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首席财务官:临床试验中剂量寻找的无校准概率贝叶斯设计。

CFO: Calibration-Free Odds Bayesian Designs for Dose Finding in Clinical Trials.

作者信息

Fang Jialu, Zhang Ninghao, Wang Wenliang, Yin Guosheng

机构信息

School of Computing and Data Science, The University of Hong Kong, Hong Kong, China.

出版信息

JCO Clin Cancer Inform. 2025 Feb;9:e2400184. doi: 10.1200/CCI-24-00184. Epub 2025 Jan 31.

Abstract

PURPOSE

Calibration-free odds type (CFO-type) designs have been demonstrated to be robust, model-free, and practically useful, which have become the state-of-the-art approach for dose finding. However, a key challenge for implementing such designs is a lack of accessible tools. We develop a user-friendly package and web-based software to facilitate easy implementation of CFO-type designs. Moreover, we incorporate randomization into the CFO framework.

METHODS

We created the package CFO and leveraged to build an interactive web application, CFO suite, for implementing CFO-type designs. We introduce the randomized CFO (rCFO) design by integrating the exploration-exploitation mechanism into the CFO framework.

RESULTS

The CFO package and CFO suite encompass various variants tailored to different clinical settings. Beyond the fundamental CFO design, these include the two-dimensional CFO (2dCFO) for drug-combination trials, accumulative CFO (aCFO) for accommodating all dose information, rCFO for integrating exploration-exploitation via randomization, time-to-event CFO (TITE-CFO), and fractional CFO (fCFO) for addressing late-onset toxicity. Using all information and addressing delayed toxicity outcomes, TITE-aCFO and fractional-aCFO are also included. The package provides functions for determining the subsequent cohort dose, selecting the maximum tolerated dose, and conducting simulations to evaluate performance, with results presented through textual and graphical outputs.

CONCLUSION

The CFO package and CFO suite provide comprehensive and flexible tools for implementing CFO-type designs in phase I clinical trials. This work is highly significant as it integrates all existing CFO-type designs to facilitate novel trial designs with enhanced performance. In addition, this promotes the spread of statistical methods using a user-friendly package and software. It strengthens collaborations between biostatisticians and clinicians, further enhancing trial performance in terms of efficiency and accuracy.

摘要

目的

无校准比值型(CFO型)设计已被证明具有稳健性、无模型性且实际有用,已成为剂量探索的最先进方法。然而,实施此类设计的一个关键挑战是缺乏可访问的工具。我们开发了一个用户友好的软件包和基于网络的软件,以促进CFO型设计的轻松实施。此外,我们将随机化纳入CFO框架。

方法

我们创建了软件包CFO,并利用它构建了一个交互式网络应用程序CFO套件,用于实施CFO型设计。我们通过将探索-利用机制整合到CFO框架中引入了随机化CFO(rCFO)设计。

结果

CFO软件包和CFO套件包含针对不同临床环境量身定制的各种变体。除了基本的CFO设计外,这些还包括用于药物组合试验的二维CFO(2dCFO)、用于容纳所有剂量信息的累积CFO(aCFO)、用于通过随机化整合探索-利用的rCFO、用于处理迟发性毒性的事件发生时间CFO(TITE-CFO)和分数CFO(fCFO)。还包括使用所有信息并处理延迟毒性结果的TITE-aCFO和分数-aCFO。该软件包提供了确定后续队列剂量、选择最大耐受剂量以及进行模拟以评估性能的功能,结果通过文本和图形输出呈现。

结论

CFO软件包和CFO套件为在I期临床试验中实施CFO型设计提供了全面且灵活的工具。这项工作非常重要,因为它整合了所有现有的CFO型设计,以促进具有更高性能的新型试验设计。此外,这通过用户友好的软件包和软件促进了统计方法的传播。它加强了生物统计学家和临床医生之间的合作,进一步提高了试验在效率和准确性方面的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc24/11797228/b0bf361d2d70/cci-9-e2400184-g001.jpg

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