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开发和验证动态的5年乳腺癌风险模型,使用重复的乳腺扫描
Shu Jiang1, Debbie L Bennett2, Bernard A Rosner3
1Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine in St Louis, St Louis, MO.
JCO clinical cancer informatics
|December 5, 2024
概括
将先前的乳房X光片纳入动态模型显著改善了5年乳腺癌风险预测. 这种方法识别了针对性干预的高风险女性,优于静态模型.
科学领域:
- 放射学 放射学是一门学科.
- 在瘤学瘤学.
- 生物统计学 生物统计学
背景情况:
- 目前的乳腺癌风险预测模型通常不充分利用历史查乳房扫描数据.
- 动态预测模型,利用串行成像,尚未广泛探索临床应用.
研究的目的:
- 开发和验证基于乳房镜的动态模型,用于预测5年乳腺癌风险.
- 与静态模型相比,评估动态风险预测的性能改进.
主要方法:
- 分析了10 099名女性的前性队列,使用反复查乳房图训练了一个动态模型.
- 该模型预测了5年的乳腺癌风险,其性能得到了外部验证.
- 用曲线下的面积 (AUC) 评估歧视,并根据美国SEER数据进行校准.
主要成果:
- 动态模型的5年AUC为0.80,比静态模型的AUC0.74.4显著改善.
- 通过动态模型识别的高风险女性 (5%以上的5年风险) 占所有乳腺癌的61%.
- 该模型显示了跨种族群体的可比性表现,包括黑人和白人女性.
结论:
- 使用先前的查乳房造影可以提高5年乳腺癌风险预测的准确性.
- 动态模型可以有效地识别那些可能受益于加强查或风险管理策略的妇女.
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