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细胞毒性药物I期临床试验的Logistic保留间隔剂量探索设计

Logistic retainment interval dose exploration design for Phase I clinical trials of cytotoxic agents.

作者信息

Murray Thomas A

机构信息

Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota, USA.

出版信息

Pharm Stat. 2021 Jul;20(4):850-863. doi: 10.1002/pst.2114. Epub 2021 Mar 18.

Abstract

Phase I studies of a cytotoxic agent often aim to identify the dose that provides an investigator specified target dose-limiting toxicity (DLT) probability. In practice, an initial cohort receives a dose with a putative low DLT probability, and subsequent dosing follows by consecutively deciding whether to retain the current dose, escalate to the adjacent higher dose, or de-escalate to the adjacent lower dose. This article proposes a Phase I design derived using a Bayesian decision-theoretic approach to this sequential decision-making process. The design consecutively chooses the action that minimizes posterior expected loss where the loss reflects the distance on the log-odds scale between the target and the DLT probability of the dose that would be given to the next cohort under the corresponding action. A logistic model is assumed for the log odds of a DLT at the current dose with a weakly informative t-distribution prior centered at the target. The key design parameters are the pre-specified odds ratios for the DLT probabilities at the adjacent higher and lower doses. Dosing rules may be pre-tabulated, as these only depend on the outcomes at the current dose, which greatly facilitates implementation. The recommended default version of the proposed design improves dose selection relative to many established designs across a variety of scenarios.

摘要

细胞毒性药物的I期研究通常旨在确定能提供研究者指定的目标剂量限制毒性(DLT)概率的剂量。在实际操作中,初始队列接受一个假定DLT概率较低的剂量,随后的给药则通过连续决定是维持当前剂量、升至相邻的更高剂量还是降至相邻的更低剂量来进行。本文提出了一种I期设计,该设计是使用贝叶斯决策理论方法来处理这个序贯决策过程而得出的。该设计连续选择使后验期望损失最小的行动,其中损失反映了目标与在相应行动下给予下一个队列的剂量的DLT概率在对数优势尺度上的距离。假设当前剂量下DLT的对数优势服从逻辑模型,其先验为弱信息t分布,以目标为中心。关键设计参数是相邻更高和更低剂量下DLT概率的预先指定的优势比。给药规则可以预先制成表格,因为这些仅取决于当前剂量的结果,这极大地便于实施。相对于许多既定设计,在各种情况下,所提出设计的推荐默认版本改进了剂量选择。

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