Data Challenges for Externally Controlled Trials: Viewpoint.
Russanthy Ruthiran VelummailumChelsea McKibbonDarren R BrennerElizabeth Ann StringerLeeland EkstromLouis DronPublished in: Journal of medical Internet research (2023)
The preferred evidence of a large randomized controlled trial is difficult to adopt in scenarios, such as rare conditions or clinical subgroups with high unmet needs, and evidence from external sources, including real-world data, is being increasingly considered by decision makers. Real-world data originate from many sources, and identifying suitable real-world data that can be used to contextualize a single-arm trial, as an external control arm, has several challenges. In this viewpoint article, we provide an overview of the technical challenges raised by regulatory and health reimbursement agencies when evaluating comparative efficacy, such as identification, outcome, and time selection challenges. By breaking down these challenges, we provide practical solutions for researchers to consider through the approaches of detailed planning, collection, and record linkage to analyze external data for comparative efficacy.
Keyphrases
- electronic health record
- randomized controlled trial
- big data
- study protocol
- public health
- clinical trial
- healthcare
- data analysis
- machine learning
- transcription factor
- risk assessment
- gene expression
- hiv infected
- artificial intelligence
- dna methylation
- genome wide
- phase ii
- high density
- decision making
- health information
- human health