体重调整腰部指数在BC流行率评估中的应用和预测值:使用NHANES数据进行全面的统计和机器学习分析
Wenjing Wang1, Biao Wu1, Jian Li1
1First Affiliated Hospital of Nanchang University, No.17 Yongwai Zhengjie, Nanchang, Jiangxi, China.
BMC cancer
|July 29, 2025
概括
在调整其他因素后,体重调整后的腰部指数 (WWI) 不是乳腺癌 (BC) 的重要独立预测指标. 然而,当与其他变量相结合时,WWI仍然可能对BC风险预测模型做出贡献.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 公共卫生 公共卫生
背景情况:
- 肥胖是已知的乳腺癌 (BC) 风险因素,但传统的指标,如BMI可能无法完全捕捉中心脂肪.
- 与BMI相比,体重调整的腰部指数 (WWI) 提供了更准确的腹部脂肪分布测量方法.
- 这项研究调查了第一次世界大战和美国人口中的BC流行之间的关联.
研究的目的:
- 评估体重调整的腰指数 (WWI) 与乳腺癌 (BC) 患病率之间的关联.
- 将第一次世界大战的预测性能与BC风险评估中的传统人体测量措施进行比较.
- 探索第一次世界大战在BC预测的多变量和机器学习模型中的实用性.
主要方法:
- 利用了来自2005-2018年国家健康和营养检查调查的10,760名女性 (年龄大于20岁) 的数据.
- 使用后勤回归来进行关联分析,并对多对线性进行差异膨胀因子诊断.
- 应用机器学习 (随机森林,LASSO) 用于使用ROC曲线和校准图表进行变量选择和模型评估.
主要成果:
- 未经调整的分析显示,第一次世界大战和西元前 (OR=1.56) 之间存在显著的关联.
- 在完全调整后,第一次世界大战和BC之间的关联不再具有统计学意义 (OR=0.98).
- 机器学习模型将第一次世界大战确定为顶级预测因素,随机森林保留了它,而LASSO排除了它. 包括第一次世界大战在内的模型显示出更好的预测性能 (AUCs ~0.79).
结论:
- 经过多变量调整后,第一次世界大战并不是BC的重要独立预测因素.
- 截面设计和有限的BC案例 (n=326) 需要谨慎的解释.
- 需要与更大的潜在队伍进行进一步的研究,以确认第一次世界大战在BC风险分层和独立预测者的作用.
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