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Changing platforms without stopping the train: experiences of data management and data management systems when adapting platform protocols by adding and closing comparisons

机译：无需停止培训即可更改平台：通过添加和关闭比较来适应平台协议时的数据管理和数据管理系统的经验

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There is limited research and literature on the data management challenges encountered in multi-arm, multi-stage platform and umbrella protocols. These trial designs allow both (1) seamless addition of new research comparisons and (2) early stopping of accrual to individual comparisons that do not show sufficient activity. FOCUS4 (colorectal cancer) and STAMPEDE (prostate cancer), run from the Medical Research Council Clinical Trials Unit (CTU) at UCL, are two leading UK examples of clinical trials implementing adaptive platform protocol designs. To date, STAMPEDE has added five new research comparisons, closed two research comparisons following pre-planned interim analysis (lack of benefit), adapted the control arm following results from STAMPEDE and other relevant trials, and completed recruitment to six research comparisons. FOCUS4 has closed one research comparison following pre-planned interim analysis (lack of benefit) and added one new research comparison, with a number of further comparisons in the pipeline. We share our experiences from the operational aspects of running these adaptive trials, focusing on data management. We held discussion groups with STAMPEDE and FOCUS4 CTU data management staff to identify data management challenges specific to adaptive platform protocols. We collated data on a number of case report form (CRF) changes, database amendments and database growth since each trial began. We found similar adaptive protocol-specific challenges in both trials. Adding comparisons to and removing them from open trials provides extra layers of complexity to CRF and database development. At the start of an adaptive trial, CRFs and databases must be designed to be flexible and scalable in order to cope with the continuous changes, ensuring future data requirements are considered where possible. When adding or stopping a comparison, the challenge is to incorporate new data requirements while ensuring data collection within ongoing comparisons is unaffected. Some changes may apply to all comparisons; others may be comparison-specific or applicable only to patients recruited during a specific time period. We discuss the advantages and disadvantages of the different approaches to CRF and database design we implemented in these trials, particularly in relation to use and maintenance of generic versus comparison-specific CRFs and databases. The work required to add or remove a comparison, including the development and testing of changes, updating of documentation, and training of sites, must be undertaken alongside data management of ongoing comparisons. Adequate resource is required for these competing data management tasks, especially in trials with long follow-up. A plan is needed for regular and pre-analysis data cleaning for multiple comparisons that could recruit at different rates and periods of time. Data-cleaning activities may need to be split and prioritised, especially if analyses for different comparisons overlap in time. Adaptive trials offer an efficient model to run randomised controlled trials, but setting up and conducting the data management activities in these trials can be operationally challenging. Trialists and funders must plan for scalability in data collection and the resource required to cope with additional competing data management tasks.
机译：关于在多臂，多阶段平台和伞协议中遇到的数据管理挑战的研究和文献有限。这些试验设计既允许（1）无缝添加新的研究比较，又可以（2）尽早停止对没有显示足够活动性的个体比较进行应计。 UOC的医学研究理事会临床试验部门（CTU）运营的FOCUS4（结肠直肠癌）和STAMPEDE（前列腺癌）是英国实施自适应平台协议设计的两个主要临床试验实例。迄今为止，STAMPEDE已添加了五项新的研究比较，在预先计划的中期分析（缺乏收益）之后完成了两项研究比较，根据STAMPEDE和其他相关试验的结果调整了对照组，并完成了六项研究比较的招募。 FOCUS4在进行了预先计划的中期分析（没有收益）之后，已经完成了一项研究比较，并增加了一项新的研究比较，还有许多其他的比较正在进行中。我们从运行这些适应性试验的运营方面分享我们的经验，重点是数据管理。我们与STAMPEDE和FOCUS4 CTU数据管理人员举行了讨论小组，以确定针对自适应平台协议的数据管理挑战。自每次试验开始以来，我们整理了许多病例报告表（CRF）变更，数据库修订和数据库增长方面的数据。我们在两项试验中都发现了类似的适应性协议特定挑战。将比较添加到公开试验中或从公开试验中删除比较为CRF和数据库开发提供了额外的复杂性。在适应性试验开始时，必须将CRF和数据库设计为灵活且可扩展的，以应对持续的变化，并确保在可能的情况下考虑将来的数据需求。添加或停止比较时，面临的挑战是合并新的数据要求，同时确保正在进行的比较中的数据收集不受影响。某些更改可能适用于所有比较;其他可能是比较特定的，或仅适用于特定时间段内招募的患者。我们讨论了在这些试验中实施的CRF和数据库设计不同方法的优缺点，特别是在使用和维护通用CRF和比较特定的CRF和数据库方面。添加或删除比较所需的工作，包括变更的开发和测试，文档更新以及站点培训，必须与正在进行的比较的数据管理一起进行。这些竞争性数据管理任务需要足够的资源，尤其是在长期随访的试验中。需要制定计划以进行定期和分析前的数据清洗，以进行多个比较，这些比较可能会以不同的速率和时间进行。数据清理活动可能需要拆分并确定优先级，尤其是在不同比较的分析时间重叠的情况下。适应性试验提供了运行随机对照试验的有效模型，但是在这些试验中设置和进行数据管理活动可能会给运营带来挑战。试用者和资助者必须计划数据收集的可伸缩性以及应对其他竞争数据管理任务所需的资源。

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