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Advanced Breast Imaging Availability by Screening Facility Characteristics

Rationale and Objectives

To determine the relationship between screening mammography facility characteristics and on-site availability of advanced breast imaging services required for supplemental screening and the diagnostic evaluation of abnormal screening findings.

Materials and Methods

We analyzed data from all active imaging facilities across six regional registries of the National Cancer Institute–funded Breast Cancer Surveillance Consortium offering screening mammography in calendar years 2011–2012 ( n = 105). We used generalized estimating equations regression models to identify associations between facility characteristics (eg, academic affiliation, practice type) and availability of on-site advanced breast imaging (eg, ultrasound [US], magnetic resonance imaging [MRI]) and image-guided biopsy services.

Results

Breast MRI was not available at any nonradiology or breast imaging–only facilities. A combination of breast US, breast MRI, and imaging-guided breast biopsy services was available at 76.0% of multispecialty breast centers compared to 22.2% of full diagnostic radiology practices ( P = .0047) and 75.0% of facilities with academic affiliations compared to 29.0% of those without academic affiliations ( P = .04). Both supplemental screening breast US and screening breast MRI were available at 28.0% of multispecialty breast centers compared to 4.7% of full diagnostic radiology practices ( P < .01) and 25.0% of academic facilities compared to 8.5% of nonacademic facilities ( P = .02).

Conclusions

Screening facility characteristics are strongly associated with the availability of on-site advanced breast imaging and image-guided biopsy service. Therefore, the type of imaging facility a woman attends for screening may have important implications on her timely access to supplemental screening and diagnostic breast imaging services.

Inherent health system attributes, such as place of service, strongly influence both access to and quality of health care in the United States . For women undergoing routine breast cancer screening in the United States, both access to and quality of breast imaging services vary widely . For women with an abnormal screening result, timely and complete diagnostic imaging evaluation is a critical, intermediate step between screen-detected malignancy and definitive treatment . Appropriate diagnostic breast imaging frequently requires modalities beyond mammography, including diagnostic breast ultrasound (US), image-guided breast biopsy, and breast magnetic resonance imaging (MRI; eg, for extent of disease and surgical planning) . Patient access to and ready availability of these advanced breast imaging modalities, therefore, may play an important role in preventing delays in diagnostic evaluation and, potentially, worse patient outcomes .

Over the last decade, technologic advances in breast imaging modalities, including higher resolution breast US and breast MRI, along with expansion of their clinical indications, have caused the rapid diffusion of these technologies into community practices . However, the diffusion and adoption of these advanced imaging modalities may not occur based on patient need, including high lifetime breast cancer risk . Moreover, the demand for more advanced breast imaging is likely to increase with new breast density reporting laws enacted by states across the United States . These laws mandate that imaging facilities inform women with mammographically dense breasts that they are at increased risk of developing cancer and some also require notification that they may benefit from supplemental screening . For women at increased risk of developing cancer, both screening breast US and screening MRI have been found to increase cancer detection beyond mammography alone, and annual screening breast MRI is a cost-effective measure among women at very high breast cancer risk . Utilization of breast MRI is also increasing among women with a personal history of breast cancer for routine surveillance .

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Materials and methods

Study Population

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Data Collection

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Statistical Analysis

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Results

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Table 1

Characteristics of Breast Imaging Facilities Participating in the BCSC

Facility Characteristic_N_ = 105 Profit/not for profit status, n (%) For profit 23 (27.1) Not for profit 62 (72.9) Unknown ∗ 20 Academic medical center status, n (%) Yes 8 (7.6) No 97 (92.4) Facility type, n (%) Multispecialty breast center 25 (23.8) Full diagnostic radiology practice 66 (62.9) Breast imaging only 4 (3.8) Nonradiology practice 10 (9.5)

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Table 2

Availability of Advanced Breast Imaging by BCSC Facility Characteristic

Facility Characteristic_N_ Any Ultrasound Screening Ultrasound Any MRI Screening MRI Number of facilities providing nonmissing data on use of this technology ( N ) 104 104 103 103 Profit/not-for-profit status For profit 23 20 (87.0%; 55.5–97.3) 4 (17.4%; 8.5–32.3) 11 (47.8%; 29.2–67.0) 5 (21.7%; 7.5–48.9) Not for profit 61 47 (77.0%; 59.1–88.6) 14 (23.0%; 15.8–32.0) 24 (40.0%; 24.0–58.4) 15 (25.0%; 8.9–53.2) Unknown 20 16 (80.0%; 49.9–94.1) 6 (30.0%; 15.0–51.0) 9 (45.0%; 25.0–66.7) 6 (30.0%; 13.8–53.4)P value .25 .47 .63 .87 Academic medical center status Yes 8 6 (75.0%; 31.7–95.1) 3 (37.5%; 14.1–68.6) 6 (75.0%; 31.6–95.1) 4 (50.0%; 19.8–80.2) No 96 77 (80.2%; 62.5–90.8) 21 (21.9%; 16.0–29.1) 38 (40%; 29.2–51.9) 22 (23.2%; 13.6–36.7)P value .79 .27 .13 .064 Facility type Multispecialty breast center 25 25/25 (100%) 9 (36.0%; 19.9–56.0) 19 (76.0%; 45.9–92.2) 14 (56%; 24.8–83.1) Full diagnostic radiology practice 66 54 (81.8%; 65.6–91.4) 15 (22.7%; 15.7–31.6) 25 (39.1%; 26.3–53.5) 12 (18.8%; 9.9–32.6) Breast imaging only 4 2 (50.0%; 12.1–87.9) 0/4 (0%) 0/4 (0%) 0/4 (0%) Nonradiology practice 9 2 (22.2%; 10.6–40.7) 0/9 (0%) 0/10 (0%) 0/10 (0%)P value † <.0001 .19 .024 .020

GEE, generalized estimating equations; MRI, magnetic resonance imaging.

Results shown here are the number of facilities which reported providing the imaging service in question (columns) within each category of the facility characteristic (row). Percentages are based on observed frequencies divided by the denominators shown in the column marked “ N ”, except for the following columns: denominator is 60 for “not-for-profit” facilities offering any ultrasound and screening ultrasound; denominator is 95 for nonacademic medical centers offering any ultrasound and screening ultrasound; and denominator is 66 for full diagnostic radiology practices offering any ultrasound and screening ultrasound.

The 95% confidence intervals are derived via delta method from postestimation predicted probability estimates obtained from unadjusted GEE models of the outcome regressed on the corresponding facility characteristic. Models accommodate the nonindependence of facilities belonging to the same practice.

All P values are from joint Wald tests of parameters estimated by GEE modeling for each descriptive variable.

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Table 3

Availability of Imaging-Guided Biopsy Services by BCSC Facility Characteristic

Facility Characteristic_N_ Any Guided Biopsy Services Stereotactic-Guided Biopsy Ultrasound-Guided Biopsy MRI-Guided Biopsy Number of facilities providing nonmissing data on use of this technology ( N ) 104 104 104 104 Profit/not-for-profit status For profit 22 7 (31.8%; 13.6–58.1) 5 (22.7%; 7.7–50.9) 7 (31.8%; 13.6–58.1) 3 (13.6%; 3.3–42.1) Not for profit 62 40 (64.5%; 47.7–78.4) 32 (51.6%; 35.1–67.8) 39 (62.9%; 48.6–75.3) 20 (32.3%; 21.7–44.9) Unknown 20 15 (75.0%; 48.3–90.6) 9 (45.0%; 25.0–66.7) 15 (75.0%; 48.3–90.6) 6 (30.0%; 11.2–59.3)P value .028 .076 .030 .23 Academic medical center status Yes 8 6 (75.0%; 31.7–95.1) 6 (75.0%; 31.7–95.1) 6 (75.0%; 31.7–95.1) 6 (75.0%; 31.7–95.1) No 96 56 (58.3%; 44.2–71.2) 40 (41.7%; 29.3–55.2) 55 (57.3%; 44.4–69.3) 23 (24.0%; 17.1–32.5)P value .45 .14 .42 .019 Facility type Multispecialty breast center 25 24 (96.0%; 75.7–99.5) 23 (92.0%; 70.9–98.2) 24 (96.0%; 75.7–99.5) 17 (68.0%; 36.9–88.5) Full diagnostic radiology practice 65 38 (58.5%; 39.5–75.2) 23 (35.4%; 17.4–58.8) 37 (56.9%; 40.1–72.3) 12 (18.5%; 10.8–29.7) Breast imaging only 4 0/4 (0%) 0/4 (0%) 0/4 (0%) 0/4 (0%) Nonradiology practice 10 0/10 (0%) 0/10 (0%) 0/10 (0%) 0/10 (0%)P value † .011 .0012 .0089 .0063

GEE, generalized estimating equations; MRI, magnetic resonance imaging.

Results reflect the number of facilities which reported providing the imaging service in question (columns) within each category of the facility characteristic (row). Percentages are based on observed frequencies divided by the denominators shown in the column marked “ N ”. The 95% confidence intervals are derived via delta method from postestimation predicted probability estimates obtained from unadjusted GEE models of the outcome regressed on the corresponding facility characteristic. Models accommodate the nonindependence of facilities belonging to the same practice.

All P values are from joint Wald tests of parameters estimated by GEE modeling for each descriptive variable.

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Table 4

Availability of a Combination of Imaging and Imaging-Guided Biopsy Services by BCSC Facility Characteristic

Facility Characteristic_N_ Both Any Ultrasound and Any MRI Both Screening Ultrasound and Screening MRI Any Ultrasound and Any MRI and Guided Biopsy Services Number of facilities providing nonmissing data on use of this technology ( N ) 102 102 101 Profit/not-for-profit status For profit 23 11 (47.8%; 29.2–67.1) 2 (8.7%; 1.8–32.7) 4 (18.2%; 5.5–46.1) Not for profit 59 22 (37.3%; 25.0–51.5) 6 (10.2%; 3.0–29.6) 20 (33.9%; 23.3–46.4) Unknown 20 9 (45.0%; 25.0–66.7) 2 (10.0%; 2.2–35.1) 9 (45.0%; 25.0–66.7)P value ∗ .46 .89 .32 Academic medical center status Yes 8 6 (75.0%; 31.6–95.1) 2 (25.0%; 8.2–55.6) 6 (75.0%; 31.6–95.1) No 94 36 (38.3%; 29.1–48.4) 8 (8.5%; 3.9–17.6) 27 (29.0%; 22.4–36.7)P value .11 .022 .041 Facility type Multispecialty breast center 25 19 (76.0%; 45.9–92.2) 7 (28.0%; 12.7–50.9) 19 (76.0%; 45.9–92.2) Full diagnostic radiology practice 64 23 (35.9%; 24.9–48.7) 3 (4.7%; 1.6–12.9) 14 (22.2%; 13.7–33.9) Breast imaging only 4 0/4 (0%) 0/4 (0%) 0/4 (0%) Nonradiology practice 9 0/9 (0%) 0/9 (0%) 0/9 (0%)P value † .023 .0009 .0047

GEE, generalized estimating equations; MRI, magnetic resonance imaging.

Results shown here are the number of facilities that reported providing the imaging service in question (columns) within each category of the facility characteristic (row). Percentages are based on observed frequencies divided by the denominators shown in the column marked “ N ”, except for the following columns: denominator is 22 for “for-profit” facilities offering both any ultrasound and any MRI; denominator is 93 for nonacademic medical centers offering both any ultrasound and any MRI; and denominator is 63 for full diagnostic radiology practices offering both any ultrasound and any MRI.

The 95% confidence intervals are derived via delta method from postestimation predicted probability estimates obtained from unadjusted GEE models of the outcome regressed on the corresponding facility characteristic. Models accommodate the nonindependence of facilities belonging to the same practice.

All P values are from joint Wald tests of parameters estimated by GEE modeling for each descriptive variable.

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Discussion

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Acknowledgments

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References

  • 1. Institute of Medicine: Unequal treatment: confronting racial and ethnic disparities in health care.2002.National Academy PressWashington, DC

  • 2. Onega T., Duell E.J., Shi X., et. al.: Race versus place of service in mortality among medicare beneficiaries with cancer. Cancer 2010; 116: pp. 2698-2706.

  • 3. Onega T., Duell E.J., Shi X., et. al.: Influence of NCI cancer center attendance on mortality in lung, breast, colorectal, and prostate cancer patients. Med Care Res Rev 2009; 66: pp. 542-560.

  • 4. Onega T., Duell E.J., Shi X., et. al.: Geographic access to cancer care in the U.S. Cancer 2008; 112: pp. 909-918.

  • 5. Sickles E.A., Miglioretti D.L., Ballard-Barbash R., et. al.: Performance benchmarks for diagnostic mammography. Radiology 2005; 235: pp. 775-790.

  • 6. Miglioretti D.L., Smith-Bindman R., Abraham L., et. al.: Radiologist characteristics associated with interpretive performance of diagnostic mammography. J Natl Cancer Inst 2007; 99: pp. 1854-1863.

  • 7. Jackson S.L., Taplin S.H., Sickles E.A., et. al.: Variability of interpretive accuracy among diagnostic mammography facilities. J Natl Cancer Inst 2009; 101: pp. 814-827.

  • 8. Elkin E.B., Atoria C.L., Leoce N., et. al.: Changes in the availability of screening mammography, 2000-2010. Cancer 2013; 119: pp. 3847-3853.

  • 9. Elkin E.B., Ishill N.M., Snow J.G., et. al.: Geographic access and the use of screening mammography. Med Care 2010; 48: pp. 349-356.

  • 10. Newman L.: IOM report sets policy priorities for improving breast cancer screening. J Natl Cancer Inst 2001; 93: pp. 574-575.

  • 11. Carney P.A., Abraham L.A., Miglioretti D.L., et. al.: Factors associated with imaging and procedural events used to detect breast cancer after screening mammography. AJR Am J Roentgenol 2007; 188: pp. 385-392.

  • 12. Hooley R.J., Andrejeva L., Scoutt L.M.: Breast cancer screening and problem solving using mammography, ultrasound, and magnetic resonance imaging. Ultrasound Q 2011; 27: pp. 23-47.

  • 13. Press R., Carrasquillo O., Sciacca R.R., et. al.: Racial/ethnic disparities in time to follow-up after an abnormal mammogram. J Womens Health (Larchmt) 2008; 17: pp. 923-930.

  • 14. Richards M.A., Westcombe A.M., Love S.B., et. al.: Influence of delay on survival in patients with breast cancer: a systematic review. Lancet 1999; 353: pp. 1119-1126.

  • 15. Stout N.K., Nekhlyudov L., Li L., et. al.: Rapid increase in breast magnetic resonance imaging use: trends from 2000 to 2011. JAMA Int Med 2014; 174: pp. 114-121.

  • 16. Wernli K.J., Demartini W.B., Ichikawa L., et. al.: Patterns of breast magnetic resonance imaging use in community practice. JAMA Int Med 2014; 174: pp. 125-132.

  • 17. Lee C.I., Bassett L.W., Lehman C.D.: Breast density legislation and opportunities for patient-centered outcomes research. Radiology 2012; 264: pp. 632-636.

  • 18. Dehkordy S.F., Carlos R.C.: Dense breast legislation in the United States: state of the states. J Am Coll Radiol 2013; 10: pp. 899-902.

  • 19. Berg W.A., Blume J.D., Cormack J.B., et. al.: Combined screening with ultrasound and mammography vs mammography alone in women at elevated risk of breast cancer. JAMA 2008; 299: pp. 2151-2163.

  • 20. Plevritis S.K., Kurian A.W., Sigal B.M., et. al.: Cost-effectiveness of screening BRCA1/2 mutation carriers with breast magnetic resonance imaging. JAMA 2006; 295: pp. 2374-2384.

  • 21. Ballard-Barbash R., Taplin S.H., Yankaskas B.C., et. al.: Breast Cancer Surveillance Consortium: a national mammography screening and outcomes database. AJR Am J Roentgenol 1997; 169: pp. 1001-1008.

  • 22. Diggle P., Heagerty P., Liang K., et. al.: Analysis of longitudinal data.2nd ed.2002.Oxford University PressOxford (UK)

  • 23. Rothman K.J.: No adjustments are needed for multiple comparisons. Epidemiology 1990; 1: pp. 43-46.

  • 24. Lu M.T., Tellis W.M., Fidelman N., et. al.: Reducing the rate of repeat imaging: import of outside images to PACS. AJR Am J Roentgenol 2012; 198: pp. 628-634.

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