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Self-reported barriers to screening breast MRI among women at high risk for breast cancer

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

Abstract

Background

Annual screening breast MRI is recommended for women at high (≥ 20% lifetime) breast cancer risk, but is underutilized. Guided by the Health Services Utilization Model (HSUM), we assessed factors associated with screening breast MRI among high-risk women.

Methods

From August 2020–January 2021, we recruited an online convenience sample of high-risk women ages 25–85 (N = 232). High-risk was defined as: pathogenic genetic mutation in self or first-degree relative; history of lobular carcinoma in situ; history of thoracic radiation; or estimated lifetime risk ≥ 20%. Participants self-reported predisposing factors (breast cancer knowledge, health locus of control), enabling factors (health insurance type, social support), need factors (perceived risk, screening-supportive social norms, provider recommendation), and prior receipt of screening breast MRI. Multivariable logistic regression analysis with backward selection identified HSUM factors associated with receipt of screening breast MRI.

Results

About half (51%) of participants had received a provider recommendation for screening breast MRI; only 32% had ever received a breast MRI. Breast cancer knowledge (OR = 1.15, 95% CI = 1.04–1.27) and screening-supportive social norms (OR = 2.21, 95% CI = 1.64–2.97) were positively related to breast MRI receipt. No other HSUM variables were associated with breast MRI receipt (all p’s > 0.1).

Conclusions

High-risk women reported low uptake of screening breast MRI, indicating a gap in guideline-concordant care. Breast cancer knowledge and screening-supportive social norms are two key areas to target in future interventions. Data were collected during the COVID-19 pandemic and generalizability of results is unclear. Future studies with larger, more heterogeneous samples are needed to replicate these findings.

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Data availability

Data are publicly available at https://osf.io/xpz35/.

Notes

  1. ACR guidelines recommend annual mammography starting at age 40. Thus, we originally intended to exclude women who had not received a mammogram in the past year. However, given that data collection occurred during the early months of the COVID-19 pandemic, and screening availability may have been limited, we elected to extend the time period in which participants were considered “up to date” on screening to two years.

References

  1. Siegel RL et al (2022) Cancer Statistics, 2022 CA: A Cancer Journal for Clinicians, 72(1): p. 7–33

  2. Monticciolo DL et al (2018) Breast Cancer Screening in Women at Higher-Than-Average risk: recommendations from the ACR. J Am Coll Radiol 15(3 Pt A):408–414

    Article  PubMed  Google Scholar 

  3. Saslow D et al (2007) American Cancer Society guidelines for breast screening with MRI as an adjunct to mammography CA: A Cancer Journal for Clinicians. 57(2):75–89

  4. National Comprehensive Cancer Network (NCCN). Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic (Version 2.2022). NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) 2022 June 24, 2022]; Available from: https://www.nccn.org/professionals/physician_gls/pdf/genetics_bop.pdf

  5. Morman NA et al (2017) Breast cancer risk assessment at the time of screening mammography: perceptions and clinical management outcomes for women at high risk. J Genet Couns 26(4):776–784

    Article  PubMed  Google Scholar 

  6. Niell B et al (2021) Distribution of estimated lifetime breast cancer risk in women undergoing screening mammography. Am J Roentgenol 217(1):48–55

    Article  Google Scholar 

  7. Lehman CD (2006) Role of MRI in screening women at high risk for breast cancer. J Magn Reson Imaging 24(5):964–970

    Article  PubMed  Google Scholar 

  8. Group MS (2005) Screening with magnetic resonance imaging and mammography of a UK population at high familial risk of breast cancer: a prospective multicentre cohort study (MARIBS). The Lancet 365(9473):1769–1778

    Article  Google Scholar 

  9. Geuzinge HA et al (2020) Cost-effectiveness of breast cancer screening with magnetic resonance imaging for women at familial risk. JAMA Oncol 6(9):1381–1389

    Article  PubMed  Google Scholar 

  10. Miles R et al (2018) Underutilization of supplemental magnetic resonance imaging screening among patients at high breast cancer risk. J Womens Health 27(6):748–754

    Article  Google Scholar 

  11. Ter-Minassian M et al (2021) Screening and preventive strategies for patients at high risk for breast cancer. JCO Oncol Pract 17(4):e575–e581

    Article  PubMed  Google Scholar 

  12. Wernli KJ et al (2020) Trends in screening breast magnetic resonance imaging use among US women, 2006 to 2016. Cancer 126(24):5293–5302

    Article  CAS  PubMed  Google Scholar 

  13. Andersen RM (1995) Revisiting the behavioral model and access to medical care: does it matter? J Health Soc Behav 36(1):1–10

    Article  CAS  PubMed  Google Scholar 

  14. Davis TC et al (2012) Differences in barriers to mammography between rural and urban women. J women’s health 21(7):748–755

    Article  Google Scholar 

  15. Spurlock WR, Cullins LS (2006) Cancer fatalism and breast cancer screening in african american women. ABNF J, 17(1)

  16. Peppercorn J et al (2015) Breast cancer screening utilization and understanding of current guidelines among rural US women with private insurance. Breast Cancer Res Treat 153(3):659–667

    Article  PubMed  Google Scholar 

  17. Peppercorn J et al (2017) Impact of the elimination of cost sharing for mammographic breast cancer screening among rural US women: a natural experiment. Cancer 123(13):2506–2515

    Article  PubMed  Google Scholar 

  18. Best AL et al (2017) Examining the influence of cost concern and awareness of low-cost Health Care on Cancer Screening among the Medically Underserved. J Health Care Poor Underserved 28(1):79–87

    Article  PubMed  Google Scholar 

  19. Henry KA et al (2014) Association between individual and geographic factors and nonadherence to mammography screening guidelines. J women’s health 23(8):664–674

    Article  Google Scholar 

  20. Peterson EB et al (2016) Impact of provider-patient communication on cancer screening adherence: a systematic review. Prev Med 93:96–105

    Article  PubMed  PubMed Central  Google Scholar 

  21. Meissner HI et al (2012) Breast and colorectal cancer screening: US primary care physicians’ reports of barriers. Am J Prev Med 43(6):584–589

    Article  PubMed  Google Scholar 

  22. Berg WA et al (2009) Reasons women at elevated risk of breast cancer refuse breast MR imaging screening: ACRIN 6666. Radiology 254(1):79–87

    Article  PubMed Central  Google Scholar 

  23. White MC et al (2018) Factors associated with breast MRI use among women with a family history of breast cancer. Breast J 24(5):764–771

    Article  PubMed  Google Scholar 

  24. Costantino JP et al (1999) Validation studies for models projecting the risk of invasive and total breast cancer incidence. J Natl Cancer Inst 91(18):1541–1548

    Article  CAS  PubMed  Google Scholar 

  25. Teitcher JE et al (2015) Detecting, preventing, and responding to “fraudsters” in internet research: ethics and tradeoffs. J Law Med Ethics 43(1):116–133

    Article  PubMed  PubMed Central  Google Scholar 

  26. Monticciolo DL et al (2021) Breast cancer screening recommendations inclusive of all women at average risk: update from the ACR and society of breast imaging. J Am Coll Radiol 18(9):1280–1288

    Article  PubMed  Google Scholar 

  27. Scherr CL, Christie J, Vadaparampil ST (2016) Breast cancer survivors’ knowledge of hereditary breast and ovarian cancer following genetic counseling: an exploration of general and survivor-specific knowledge items. Public health genomics 19(1):1–10

    Article  PubMed  Google Scholar 

  28. Wallston KA, Strudler Wallston B, DeVellis R (1978) Development of the multidimensional health locus of control (MHLC) scales. Health Educ Monogr 6(1):160–170

    Article  CAS  PubMed  Google Scholar 

  29. Sherbourne CD, Stewart AL (1991) The MOS social support survey. Soc Sci Med 32(6):705–714

    Article  CAS  PubMed  Google Scholar 

  30. Champion VL (1999) Revised susceptibility, benefits, and barriers scale for mammography screening. Res Nurs health 22(4):341–348

    Article  CAS  PubMed  Google Scholar 

  31. Misovich SJ et al (2003) Predicting breast Self-Examination: a test of the information‐motivation‐behavioral skills model. J Appl Soc Psychol 33(4):775–790

    Article  Google Scholar 

  32. Stoll CR et al (2015) Barriers to mammography among inadequately screened women. Health Educ Behav 42(1):8–15

    Article  PubMed  Google Scholar 

  33. Madadi M et al (2014) Analyzing factors associated with women’s attitudes and behaviors toward screening mammography using design-based logistic regression. Breast Cancer Res Treat 144(1):193–204

    Article  PubMed  Google Scholar 

  34. Ritchie D, Van Hal G, Van den Broucke S (2022) Factors affecting intention to screen after being informed of benefits and harms of breast cancer screening: a study in 5 european countries in 2021. Archives of Public Health 80(1):1–12

    Article  Google Scholar 

  35. Allen JD, Stoddard AM, Sorensen G (2008) Do social network characteristics predict mammography screening practices? Health Educ Behav 35(6):763–776

    Article  PubMed  Google Scholar 

  36. Vries Hd, Kremers SP, Lippke S (2018) Health education and health promotion: key concepts and exemplary evidence to support them, in principles and concepts of behavioral medicine. Springer, pp 489–532

  37. Rebbeck TR et al (2018) Precision prevention and early detection of cancer: fundamental principles. 8(7):803–811

  38. Pan I-W, Oeffinger KC, Shih Y-CT (2022) Cost-sharing and out-of-pocket cost for women who received MRI for breast cancer screening. JNCI: J Natl Cancer Inst 114(2):254–262

    Article  PubMed  Google Scholar 

  39. Smalls BL et al (2018) Social support and breast cancer screening in rural A ppalachia. Psycho-oncology 27(9):2281–2288

    Article  PubMed  PubMed Central  Google Scholar 

  40. Topolovec-Vranic J, Natarajan K (2016) The use of social media in recruitment for medical research studies: a scoping review. J Med Internet Res 18(11):e5698

    Article  Google Scholar 

  41. Walker MJ et al (2013) Accuracy of self-reported screening mammography Use: examining recall among female relatives from the Ontario site of the breast cancer family registry International Scholarly Research Notices, 2013

  42. Larouche G et al (2012) Self-reported mammography use following BRCA1/2 genetic testing may be overestimated. Fam Cancer 11(1):27–32

    Article  CAS  PubMed  Google Scholar 

  43. Terry MB et al (2019) 10-year performance of four models of breast cancer risk: a validation study. Lancet Oncol 20(4):504–517

    Article  PubMed  Google Scholar 

  44. Taplin SH et al (2012) Introduction: understanding and influencing multilevel factors across the cancer care continuum. J Natl Cancer Inst Monogr 2012(44):2–10

    Article  PubMed  PubMed Central  Google Scholar 

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Funding

This work was supported by a grant from the Breast Cancer Research Foundation (ASPO-19-002, PI: Conley). The content presented here is solely the responsibility of the authors and does not represent the official views of the Breast Cancer Research Foundation.

Author information

Authors and Affiliations

  1. Department of Oncology, Georgetown University, Washington, DC, USA

    Claire C. Conley, Jennifer D. Rodriguez & Suzanne C. O’Neill

  2. Moffitt Cancer Center, Health Outcomes and Behavior Program, Tampa, FL, USA

    McKenzie McIntyre & Susan T. Vadaparampil

  3. Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA

    Naomi C. Brownstein

  4. Department of Diagnostic Imaging and Interventional Radiology, Moffitt Cancer Center, Tampa, FL, USA

    Bethany L. Niell

  5. Cancer Prevention and Control Program, Georgetown Lombardi Comprehensive Cancer Center, 2115 Wisconsin Ave NW, Suite 300, 20007, Washington, DC, USA

    Claire C. Conley

Authors
  1. Claire C. Conley
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  6. Suzanne C. O’Neill
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  7. Susan T. Vadaparampil
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Contributions

CCC: Conceptualization, funding acquisition, formal analysis, visualization, interpretation, writing–original draft. JDR: Investigation, data curation, project administration, writing–review and editing. MM: Investigation, data curation, project administration, writing–review and editing. NCB: Data curation, formal analysis, methodology, writing–review and editing. BLN: Conceptualization, resources, supervision, writing–review and editing. SCO: Conceptualization, supervision, writing–review and editing. STC: Conceptualization, funding acquisition, resources, supervision, writing–review and editing.

Corresponding author

Correspondence to Claire C. Conley.

Ethics declarations

Ethics approval

Study procedures were reviewed by the Advarra Institutional Review Board (Protocol #00000971) and determined exempt from IRB oversight due to minimal risk.

Consent to participate

The Advarra Institutional Review Board provided a waiver of informed consent for this study (Protocol #00000971) due to minimal risk.

Competing interests

Drs. Conley and O’Neill have received research funding from Pfizer. No other authors have conflicts of interest to disclose.

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Conley, C.C., Rodriguez, J.D., McIntyre, M. et al. Self-reported barriers to screening breast MRI among women at high risk for breast cancer. Breast Cancer Res Treat 202, 345–355 (2023). https://doi.org/10.1007/s10549-023-07085-w

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  • DOI: https://doi.org/10.1007/s10549-023-07085-w

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