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评估盖尔模型:乳腺癌风险评估中的种族差异

Melissa Rangel1, Shirlene Paul1, Dipti Gupta1

  • 1Rush University Medical Center, Chicago, IL, USA.

Annals of surgical oncology
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概括
此摘要是机器生成的。

盖尔模型低估了黑人女性的乳腺癌风险. 尽管诊断率相似,但与白人女性相比,黑人女性不太可能被该模型归类为高风险 (HR).

关键词:
不平等性 不平等性盖尔 模型 模型 盖尔种族 种族 种族 种族风险计算器风险计算器

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科学领域:

  • 医疗信息学医学信息学
  • 公共卫生 公共卫生
  • 流行病学 流行病学

背景情况:

  • 盖尔模型是一种乳腺癌风险评估工具,最初是基于主要来自白人女性的数据开发的.
  • 尽管对不同人群进行了重新校准,但仍然存在对低估某些种族群体乳腺癌风险的担忧.

研究的目的:

  • 评估盖尔模型在不同种族群体的乳腺癌风险分类方面的表现.
  • 在高风险 (HR) 分类中识别潜在的种族差异.

主要方法:

  • 一项回顾性研究分析了31256名年龄在25-75岁的女性的电子医疗记录,这些女性接受了乳房造影.
  • 该队列包括各种种族群体:11589名黑人/非洲裔美国人,11008名白人,5872名西班牙裔/拉丁裔,1429名亚裔和1358名其他种族群体.

主要成果:

  • 在种族群体之间观察到高风险 (HR) 分类的显著差异.
  • 白人女性的人力资源分类率最高 (11.4%).
  • 与白人女性相比,黑人女性在HR分类的几率比率 (OR = 0.23) 显著较低,即使在对其他变量进行控制后也是如此. 黑人 (1.57%) 和白人 (1.6%) 妇女的乳腺癌诊断率相似.

结论:

  • 盖尔模型证明了高风险分类中的种族差异.
  • 黑人女性不太可能被确定为高风险女性,尽管癌症发病率与白人女性相比较.
  • 这突显了风险评估算法中基于种族的变量的潜在限制.