cancer outcomes in the United States: a systematic review of characteristics in multilevel analyses. Ann Epidemiol 27(11):739-748.e3. https://doi.org/10.1016/j.annepidem.2017.10.002

    Article  PubMed  Google Scholar 

  27. Warnecke RB, Campbell RT, Vijayasiri G, Barrett RE, Rauscher GH (2019) Multilevel examination of health disparity: the role of policy implementation in neighborhood context, in patient resources, and in healthcare facilities on later stage of breast cancer diagnosis. Cancer Epidemiol Biomark Prev Publ Am Assoc Cancer Res Cosponsored Am Soc Prev Oncol 28(1):59–66. https://doi.org/10.1158/1055-9965.EPI-17-0945

    Article  Google Scholar 

  28. Eberl MM, Fox CH, Edge SB, Carter CA, Mahoney MC (2006) BI-RADS classification for management of abnormal mammograms. J Am Board Fam Med 19(2):161–164. https://doi.org/10.3122/jabfm.19.2.161

    Article  PubMed  Google Scholar 

  29. Lawson MB, Bissell MCS, Miglioretti DL et al (2022) Multilevel factors associated with time to biopsy after abnormal screening mammography results by race and ethnicity. JAMA Oncol 8(8):1115–1126. https://doi.org/10.1001/jamaoncol.2022.1990

    Article  PubMed  PubMed Central  Google Scholar 

  30. Anderson RT, Hillemeier MM, Camacho FT et al (2023) The breast-imaging operations, practices and systems inventory: a framework to examine mammography facility effects on screening in rural communities. J Rural Health. https://doi.org/10.1111/jrh.12798

    Article  PubMed  Google Scholar 

  31. Himmelstein G, Himmelstein KEW (2020) Inequality set in concrete: physical resources available for care at hospitals serving people of color and other U.S. Hospitals. Int J Health Serv 50(4):363–370. https://doi.org/10.1177/0020731420937632

    Article  PubMed  Google Scholar 

  32. Eberth JM, Hung P, Benavidez GA et al (2022) The problem of the color line: spatial access to hospital services for minoritized racial and ethnic groups. Health Aff (Millwood) 41(2):237–246. https://doi.org/10.1377/hlthaff.2021.01409

    Article  PubMed  Google Scholar 

  33. Williams DR, Mohammed SA, Shields AE (2016) Understanding and effectively addressing breast cancer in African American women: unpacking the social context. Cancer 122(14):2138–2149. https://doi.org/10.1002/cncr.29935

    Article  PubMed  Google Scholar 

  34. Wheeler SB, Reeder-Hayes KE, Carey LA (2013) Disparities in breast cancer treatment and outcomes: biological, social, and health system determinants and opportunities for research. Oncologist 18(9):986–993. https://doi.org/10.1634/theoncologist.2013-0243

    Article  PubMed  PubMed Central  Google Scholar 

  35. Bailey ZD, Krieger N, Agénor M, Graves J, Linos N, Bassett MT (2017) Structural racism and health inequities in the USA: evidence and interventions. The Lancet 389(10077):1453–1463. https://doi.org/10.1016/S0140-6736(17)30569-X

    Article  Google Scholar 

  36. Gee GC, Ford CL (2011) STRUCTURAL RACISM AND HEALTH INEQUITIES. Bois Rev Soc Sci Res Race 8(01):115–132. https://doi.org/10.1017/S1742058X11000130

    Article  Google Scholar 

  37. Braveman PA, Arkin E, Proctor D, Kauh T, Holm N (2022) Systemic and structural racism: definitions, examples, health damages. And Approaches To Dismantling Health Aff (Millwood) 41(2):171–178. https://doi.org/10.1377/hlthaff.2021.01394

    Article  PubMed  Google Scholar 

  38. Groos M, Wallace M, Hardeman R, Theall KP (2018) Measuring inequity: a systematic review of methods used to quantify structural racism. J Health Disparities Res Pract 11(2):16

    Google Scholar 

  39. Yankaskas BC (2021) Population-Based Mammography Registry. NORTH CAROLINA UNIV AT CHAPEL HILL; 1998. Accessed April 26 2021. https://apps.dtic.mil/sti/citations/ADA361525

  40. Ballard-Barbash R, Taplin SH, Yankaskas BC et al (1997) Breast cancer surveillance consortium: a national mammography screening and outcomes database. Am J Roentgenol 169(4):1001–1008. https://doi.org/10.2214/ajr.169.4.9308451

    Article  CAS  Google Scholar 

  41. D’Orsi CJ, Sickles EA, Mendelson EB (2013) ACR BI-RADS Atlas, Breast Imaging Reporting and Data System, 2nd edn. American College of Radiology, Reston

    Google Scholar 

  42. University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps. County Health Rankings & Roadmaps. Published 2020. Accessed November 21 2022. https://www.countyhealthrankings.org/explore-health-rankings/rankings-data-documentation/national-data-documentation-2010-2019

  43. United States Census Bureau. 2020 American Community Survey 5-Year Estimates - Selected social characteristics [Data file]. Published 2022. Accessed November 21 2022. https://data.census.gov/table?tid=ACSDP1Y2021.DP04

  44. United States Census Bureau. 2020 American Community Survey 5-Year Estimates - Poverty status in the past 12 months [Data file]. Published 2022. Accessed November 21 2022. https://data.census.gov/table?tid=ACSDP1Y2021.DP04

  45. Sobel ME (1982) Asymptotic confidence intervals for indirect effects in structural equation models. Sociol Methodol 13:290–312. https://doi.org/10.2307/270723

    Article  Google Scholar 

  46. Schafer JL (1997) Analysis of incomplete multivariate data. Chapman and Hall/CRC. https://doi.org/10.1201/9780367803025

    Article  Google Scholar 

  47. Rubin DB (1976) Inference and missing data. Biometrika 63(3):581–592. https://doi.org/10.2307/2335739

    Article  MathSciNet  Google Scholar 

  48. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol 57(1):289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x

    Article  MathSciNet  Google Scholar 

  49. Landrine H, Corral I, Lee JGL, Efird JT, Hall MB, Bess JJ (2016) Residential segregation and racial cancer disparities: a systematic review. J Racial Ethn Health Disparities. https://doi.org/10.1007/s40615-016-0326-9

    Article  PubMed  Google Scholar 

  50. Plascak JJ, Rundle AG, Xu X et al (2022) Associations between neighborhood disinvestment and breast cancer outcomes within a populous state registry. Cancer 128(1):131–138. https://doi.org/10.1002/cncr.33900

    Article  CAS  PubMed  Google Scholar 

  51. Sorice KA, Fang CY, Wiese D et al (2022) Systematic review of neighborhood socioeconomic indices studied across the cancer control continuum. Cancer Med 11(10):2125–2144. https://doi.org/10.1002/cam4.4601

    Article  PubMed  PubMed Central  Google Scholar 

  52. Rent Debt in America: Stabilizing Renters Is Key to Equitable Recovery | National Equity Atlas. Accessed September 11 2022. https://nationalequityatlas.org/rent-debt-in-america-08-10-2021

  53. Tangka F, Kenny K, Miller J, Howard DH (2020) The eligibility and reach of the national breast and cervical cancer early detection program after implementation of the affordable care act. Cancer Causes Control CCC 31(5):473–489. https://doi.org/10.1007/s10552-020-01286-0

    Article  PubMed  PubMed Central  Google Scholar 

  54. Rice LJ, Halbert CH (2017) Chapter Five - Social Networks Across Common Cancer Types: The Evidence, Gaps, and Areas of Potential Impact. In: Ford ME, Watson DK (eds) Advances in Cancer Research. Cancer Disparities. Elsevier, Amsterdam

    Google Scholar 

  55. Rauscher GH, Ferrans CE, Kaiser K, Campbell R, Calhoun E, Warnecke RB (2010) Misconceptions about breast lumps and delayed medical presentation in urban breast cancer patients. Cancer Epidemiol Biomark Prev Publ Am Assoc Cancer Res Cosponsored Am Soc Prev Oncol 19(3):640–647. https://doi.org/10.1158/1055-9965.EPI-09-0997

    Article  Google Scholar 

  56. Szukis HA, Qin B, Xing CY et al (2019) Factors associated with initial mode of breast cancer detection among black Women in the Women’s circle of health study. J Oncol 2019:e3529651. https://doi.org/10.1155/2019/3529651

    Article  Google Scholar 

  57. White K, Haas JS, Williams DR (2012) Elucidating the role of place in health care disparities: the example of racial/ethnic residential segregation. Health Serv Res 47(3pt2):1278–1299. https://doi.org/10.1111/j.1475-6773.2012.01410.x

    Article  PubMed  PubMed Central  Google Scholar 

  58. Barber LE, Zirpoli GR, Cozier YC et al (2021) Neighborhood disadvantage and individual-level life stressors in relation to breast cancer incidence in US Black Women. Breast Cancer Res 23(1):108. https://doi.org/10.1186/s13058-021-01483-y

    Article  PubMed  PubMed Central  Google Scholar 

  59. Goel N, Westrick AC, Bailey ZD et al (2022) Structural racism and breast cancer-specific survival : impact of economic and racial residential segregation. Ann Surg 275(4):776–783. https://doi.org/10.1097/SLA.0000000000005375

    Article  PubMed  Google Scholar 

  60. Geronimus AT, Hicken M, Keene D, Bound J (2006) “Weathering” and age patterns of allostatic load scores among blacks and whites in the United States. Am J Public Health 96(5):826–833

    Article  PubMed  PubMed Central  Google Scholar 

  61. Ibekwe LN, Fernández-Esquer ME, Pruitt SL, Ranjit N, Fernández ME (2022) Associations between perceived racial discrimination, racial residential segregation, and cancer screening adherence among low-income African Americans: a multilevel, cross-sectional analysis. Ethn Health. https://doi.org/10.1080/13557858.2022.2043246

    Article  PubMed  Google Scholar 

  62. Martin P, Liaw W, Bazemore A, Jetty A, Petterson S, Kushel M (2019) Adults with housing insecurity have worse access to primary and preventive care. J Am Board Fam Med 32(4):521–530. https://doi.org/10.3122/jabfm.2019.04.180374

    Article  PubMed  Google Scholar 

  63. Taylor L (2018) Housing and health: an overview of the literature. Health Aff Health Policy Brief. https://doi.org/10.1377/hpb20180313.396577

    Article  Google Scholar 

  64. Joint Center for Housing Studies of Harvard University (2019) The State of the Nation’s Housing 2019. Harvard University, Cambridge

    Google Scholar 

  65. Rohe W, Owens T, Kerns S (2017) Extreme Housing Conditions in North Carolina. Center for Urban and Regional Studies The University of North Carolina at Chapel Hill

  66. US Census Bureau. 2016–2020 American Community Survey 5-Year Estimate 2022. http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?fpt=table

  67. Larson K, Mathews HF, Torres E, Lea CS (2017) Responding to health and social needs of aging Latinos in new-growth communities: a qualitative study. BMC Health Serv Res 17(1):601. https://doi.org/10.1186/s12913-017-2551-2

    Article  PubMed  PubMed Central  Google Scholar 

  68. Philbin MM, Flake M, Hatzenbuehler ML, Hirsch JS (2018) State-level immigration and immigrant-focused policies as drivers of Latino health disparities in the United States. Soc Sci Med 199:29–38. https://doi.org/10.1016/j.socscimed.2017.04.007

    Article  PubMed  Google Scholar 

  69. Asad AL, Clair M (2018) Racialized legal status as a social determinant of health. Soc Sci Med 199:19–28. https://doi.org/10.1016/j.socscimed.2017.03.010

    Article  PubMed  Google Scholar 

  70. State Cancer Profiles > 5-Year Rate Changes. Accessed November 16 2022. https://statecancerprofiles.cancer.gov/recenttrend/index.php?0&00&0&9599&136&999&38&2&0&0&2#results

  71. Blake KD, Moss JL, Gaysynsky A, Srinivasan S, Croyle RT (2017) Making the case for investment in rural cancer control: an analysis of rural cancer incidence, mortality, and funding trends. Cancer Epidemiol Biomarkers Prev 26(7):992–997. https://doi.org/10.1158/1055-9965.EPI-17-0092

    Article  PubMed  PubMed Central  Google Scholar 

  72. Zahnd WE, Murphy C, Knoll M et al (2021) The Intersection of Rural Residence and Minority Race/Ethnicity in Cancer Disparities in the United States. Int J Environ Res Public Health. https://doi.org/10.3390/ijerph18041384

    Article  PubMed  PubMed Central  Google Scholar 

  73. Polite BN, Adams-Campbell LL, Brawley OW et al (2017) Charting the future of cancer health disparities research: a position statement from the American association for cancer research, the American cancer society, the American society of clinical oncology, and the national cancer institute. Cancer Res. https://doi.org/10.1158/0008-5472.CAN-17-0623

    Article  PubMed  Google Scholar 

  74. Doherty JA, Johnson M, McPheron H (2022) Advancing health equity through organizational change: perspectives from health care leaders. Health Care Manage Rev 47(3):263–270. https://doi.org/10.1097/HMR.0000000000000326

    Article  PubMed  Google Scholar 

  75. Institute for Healthcare Improvement. Health Equity: Prioritization, Perception, and Progress. Institute for Healthcare Improvement. 2021:1–9

  76. McIver DL. 2022 Cms Framework for Health Equity 2022–2032. Published online 2022:40.

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Acknowledgements

This work was supposed by funding from the National Cancer Institute under Grant# U01CA70040 and P01CA154292. We would like to thank the women and imaging facilities that have provided data to the Carolina Mammography Registry.

Funding

This work was supported by funding from the National Cancer Institute under Grant# U01CA70040 and P01CA154292.

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Authors and Affiliations

  1. Department of Health Education and Promotion, College of Health and Human Performance, East Carolina University, 2307 Carol G. Belk Building, Mail Stop 529, Greenville, NC, 27858, USA

    Deeonna E. Farr

  2. Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA

    Thad Benefield & Louise M. Henderson

  3. School of Social Work, College of Health and Human Performance, East Carolina University, Greenville, NC, 27858, USA

    Mi Hwa Lee

  4. Office of the Vice Chancellor for Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-4000, USA

    Essie Torres

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Contributions

CRediT Statement—DF: Conceptualization, Methodology, Writing—Original Draft; TB: Methodology, Formal Analysis, Writing—Review and Editing; MHL: Writing—Review and Editing; ET: Writing—Review and Editing; LH: Supervision, Funding Acquisition, Writing—Review and Editing.

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Correspondence to Deeonna E. Farr.

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The authors declare no potential conflicts of interest.

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Data used in this study came from the Carolina Mammography Registry (CMR). The CMR was approved by the University of North Carolina Institutional Review Board with a waiver of informed consent for research and a waiver of HIPAA authorization.

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Data used in this study came from the Carolina Mammography Registry (CMR). The CMR was approved by the University of North Carolina Institutional Review Board with a waiver of informed consent for research and a waiver of HIPAA authorization.

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Farr, D.E., Benefield, T., Lee, M.H. et al. Multilevel contributors to racial and ethnic inequities in the resolution of abnormal mammography results. Cancer Causes Control (2024). https://doi.org/10.1007/s10552-024-01851-x

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