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Risk Models for Breast Cancer and Their Validation
Adam R Brentnall1, Jack Cuzick1
1Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, Charterhouse square, London, EC1M 6BQ.
Statistical Science : a Review Journal of the Institute of Mathematical Statistics
|April 1, 2020
Summary
Accurate breast cancer risk assessment is crucial for early detection and prevention. This study updates the IBIS (Tyrer-Cuzick) model and methods for assessing its calibration, improving personalized cancer risk evaluation.
Area of Science:
- Oncology
- Biostatistics
- Epidemiology
Background:
- Rising cancer incidence necessitates improved prevention and early diagnosis strategies.
- Risk assessment models are vital for identifying individuals requiring targeted cancer interventions.
- Comprehensive breast cancer risk models are challenging due to limited data on joint risk factor effects.
Purpose of the Study:
- To review and update the IBIS (Tyrer-Cuzick) breast cancer risk prediction model.
- To develop and assess methods for model calibration, accounting for competing mortality.
- To demonstrate the model and calibration methods using a large mammography screening cohort.
Main Methods:
- Review of the IBIS (Tyrer-Cuzick) model development and recent updates.
- Development and application of calibration assessment techniques for long-term risk prediction.
- Utilizing a cohort of 132,139 women from mammography screening in Washington State, USA.
Main Results:
- The study presents an updated IBIS (Tyrer-Cuzick) breast cancer risk model.
- Novel methods for assessing model calibration, crucial for reliable risk estimates, are reviewed and developed.
- The model and calibration techniques are validated on a substantial dataset of women undergoing mammography screening.
Conclusions:
- The updated IBIS (Tyrer-Cuzick) model offers enhanced precision for breast cancer risk assessment.
- Robust calibration methods are essential for ensuring the accuracy of long-term cancer risk predictions.
- This work supports improved targeted screening and prevention strategies for breast cancer.
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