In oncological studies, the use of SCA (synthetic control arms) has successfully lead to the expedited approval of multiple innovative therapies.
For example, the EFGR modulator Tagrisso by AstraZeneca received approval from the FDA in only three years from the first patient receiving the dose due to the use of SCAs.
In non-oncological fields, SCA trials are commonly used in combination with natural history studies, for example, the trial performed for approval for Zolgensma, a gene therapy indicated for spinal muscular atrophy.
In order to choose the right approach for designing SCAs, different factors come into play such as the types of data available, the anticipated length of a trial, the desired sample size, and the potential biases.
The possibility of sampling bias while using real-world data is higher but can be quantified and minimized by adjusting the use of propensity scores.
Deciding the best SCA approach is important to make sure that the findings are robust and necessary transparency is maintained.
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