Last week, Robert Szulkin, Research Principal, Real World Evidence, discussed the need for real-world evidence studies, noting that not all clinical questions can be answered by randomized trials, such as in cases of rare diseases where it may be difficult to find enough patients for the trial. In these cases, he highlights that single-arm trials with an external comparator arm from real-world data may be a good alternative. Let’s take a closer look at this method:
Single-arm trials, unlike randomized control trials, forgo the use of a placebo or standard of care as a control. Instead, they establish clinical benefit by demonstrating the effects of a new therapy or treatment via comparison with a synthetic control arm (SCA) derived from external sources. This alternative approach leverages real-world data from various sources or evaluations of historical trial data for the sake of comparison. The use of SCA has enabled investigators to leverage combined data from uncontrolled single-arm trials and post-market studies to create much smaller trials.
Our eBook Demystifying Synthetic Control Arms delves into this topic and covers:
- An introduction to SCA
- Propensity scoring methods
- Bayesian dynamic borrowing
- A case study on non-small cell lung cancer
- Questions to ask if you are considering a choice between placebo-controlled and single-arm trials
To download the complimentary eBook, click below:
Demystifying Synthetic Control Arms kicks off this winter’s Weekend Reads series, which features complimentary publications on a variety of topics on clinical trial design and data science. Subscribe to our weekly newsletter below and never miss a post!
Read more from Perspectives on Enquiry and Evidence:
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Epidemiological Methods to Tackle Real-World Evidence Challenges
FDA Guidance on the Design and Conduct of Externally Controlled Trials — What to Watch
Developing Synthetic Control Arms Using Bayesian Models
