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用于序贯估计的响应自适应随机化程序的启动设计。

Start-up designs for response-adaptive randomization procedures with sequential estimation.

作者信息

Haines Linda M, Sadiq Hassan

机构信息

Department of Statistical Sciences, University of Cape Town, Private Bag X3, Rondebosch, 7701, South Africa.

出版信息

Stat Med. 2015 Sep 20;34(21):2958-70. doi: 10.1002/sim.6528. Epub 2015 May 6.

Abstract

Response-adaptive randomization procedures are appropriate for clinical trials in which two or more treatments are to be compared, patients arrive sequentially and the response of each patient is recorded before the next patient arrives. However, for those procedures that involve sequential estimation of model parameters, start-up designs are commonly required in order to provide initial estimates of the parameters. In this paper, a suite of such start-up designs for two treatments and binary patient responses are considered and compared in terms of the numbers of patients required in order to give meaningful parameters estimates, the number of patients allocated to the better treatment, and the bias in the parameter estimates. It is shown that permuted block designs with blocks of size 4 are to be preferred over a wide range of parameter values. For the case of two treatments, normal responses and selected start-up procedures, a design incorporating complete randomization followed appropriately by repeats of one of the treatments yields the minimum expected number of patients and is to be preferred.

摘要

适应性随机化程序适用于比较两种或更多治疗方法的临床试验,患者依次到达,且在下一位患者到达之前记录每位患者的反应。然而,对于那些涉及模型参数序贯估计的程序,通常需要启动设计来提供参数的初始估计值。本文考虑并比较了一套针对两种治疗方法和二元患者反应的此类启动设计,比较内容包括为给出有意义的参数估计所需的患者数量、分配给更好治疗方法的患者数量以及参数估计中的偏差。结果表明,在广泛的参数值范围内,大小为4的置换区组设计更受青睐。对于两种治疗方法、正态反应和选定的启动程序的情况,一种先进行完全随机化然后适当重复其中一种治疗方法的设计产生的预期患者数量最少,是更可取的。

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