Bayesian Survival Analysis With Nonproportional Hazards
非比例风险下的贝叶斯生存分析AI 解读 ↓
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分类依据与纠错
AI 根据所提供的论文材料归类：摘要直接比较联合与单药治疗效果，并明确指出阿司匹林分配非随机，涉及治疗效应的因果解释。
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非比例风险下的贝叶斯生存分析
- 研究问题
- 普伐他汀与阿司匹林联合使用是否至少与单药同样有效，以及联合效果是否超过两种单药效果之和？
- 方法与思路
- 作者以五项随机临床试验建立三个贝叶斯分层生存模型，调整已知协变量，其中两个采用比例风险、一个不采用。
- 材料陈述的贡献
- 摘要说明以心肌梗死发生时间为重点，计算联合治疗不劣于单药及具有协同作用的概率，但未报告概率数值。
- 阅读关注点
- 应核对阿司匹林非随机使用的处理方式、风险模型与先验，以及联合效果和协同作用分别在哪种尺度上定义。
- 阅读边界
- 仅据版本未明的 OpenAlex 索引摘要；阿司匹林使用未随机化，协变量调整是否足以支持因果解释及具体效应均未说明。
原文摘要
Both pravastatin and aspirin are approved by the U.S. Food and Drug Administration (FDA) for secondary prevention of cardiovascular events. This article describes statistical analyses used for a successful submission to the FDA that contends that copackaging pravastatin and aspirin provides a health benefit. From the efficacy perspective this is taken to mean that the combination is more effective than either agent considered alone. We present three Bayesian hierarchical survival models and apply them to the results of five randomized clinical trials. These trials evaluated the benefit of pravastatin in the secondary-prevention setting. Aspirin use was recorded for patients in these trials, but assignment to aspirin was not randomized. We compare the effects of pravastatin and aspirin considered in combination and when given alone. We focus on time to myocardial infarction, although it was just one of several endpoints considered in the presentation to the FDA. Two of the models assume proportional hazards and the third does not. In all three models we adjust for known covariates. Our principal focus is the probability that the combination of pravastatin and aspirin is at least as effective as the agents considered separately. We also find the probability that the combination is synergistic in the sense that the effect of the combination is better than the sum of the effects of the two agents taken alone.