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A review of available software for adaptive clinical trial design

计算机科学 编码(集合论) 适应(眼睛) 代码评审 软件 源代码 过程(计算) 软件工程 公共领域 数据科学 领域(数学分析) 万维网 风险分析(工程) 软件开发 软件质量 程序设计语言 数学分析 集合(抽象数据类型) 哲学 神学 物理 光学 医学 数学
作者
Michael J. Grayling,Graham Wheeler
出处
期刊:Clinical Trials [SAGE]
卷期号:17 (3): 323-331 被引量:4
标识
DOI:10.1177/1740774520906398
摘要

Background/aims: The increasing cost of the drug development process has seen interest in the use of adaptive trial designs grow substantially. Accordingly, much research has been conducted to identify barriers to increasing the use of adaptive designs in practice. Several articles have argued that the availability of user-friendly software will be an important step in making adaptive designs easier to implement. Therefore, we present a review of the current state of software availability for adaptive trial design. Methods: We review articles from 31 journals published in 2013–2017 that relate to methodology for adaptive trials to assess how often code and software for implementing novel adaptive designs is made available at the time of publication. We contrast our findings against these journals’ policies on code distribution. We also search popular code repositories, such as Comprehensive R Archive Network and GitHub, to identify further existing user-contributed software for adaptive designs. From this, we are able to direct interested parties toward solutions for their problem of interest. Results: Only 30% of included articles made their code available in some form. In many instances, articles published in journals that had mandatory requirements on code provision still did not make code available. There are several areas in which available software is currently limited or saturated. In particular, many packages are available to address group sequential design, but comparatively little code is present in the public domain to determine biomarker-guided adaptive designs. Conclusions: There is much room for improvement in the provision of software alongside adaptive design publications. In addition, while progress has been made, well-established software for various types of trial adaptation remains sparsely available.

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