LAUSR

Objectives Cancer is increasingly classified according to biomarkers that drive tumour growth and therapies developed to target them. In rare biomarker-defined cancers, randomised controlled trials to adequately assess targeted therapies may be infeasible. Extrapolating existing evidence of targeted therapy from common cancers to rare cancers sharing the same biomarker may reduce evidence requirements for regulatory approval in rare cancers. It is unclear whether guidelines exist for extrapolation. We sought to identify methodological guidance for extrapolating evidence from targeted therapies used for common cancers to rare biomarker-defined cancers. Design Scoping review. Data sources Websites of health technology assessment agencies, regulatory bodies, research groups, scientific societies and industry. EBM Reviews—Cochrane Methodology Register and Health Technology Assessment, Embase and MEDLINE databases (1946 to 11 May 2022). Eligibility criteria Papers proposing a framework or recommendations for extrapolating evidence for rare cancers, small populations and biomarker-defined cancers. Data extraction and synthesis We extracted framework details where available and guidance for components of extrapolation. We used these components to structure and summarise recommendations. Results We identified 23 papers. One paper provided an extrapolation framework but was not cancer specific. Extrapolation recommendations addressed six distinct components: strategies for grouping cancers as the same biomarker-defined disease; analytical validation requirements of a biomarker test to use across cancer types; strategies to generate control data when a randomised concurrent control arm is infeasible; sources to inform biomarker clinical utility assessment in the absence of prospective clinical evidence; requirements for surrogate endpoints chosen for the rare cancer; and assessing and augmenting safety data in the rare cancer. Conclusions In the absence of an established framework, our recommendations for components of extrapolation can be used to guide discussions about interpreting evidence to support extrapolation. The review can inform the development of an extrapolation framework for biomarker-targeted therapies in rare cancers.