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Adding Previous Screening Mammogram Images Improves Cancer Prediction

By Elana Gotkine HealthDay Reporter

Medically reviewed by Carmen Pope, BPharm. Last updated on Dec 9, 2024.

via HealthDay

MONDAY, Dec. 9, 2024 -- Five-year breast cancer (BC) risk prediction is improved with the addition of previous screening mammogram images beyond static models, according to a study published online Dec. 5 in JCO: Clinical Cancer Informatics.

Shu Jiang, Ph.D., from the Washington University School of Medicine in St. Louis, and colleagues analyzed a prospective cohort of 10,099 cancer-free women at entry (Nov. 3, 2008, through February 2012) from WashU. Participants were followed-up through 2020, and 478 pathology-confirmed BCs were identified. A dynamic model using repeated screening mammograms at WashU was trained to predict five-year risk. To assess discriminative performance, the model was applied to an external validation cohort (Emory), including 18,360 women screened from 2013 and followed through 2020, with 332 pathology-confirmed BCs.

The researchers found that a five-year area under the curve (AUC) of 0.80 was obtained in the external validation using three years of previous mammogram images. This represented a significant improvement over the AUC of 0.74 for the current visit mammogram, identified in the same women. Comparing high (>4 percent) to very low (<0.3 percent) five-year risk, a risk ratio of 21.1 was observed when calibrated. The dynamic model classified 16 percent of the cohort as high-risk, including 61 percent of women diagnosed with BC. Comparable performance was seen for the dynamic model in Black and White women.

"This dynamic model incorporates repeated mammograms for long-term risk prediction, showing that adding previous mammograms significantly improves five-year BC prediction," the authors write.

Several authors disclosed ties to the biotechnology and medical technology industries.

Abstract/Full Text

Disclaimer: Statistical data in medical articles provide general trends and do not pertain to individuals. Individual factors can vary greatly. Always seek personalized medical advice for individual healthcare decisions.

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