Changing platforms without stopping the train: experiences of data management and data management systems when
Dominic Hague1,2, Stephen Townsend3,4, Lindsey Masters3,4
1MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, UCL, London, UK. d.hague@ucl.ac.uk.
Trials
|May 30, 2019
Summary
Adaptive platform trials present unique data management challenges. Flexible case report forms and databases are crucial for managing evolving trial designs and ensuring data integrity throughout complex adaptive clinical trials.
Area of Science:
- Clinical Trials Methodology
- Data Management in Research
- Oncology Clinical Research
Background:
- Limited research exists on data management for multi-arm, multi-stage platform and umbrella protocols.
- Adaptive trial designs allow seamless addition/stopping of comparisons, exemplified by FOCUS4 (colorectal cancer) and STAMPEDE (prostate cancer).
- These trials have undergone significant adaptations, including adding/closing comparisons and modifying control arms.
Purpose of the Study:
- To identify and share data management challenges specific to adaptive platform protocols.
- To analyze operational experiences from the STAMPEDE and FOCUS4 trials.
- To provide insights into best practices for data management in adaptive trials.
Main Methods:
- Discussion groups were held with data management staff from STAMPEDE and FOCUS4.
- Data on case report form (CRF) changes, database amendments, and database growth were collected.
- Experiences from the operational aspects of running these adaptive trials were documented.
Main Results:
- Similar adaptive protocol-specific challenges were identified in both trials.
- Adding/removing comparisons complicates CRF and database development, requiring flexible and scalable designs.
- Managing continuous changes necessitates careful planning for data collection and database amendments.
Conclusions:
- Adaptive trials are efficient but pose operational data management challenges.
- CRFs and databases must be designed for flexibility and scalability from the outset.
- Adequate resources and planning are essential for managing competing data management tasks in adaptive trials.
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