Historical controls and synthetic data: breast cancer, ALS

Use case 2 seeks to demonstrate how real-world data (RWD) can contribute to answering questions that are not typically answered by clinical trials, due to ethical or practical issues. These questions need to be answered for regulatory evaluation and health technology assessment (HTA), in the improvement of external validity and statistical power and precision.

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  • For breast cancer, historical population control arms will be created to include populations otherwise neglected in randomized controlled trials (RCT): pregnant women, women with serious co-morbidity that influences participation in studies (psychiatric disorder, cardiovascular disease), older women, men with breast cancer, and women with poor performance status.
  • In the scope of rare and lethal phenotypes such as Amyotrophic Lateral Sclerosis (ALS), there is a need for external control to increase the small sample size available, to increase inference robustness to improve HTA and reimbursement decisions. Real4Reg will employ synthetic data.

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Therefore, in use case 2 we will examine and display which types of RWD can serve as high-quality external control arms (i.e., description of feasibility and data quality), and which methods and standards should be applied to encourage transparency as replicability in RWD use for study design purposes.