Single arm trials are emerging as an accepted way of assessing a new treatment intervention. They establish clinical benefit by demonstrating the positive effects of a new therapy or treatment, without the need to use placebo or standard of care as a control. Instead, alternative approaches of establishing the comparison are used; these have become known as external controls or synthetic control arms (SCA) and include approaches leveraging real world data from various sources or evaluations of historical clinical trial data.
Is your Trial a Candidate for a Synthetic Control Arm? Continue reading this blog to learn more.
Whereas placebo-controlled randomized control trials remain the gold standard, in some situations, single arm trials have become an accepted way of assessing a new treatment intervention. Like in the case of rare diseases, getting a control group is often difficult and randomizing to control is next to impossible because the disease is rare, and it is challenging to get patients. SCA is used a fair bit as an internal tool in scenarios where there is difficulty in patient recruitment, whether due to a small population or other issues with reaching enrollment targets. Advanced statistical methods are applied to historical trial or real world data to build the SCA in a way that allows for the appropriate comparison with data gathered during the execution of the single arm trial.
There could also be pragmatic or ethical issues to offering standard of care in certain therapeutic areas. For example, patients might drop out of an oncology trial if enrolled into the control arm, or it might simply be unethical to give the standard of care to an ill patient making a single arm trial a necessity. Instances where a single arm trial is implemented, a synthetic control arm can play an important role for augmenting data collected for submission.
In several cases, synthetic controls can prove to be quite helpful and they can resolve difficult problems in a fairly short period of time. Through our checklist, Cytel aims to provide researchers, clinicians and policy-makers with a quality assessment methodology for both readers and groups involved in relation to synthetic control research to improve the clarity of reporting. We recognize that each synthetic control project contains its own unique challenges with regards to generalizability of results, interpretation and associated statistical methodology.
Is your trial a candidate for a synthetic control arm?
Download our latest infographic to find out! Click below to access the infographic, which will help you determine if a synthetic control arm is the right method for your trial.