A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model. Issue 2 (11th May 2019)

• Record Type: Journal Article
• Authors: Brentnall, Adam R; Cohn, Wendy F; Knaus, William A; Yaffe, Martin J; Cuzick, Jack; Harvey, Jennifer A
• Is Part Of: Journal of breast imaging. Volume 1:Issue 2(2019)
• Page Start: 99
• Page End: 106
• Publication Date: 2019-05-11
• Subjects: breast cancer risk models -- breast neoplasms -- breast density -- early detection of cancer -- risk factors; Breast -- Imaging -- Periodicals; Breast -- Cancer -- Diagnosis -- Periodicals; 616.994490
• DOI: 10.1093/jbi/wbz006
• Languages: English
• ISSNs: 2631-6110

Abstract

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 th to 75 th percentile of the adjusted percent density distribution in control participants (IQ-OR). 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 (Pdiff = 0.014) or volumetric percent density (Pdiff = 0.065). In this setting, 4.8% of women were at high risk (8% + 10-year risk), using the Tyrer-Cuzick model without density, and 7.1% (BI-RADS) compared with 6.8% (volumetric) when combined with density. 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.