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An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
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标志着左截止的竞争风险数据的地标
Theresa Unseld1, Tobias Bluhmki2, Jan Beyersmann2
1Institute of Medical Biometry and Epidemiology, Ulm University, Helmholtzstraße 22, Ulm, Germany.
Biometrical journal. Biometrische Zeitschrift
|October 29, 2024
概括
路标提供了在怀孕期间药物安全性的动态预测,比较了诸如自发性流产 (SAB) 等不良结果的风险与诺基诺暴露. 虽然地标显示了一些效应减弱,但结果与以前的发现一致.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 药物监督 药物监督 药物监督
背景情况:
- 在怀孕期间评估药物安全性需要对不良结果进行准确的动态预测.
- 复杂的多状态模型可能对实时风险评估具有挑战性.
研究的目的:
- 开发和评估用于分析与怀孕药物安全性竞争风险的左截断数据的标志性方法.
- 用模拟和现实世界的数据,将地标预测与传统方法进行比较.
主要方法:
- 将标志技术应用于德国胚胎毒素药监督研究所的队列研究.
- 模拟研究比较地标,非参数多态模型和考克斯回归.
- 对自发堕胎 (SAB) 和选择性终止怀孕的累积发病率的分析.
主要成果:
- 标志性估计显示了一些减弱,但仍然接近多州模型估计.
- 在怀孕早期暴露于化诺可能会增加选择性终止妊娠的累积发病率.
- 没有显著增加自发流产 (SAB) 风险或累积发病率被观察到在诺基诺暴露的妇女.
结论:
- 里程碑是复杂场景中的动态预测的可行替代方案,如怀孕药物安全性.
- 这些发现支持了先前的分析,表明在第一季度暴露在化类中,SAB风险没有增加.
- 诺基诺暴露与选择性终止怀孕之间的潜在联系需要进一步调查.
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