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基于传统风险因素和循环代谢物的新型2型糖尿病预测评分:在两个大型队列研究中推导和验证模型
Ruijie Xie1,2, Christian Herder3,4,5, Sha Sha1,2
1Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Im Neuenheimer Feld 581, Heidelberg, 69120, Germany.
EClinicalMedicine
|December 25, 2024
概括
添加11或4个代谢生物标志物显著改善了超出临床剑桥糖尿病风险评分 (CDRS) 的2型糖尿病风险预测. 这些新型模型,包括英国生物库糖尿病风险评分 (UKB-DRS),显示出常规临床使用的潜力.
科学领域:
- 生物化学 生物化学
- 代谢学 代谢学 代谢学
- 流行病学 流行病学
背景情况:
- 2型糖尿病风险评估依赖于像剑桥糖尿病风险评分 (CDRS) 这样的临床评分.
- 代谢生物标志物对2型糖尿病风险的增量预测值尚未完全确定.
- 新的生物标志物可以增强目前的风险预测模型.
研究的目的:
- 评估代谢生物标志物对CDRS10年2型糖尿病风险的附加预测价值.
- 开发和验证一个新的糖尿病风险预测模型,包括代谢数据.
- 评估代谢生物标志物在糖尿病风险分层中的临床实用性.
主要方法:
- 利用英国生物库 (86,232名参与者) 进行模型推导和内部验证.
- 包括德国ESTHER队列 (4383名参与者) 进行外部验证.
- 量化了249种NMR衍生代谢物,使用LASSO回归选择了11种生物标志物,并通过C指数和NRI评估了模型性能.
主要成果:
- 添加11个代谢生物标志物显著改善了内部验证 (0.815到0.834) 和外部验证 (0.770到0.798) 中的C指数.
- 连续净重新分类指数 (NRI) 在两个队列 (39.8%内部,33.8%外部) 中均显著改善.
- 使用4种代谢物的简洁模型显示了可比的预测性能.
结论:
- 新的英国生物库糖尿病风险评分 (UKB-DRS),包括11或4种代谢物,显著超过临床CDRS.
- UKB-DRS需要最小的临床信息和血液样本,使其适用于广泛使用.
- 高通量NMR代谢学为例行糖尿病风险评估提供了一种具有成本效益的方法.
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