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Brentnall AR, Cohn WF, Knaus WA, et al. A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model. J Breast Imaging. 2019;1(2):99-106doi: 10.1093/jbi/wbz006.
Brentnall, A. R., Cohn, W. F., Knaus, W. A., Yaffe, M. J., Cuzick, J., & Harvey, J. A. (2019). A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model. Journal of breast imaging, 1(2), 99-106. https://doi.org/10.1093/jbi/wbz006
Brentnall, Adam R, et al. "A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model." Journal of breast imaging vol. 1,2 (2019): 99-106. doi: https://doi.org/10.1093/jbi/wbz006
Brentnall AR, Cohn WF, Knaus WA, Yaffe MJ, Cuzick J, Harvey JA. A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model. J Breast Imaging. 2019 Jun;1(2):99-106. doi: 10.1093/jbi/wbz006. Epub 2019 May 11. PMID: 31423486; PMCID: PMC6690422.
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J Breast Imaging. 2019 Jun;1(2):99-106. doi: 10.1093/jbi/wbz006. Epub 2019 May 11.

A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model.

Journal of breast imaging

Adam R Brentnall, Wendy F Cohn, William A Knaus, Martin J Yaffe, Jack Cuzick, Jennifer A Harvey

Affiliations

  1. Queen Mary University of London, Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts and The London School of Medicine and Dentistry, London, UK.
  2. University of Virginia, Public Health Sciences, University of Virginia Health Sciences Center, Charlottesville, VA.
  3. NantHealth, Inc., Culver City, CA, and University of Virginia, Public Health Sciences, University of Virginia Health Sciences Center, Charlottesville, VA.
  4. Sunnybrook Health Sciences Center, Medical Biophysics, Sunnybrook Research Institute, Toronto, Ontario, Canada.
  5. University of Virginia, Department of Radiology and Medical Imaging, University of Virginia Health Sciences Center, Charlottesville, VA.

PMID: 31423486 PMCID: PMC6690422 DOI: 10.1093/jbi/wbz006

Abstract

BACKGROUND: Accurate breast cancer risk assessment for women attending routine screening is needed to guide screening and preventive interventions. We evaluated the accuracy of risk predictions from both visual and volumetric mammographic density combined with the Tyrer-Cuzick breast cancer risk model.

METHODS: A case-control study (474 patient participants and 2243 healthy control participants) of women aged 40-79 years was performed using self-reported classical risk factors. Breast density was measured by using automated volumetric software and Breast Imaging and Reporting Data System (BI-RADS) density categories. Odds ratios (95% CI) were estimated by using logistic regression, adjusted for age, demographic factors, and 10-year risk from the Tyrer-Cuzick model, for a change from the 25

RESULTS: After adjustment for classical risk factors in the Tyrer-Cuzick model, age, and body mass index (BMI), BI-RADS density had an IQ-OR of 1.55 (95% CI = 1.33 to 1.80) compared with 1.40 (95% CI = 1.21 to 1.60) for volumetric percent density. Fibroglandular volume (IQ-OR = 1.28, 95% CI = 1.12 to 1.47) was a weaker predictor than was BI-RADS density (P

CONCLUSION: The addition of volumetric and visual mammographic density measures to classical risk factors improves risk stratification. A combined risk could be used to guide precision medicine, through risk-adapted screening and prevention strategies.

Keywords: breast cancer risk models; breast density; breast neoplasms; early detection of cancer; risk factors

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