Survival analysis following dynamic randomization

Xiaolong Luo; Mingyu Li; Gongjun Xu; Dongsheng Tu

doi:10.1016/j.conctc.2016.02.004

Survival analysis following dynamic randomization

Xiaolong Luo, Mingyu Li, Gongjun Xu, Dongsheng Tu

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Abstract

In this paper, we propose a method to analyze survival data from a clinical trial that utilizes a dynamic randomization for subject enrollment. The method directly accounts for dynamic subject randomization process using a marked point process (MPP). Its corresponding martingale process is used to formulate an equation for estimating the treatment effect size and for hypothesis testing. We perform simulation analyses to evaluate the outcomes of the proposed method as well as the conventional log rank method and re-randomized testing procedure.

Original language	English (US)
Pages (from-to)	39-47
Number of pages	9
Journal	Contemporary Clinical Trials Communications
Volume	3
DOIs	https://doi.org/10.1016/j.conctc.2016.02.004
State	Published - Aug 15 2016

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© 2016 The Authors.

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abstract = "In this paper, we propose a method to analyze survival data from a clinical trial that utilizes a dynamic randomization for subject enrollment. The method directly accounts for dynamic subject randomization process using a marked point process (MPP). Its corresponding martingale process is used to formulate an equation for estimating the treatment effect size and for hypothesis testing. We perform simulation analyses to evaluate the outcomes of the proposed method as well as the conventional log rank method and re-randomized testing procedure.",

author = "Xiaolong Luo and Mingyu Li and Gongjun Xu and Dongsheng Tu",

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AU - Luo, Xiaolong

AU - Li, Mingyu

AU - Xu, Gongjun

AU - Tu, Dongsheng

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N2 - In this paper, we propose a method to analyze survival data from a clinical trial that utilizes a dynamic randomization for subject enrollment. The method directly accounts for dynamic subject randomization process using a marked point process (MPP). Its corresponding martingale process is used to formulate an equation for estimating the treatment effect size and for hypothesis testing. We perform simulation analyses to evaluate the outcomes of the proposed method as well as the conventional log rank method and re-randomized testing procedure.

AB - In this paper, we propose a method to analyze survival data from a clinical trial that utilizes a dynamic randomization for subject enrollment. The method directly accounts for dynamic subject randomization process using a marked point process (MPP). Its corresponding martingale process is used to formulate an equation for estimating the treatment effect size and for hypothesis testing. We perform simulation analyses to evaluate the outcomes of the proposed method as well as the conventional log rank method and re-randomized testing procedure.

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JO - Contemporary Clinical Trials Communications

JF - Contemporary Clinical Trials Communications

ER -

Survival analysis following dynamic randomization

Abstract

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