适应BOADICEA乳腺癌和卵巢癌风险模型,以适应英国种族多样化的人口
Lorenzo Ficorella1, Xin Yang2, Nasim Mavaddat2
1Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. lf364@medschl.cam.ac.uk.
British journal of cancer
|July 17, 2025
概括
更新后的BOADICEA算法现在为英国不同人口提供了特定种族的乳腺和卵巢癌风险预测. 这提高了非白人妇女的癌症风险评估,可能改善医疗保健公平.
科学领域:
- 基因组学和流行病学
- 癌症风险预测建模模型
- 健康差距 研究 研究 研究 研究
背景情况:
- 乳腺和卵巢癌风险预测工具BOADICEA算法主要是使用白人/欧洲人的数据开发的.
- 这种种族偏见限制了现有的风险预测模型对不同人群的准确性和适用性.
- 有关种族特异性风险估计的必要性至关重要,以确保公平的癌症风险评估.
研究的目的:
- 更新BOADICEA算法,将主要英国族群的种族特异性风险因素和人口癌症发病率纳入其中.
- 开发用于计算混合遗传祖先个体的调整多基因分数的方法.
- 为英国非白人妇女提供更准确的乳腺和卵巢癌风险预测.
主要方法:
- 利用多种数据来源,估计了英国的白人,黑人,南亚人,东亚人和混合族群的风险因素分布和影响大小.
- 纳入特定种族的人口癌症发病率数据.
- 开发了一种新的方法来获得混合遗传祖先的个体调整的多基因分数.
主要成果:
- 与白人相比,所有非白人族群的乳腺癌和卵巢癌预测的平均绝对风险在所有非白人族群中都较低.
- 发现非白人族群的风险分布较窄.
- 根据当前的国家指导方针,显著较少的非白人女性被归类为中度或高风险.
结论:
- 通过CanRisk工具访问的更新的BOADICEA算法为英国的非白人妇女提供了更合适的风险估计.
- 目前的风险分类准则可能需要修订,以更好地反映非白人妇女的风险概况.
- 需要进一步的前性研究来验证模型在不同人群中的表现.
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