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Estimating the time to a composite outcome when event ascertainment is delayed and non-monotone and event adjudication is incomplete.

机译:估计事件确定被延迟并且非单调和事件裁决不完整时达到复合结果的时间。

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摘要

Frequently in clinical trials, the endpoint of interest is the time to a composite outcome. A composite outcome consists of one or more types of primary event constituents and the time to the first event in this set is of interest. Although one can assume that event times will be reported by the time of the final analysis, one cannot necessarily assume that all events will have been recorded to the database at the time of interim monitoring. Events may be unreported, and thus, using the Kaplan-Meier estimate of the time to the first event will overestimate survival. Several methods exist to compensate for delayed event ascertainment and these may be applied to estimate survival time to a composite outcome if events are reported in order. However, if events are reported in a non- monotone fashion (out of order), a later event may be reported at the time of interim monitoring but the first event (the composite outcome of interest) may be unreported; hence, the earliest reported event time is not necessarily the true composite outcome time and these methods yield a biased estimate of survival. Additionally, many trials require primary endpoint adjudication, which may be incomplete at the time of interim monitoring; thus, the primary status of events may be unknown, additionally biasing the estimate. We propose an estimator that correctly estimates the time to the composite endpoint under these conditions and will illustrate using data from the Reduction of Events by Darbepoetin Alfa in Heart Failure (RED-HF) Trial. We will demonstrate the benefit of correct survival estimation on trial planning.
机译:在临床试验中,关注的终点通常是达到复合结果的时间。复合结果由一种或多种类型的主要事件成分组成,并且该组中第一个事件的时间很有趣。尽管可以假定事件时间将在最终分析时报告,但不一定可以假设在临时监视时所有事件都已记录到数据库中。事件可能未报告,因此,使用Kaplan-Meier估计第一次事件发生的时间将高估生存率。存在几种方法来补偿延迟的事件确定,如果按顺序报告事件,则可以将这些方法用于估计复合结果的生存时间。但是,如果事件以非单调方式报告(乱序),则在临时监视时可能会报告一个较晚的事件,但第一个事件(感兴趣的复合结果)可能不会报告;因此,最早报告的事件时间不一定是真正的复合结果时间,并且这些方法得出的生存估计有偏差。此外,许多试验都要求主要终点裁决,在临时监测时可能还不完整。因此,事件的主要状态可能是未知的,从而使估计值产生偏差。我们提出了一种估计器,可以正确估计在这些条件下到达复合终点的时间,并将说明使用达比泊汀·阿尔法在心力衰竭(RED-HF)试验中减少事件的数据。我们将在试验计划中证明正确的生存估计的好处。

著录项

  • 作者

    Schwefel, Brittany.;

  • 作者单位

    The University of Wisconsin - Madison.;

  • 授予单位 The University of Wisconsin - Madison.;
  • 学科 Statistics.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 170 p.
  • 总页数 170
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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