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用于癌症I期临床试验的灵活贝叶斯方法。具有过量控制的剂量递增。

Flexible Bayesian methods for cancer phase I clinical trials. Dose escalation with overdose control.

作者信息

Tighiouart Mourad, Rogatko André, Babb James S

机构信息

Department of Biostatistics and Winship Cancer Institute, Emory University, 1518 Clifton Road, NE, Atlanta, GA 30322, USA.

出版信息

Stat Med. 2005 Jul 30;24(14):2183-96. doi: 10.1002/sim.2106.

Abstract

We examine a large class of prior distributions to model the dose-response relationship in cancer phase I clinical trials. We parameterize the dose-toxicity model in terms of the maximum tolerated dose (MTD) gamma and the probability of dose limiting toxicity (DLT) at the initial dose rho(0). The MTD is estimated using the EWOC (escalation with overdose control) method of Babb et al. We show through simulations that a candidate joint prior for (rho0,gamma) with negative a priori correlation structure results in a safer trial than the one that assumes independent priors for these two parameters while keeping the efficiency of the estimate of the MTD essentially unchanged.

摘要

我们研究了一大类先验分布,以对癌症I期临床试验中的剂量反应关系进行建模。我们根据最大耐受剂量(MTD)γ和初始剂量ρ(0)时剂量限制毒性(DLT)的概率对剂量毒性模型进行参数化。使用Babb等人的EWOC(过量控制下的剂量递增)方法估计MTD。我们通过模拟表明,对于(ρ0,γ)具有负先验相关结构的候选联合先验会导致比假设这两个参数独立先验的试验更安全,同时保持MTD估计效率基本不变。

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