Unknown

Dataset Information

0

Simplified Breast Risk Tool Integrating Questionnaire Risk Factors, Mammographic Density, and Polygenic Risk Score: Development and Validation.


ABSTRACT:

Background

Clinical use of breast cancer risk prediction requires simplified models. We evaluate a simplified version of the validated Rosner-Colditz model and add percent mammographic density (MD) and polygenic risk score (PRS), to assess performance from ages 45-74. We validate using the Mayo Mammography Health Study (MMHS).

Methods

We derived the model in the Nurses' Health Study (NHS) based on: MD, 77 SNP PRS and a questionnaire score (QS; lifestyle and reproductive factors). A total of 2,799 invasive breast cancer cases were diagnosed from 1990-2000. MD (using Cumulus software) and PRS were assessed in a nested case-control study. We assess model performance using this case-control dataset and evaluate 10-year absolute breast cancer risk. The prospective MMHS validation dataset includes 21.8% of women age <50, and 434 incident cases identified over 10 years of follow-up.

Results

In the NHS, MD has the highest odds ratio (OR) for 10-year risk prediction: ORper SD = 1.48 [95% confidence interval (CI): 1.31-1.68], followed by PRS, ORper SD = 1.37 (95% CI: 1.21-1.55) and QS, ORper SD = 1.25 (95% CI: 1.11-1.41). In MMHS, the AUC adjusted for age + MD + QS 0.650; for age + MD + QS + PRS 0.687, and the NRI was 6% in cases and 16% in controls.

Conclusion

A simplified assessment of QS, MD, and PRS performs consistently to discriminate those at high 10-year breast cancer risk.

Impact

This simplified model provides accurate estimation of 10-year risk of invasive breast cancer that can be used in a clinical setting to identify women who may benefit from chemopreventive intervention.See related commentary by Tehranifar et al., p. 587.

SUBMITTER: Rosner B 

PROVIDER: S-EPMC8026588 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC7590110 | biostudies-literature
| S-EPMC6190790 | biostudies-other
| S-EPMC3680940 | biostudies-literature
| S-EPMC4107377 | biostudies-literature
| S-EPMC4410663 | biostudies-literature
| S-EPMC5581885 | biostudies-other