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Estimating and Testing Treatment Effects and Covariate by Treatment Interaction Effects in Randomized Clinical Trials with All-or-Nothing Compliance.

机译:在具有全有或全无合规性的随机临床试验中评估和测试治疗效果以及通过治疗相互作用的协变量。

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摘要

In this dissertation, we develop and evaluate methods for adjusting for treatment non-compliance in a randomized clinical trial with time-to-event outcome within the proportional hazards framework. Adopting the terminology in Cuzick et al. [2007], we assume the patient population consists of three (possibly) latent groups: the ambivalent group, the insisters and the refusers, and we are interested in analyzing the treatment effect, or the covariate by treatment interaction effect, within the ambivalent group. In Chapter 1, we propose a weighted per-protocol (Wtd PP) approach, and motivated by the pseudo likelihood (PL) considered in Cuzick et al. [2007], we also consider a full likelihood (FL) approach and for both likelihood methods, we propose an EM algorithm for estimation. In Chapter 2, we consider a biomarker study conducted within a clinical trial with non-compliance, where the interest is to estimate the interaction effect between the biomarker and the treatment but it is only feasible to collect the biomarker information from a selected sample of the patients enrolled on the trial. We propose a weighted likelihood (WL) method, a weighted pseudo likelihood (WPL) method and a doubly weighted per-protocol (DWtd PP) method by weighting the corresponding estimating equations in Chapter 1. In Chapter 3, we explore the impact of various assumptions of non-compliance on the performance of the methods considered in Chapter 1 and the commonly used intention-to-treat (ITT), as-treated (AT) and the per-protocol (PP) methods. Results from the first two chapters show that the likelihood methods and the weighted likelihood methods are unbiased, when the underlying model is correctly specified in the likelihood specification, and they are more efficient than the Wtd PP method and the DWtd PP method when the number of risk parameters is moderate. The Wtd PP method and the DWtd PP method are potentially more robust to outcome model misspecifications among the insisters and the refusers. Results from Chapter 3 suggest that when treatment non-compliance is present, careful considerations need to be given to the design and analysis of a clinical trial, and various methods could be considered given the specific setting of the trial.
机译:在本文中,我们开发并评估了在比例风险框架内具有事件发生时间的随机临床试验中调整治疗不依从性的方法。在Cuzick等人中采用术语。 [2007],我们假设患者群体由三个(可能)潜在群体组成:矛盾群体,坚持者和拒绝者,并且我们有兴趣分析矛盾群体中的治疗效果或通过治疗相互作用的协变量。在第一章中,我们提出了一种基于协议的加权(Wtd PP)方法,并以Cuzick等人考虑的伪似然(PL)为动机。 [2007],我们还考虑了全似然(FL)方法,对于这两种似然方法,我们提出了一种用于估计的EM算法。在第2章中,我们考虑了一项在不符合标准的临床试验中进行的生物标志物研究,目的是评估生物标志物与治疗之间的相互作用,但仅从选定的样本中收集生物标志物信息是可行的患者参加了试验。我们通过加权第1章中的相应估计方程,提出了加权似然(WL)方法,加权伪似然(WPL)方法和双加权按协议(DWtd PP)方法。在第3章中,我们探讨了各种方法的影响。假设不符合第1章中所考虑的方法的性能以及常用的意向治疗(ITT),经处理的(AT)和按方案(PP)的方法。前两章的结果表明,当似然规范中正确指定了基础模型时,似然法和加权似然法是无偏的,并且当Wn的PP数为2时,它们比Wtd PP和DWtd PP的效率更高。风险参数适中。 Wtd PP方法和DWtd PP方法对于坚持者和拒绝者之间的结果模型错误指定可能更健壮。第3章的结果表明,如果存在治疗不依从的情况,则需要仔细考虑临床试验的设计和分析,并且可以根据试验的具体设置考虑各种方法。

著录项

  • 作者

    Li, Shuli.;

  • 作者单位

    Harvard University.;

  • 授予单位 Harvard University.;
  • 学科 Biostatistics.;Pharmaceutical sciences.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 124 p.
  • 总页数 124
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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