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血液学和肿瘤学II期临床试验分析:三角检验与常用方法的比较。

Analysis of phase II clinical trials in haematology and oncology: comparison of the triangular test to the usual methods.

作者信息

Benichou J, Bellissant E, Chastang C

机构信息

Département de Biostatistique et Informatique Médicale, Hôpital Saint Louis, Paris, France.

出版信息

Stat Med. 1991 Jun;10(6):989; discussion 989-90. doi: 10.1002/sim.4780100620.

Abstract

Phase II cancer clinical trials are non-comparative trials which are designed to determine whether the response rate p to the treatment under study is greater than a certain value p0, that is, to test H0, given by p less than or equal to p0 against H1 given by p greater than po. By choosing type I error alpha and the power 1-beta and by specifying H1, that is, by choosing a clinically relevant improvement p1), one can compute the number of patients N to be included for a fixed-sample approach. Various other approaches have been proposed such as multistage methods and Wald's continuous sequential probability ratio test (SPRT). As an alternative approach, we extended the triangular test (TT), proposed by Whitehead for comparative trials, to the situation of non-comparative trials with a binary outcome. We expressed H0 and H1 in terms of the log odds-ratio statistics, namely log [p(1-p0)/p0-(1-p)]. With this choice, the two statistics of interest, Z and V, have simple expressions: Z is the difference between the observed number of positive outcomes and the expected number under H0 and V is the variance of Z under H0. After every group of n patients, Z is plotted against V, and the trial proceeds until a boundary is crossed. In our simulations, type I error alpha and the power 1-beta were close to nominal values with the TT and the average sample size was close to Wald's continuous SPRT and compared favourably with the multistage methods proposed by Herson and Fleming. Given its statistical properties and its easy use, the TT should be considered for planning and analysing cancer phase II trials.

摘要

癌症II期临床试验是非对照试验,旨在确定所研究治疗的缓解率p是否大于某个值p0,即检验原假设H0(p小于或等于p0)与备择假设H1(p大于p0)。通过选择I型错误α和检验功效1-β,并指定H1,即选择具有临床相关性的改善值p1,可以计算固定样本量方法所需纳入的患者数量N。还提出了各种其他方法,如多阶段方法和Wald连续序贯概率比检验(SPRT)。作为一种替代方法,我们将Whitehead为对照试验提出的三角检验(TT)扩展到二元结果的非对照试验情况。我们用对数优势比统计量来表示H0和H1,即log[p(1 - p0)/p0(1 - p)]。通过这种选择,两个感兴趣统计量Z和V有简单的表达式:Z是观察到的阳性结果数量与H0下预期数量的差值,V是H0下Z的方差。在每组n个患者之后,将Z与V绘制成图,试验继续进行,直到越过边界。在我们的模拟中,TT的I型错误α和检验功效1-β接近标称值,平均样本量接近Wald连续SPRT,并且与Herson和Fleming提出的多阶段方法相比更具优势。鉴于其统计特性和易用性,在规划和分析癌症II期试验时应考虑使用TT。

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