OA Epidemiology

Breast Cancer Risk Prediction Model: A Nomogram Based on Common Mammographic Screening Findings

Proceedings of the 2013 annual meeting of the Netherlands Epidemiology Society

Volume 1 Issue S1 Abstract 43

 

J.M.H. Timmers, National Centre for Breast Cancer Screening/Radboud University Medical Centre, Nijmegen, the Netherlands
A.L.M. Verbeek, National Centre for Breast Cancer Screening/Radboud University Medical Centre, Nijmegen, the Netherlands
J. IntHout, Radboud University Medical Centre, Nijmegen, the Netherlands
R.M. Pijnappel, National Centre for Breast Cancer Screening, Nijmegen; UMC Utrecht, the Netherlands
M.J.M. Broeders, National Centre for Breast Cancer Screening/Radboud University Medical Centre, Nijmegen, the Netherlands
G.J. den Heeten, National Centre for Breast Cancer Screening, Nijmegen; AMC UvA, Amsterdam

Background
We set out to develop a prediction model for breast cancer based on common mammographic findings on screening mammograms aiming to reduce reader variability in assigning BI-RADS.

Methods
We retrospectively reviewed 352 positive screening mammograms of women participating in the Dutch screening programme (Nijmegen region, 2006–2008). The following mammographic findings were assessed by consensus reading of three expert radiologists: masses and mass density, calcifications, architectural distortion, focal asymmetry and mammographic density, and BI-RADS. Data on age, diagnostic work-up and final diagnosis were collected from patient records. Multivariate logistic regression analyses were used to build a breast cancer prediction model, presented as a nomogram.

Results
Breast cancer was diagnosed in 108 cases (31%). The highest positive predictive value (PPV) was found for spiculated masses (96%) and the lowest for well-defined masses (10%). Characteristics included in the nomogram are age, mass, calcifications, architectural distortion and focal asymmetry.

Conclusion
With our nomogram we developed a tool assisting screening radiologists in determining the chance of malignancy based on mammographic findings. We propose cut-off values for assigning BI-RADS in the Dutch programme based on our nomogram which will need to be validated in future research. These values can easily be adapted for use in other screening programmes.

Published: 06 Jun, 2013

 
Licensee OA Publishing London 2013. Creative Commons Attribution License (CC-BY)