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AIDE:用于加速I期临床试验的自适应患者内剂量递增设计。

AIDE: Adaptive intrapatient dose escalation designs to accelerate Phase I clinical trials.

作者信息

Zhou Yanhong, Zhao Yujie, Cicconetti Greg, Mu Yunming, Yuan Ying, Wang Li, Penugonda Sudhir, Salman Zeena

机构信息

Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.

Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Illinois, USA.

出版信息

Pharm Stat. 2023 Mar;22(2):300-311. doi: 10.1002/pst.2272. Epub 2022 Nov 5.

Abstract

Designing Phase I clinical trials is challenging when accrual is slow or sample size is limited. The corresponding key question is: how to efficiently and reliably identify the maximum tolerated dose (MTD) using a sample size as small as possible? We propose model-assisted and model-based designs with adaptive intrapatient dose escalation (AIDE) to address this challenge. AIDE is adaptive in that the decision of conducting intrapatient dose escalation depends on both the patient's individual safety data, as well as other enrolled patient's safety data. When both data indicate reasonable safety, a patient may perform intrapatient dose escalation, generating toxicity data at more than one dose. This strategy not only provides patients the opportunity to receive higher potentially more effective doses, but also enables efficient statistical learning of the dose-toxicity profile of the treatment, which dramatically reduces the required sample size. Simulation studies show that the proposed designs are safe, robust, and efficient to identify the MTD with a sample size that is substantially smaller than conventional interpatient dose escalation designs. Practical considerations are provided and R code for implementing AIDE is available upon request.

摘要

当入组速度缓慢或样本量有限时,设计I期临床试验具有挑战性。相应的关键问题是:如何以尽可能小的样本量高效且可靠地确定最大耐受剂量(MTD)?我们提出了具有自适应患者内剂量递增(AIDE)的模型辅助和基于模型的设计,以应对这一挑战。AIDE具有适应性,即进行患者内剂量递增的决策取决于患者的个体安全性数据以及其他入组患者的安全性数据。当这两种数据均表明安全性合理时,患者可以进行患者内剂量递增,从而在多个剂量下生成毒性数据。这种策略不仅为患者提供了接受更高潜在更有效剂量的机会,还能对治疗的剂量-毒性概况进行有效的统计学习,从而显著减少所需的样本量。模拟研究表明,所提出的设计安全、稳健且高效,能够以比传统患者间剂量递增设计小得多的样本量确定MTD。文中提供了实际考虑因素,如需实现AIDE的R代码可随时索取。

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