咖啡因摄入量,身体活动和前列腺癌之间的探索,使用大规模NHANES调查的数据:一个横截面研究
1Department of Urology, Wuhan Fourth Hospital, Wuhan, China.
Medicine
|December 10, 2025
概括
高咖啡因摄入量和高体力活动 (PA) 与增加前列腺癌风险有关. 适度的PA可能会提供保护,而机器学习模型在预测癌症发生方面表现有前途.
科学领域:
- 在瘤学瘤学.
- 流行病学 流行病学
- 计算生物学 计算生物学
背景情况:
- 前列腺癌仍然是一个重大的全球健康问题.
- 了解咖啡因摄入量和体力活动 (PA) 等生活方式因素对于预防至关重要.
- 预测建模可以帮助早期检测和风险评估.
研究的目的:
- 为了研究咖啡因消费,PA水平和前列腺癌风险之间的关联.
- 开发和评估用于预测前列腺癌发生的机器学习模型.
- 为了确定前列腺癌的潜在可修改的风险因素.
主要方法:
- 从国家健康和营养检查调查 (2009-2018) 中对1789名受试者的分析.
- 使用多变量调整后勤回归来评估关联.
- 使用机器学习算法 (极端梯度提升,AdaBoost,Catboost,提升树) 进行预测建模.
主要成果:
- 大量的咖啡因摄入与前列腺癌的更高几率比率 (OR) 有关 (OR=1.25,95% CI:2.21-15.52).
- 高PA显示风险增加 (OR=1.68,95% CI:1.47-3.80),而中度PA显示相反的关联 (OR=0.66,95% CI:0.48-0.81).
- 机器学习模型,特别是极端梯度提升,Catboost和Boost树,实现了高预测精度 (AUC高达0.90).
结论:
- 大量的咖啡因摄入量和高的血压与前列腺癌的风险增加有关.
- 适度的PA可能对前列腺癌有保护作用.
- 机器学习模型显示出预测前列腺癌风险的巨大潜力.
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