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BACKGROUND: Advances in understanding of potentially targetable molecular pathways driving carcinogenesis coupled with rapid development of tumor profiling technologies are partitioning cancers into rare biomarker-defined diseases. Assessing biomarker-targeted therapies within these small populations in adequately powered randomized trials is becoming unfeasible, leading to reliance on lower quality evidence from uncontrolled studies using unvalidated surrogate outcomes. When robust evidence for a targeted therapy being considered already exists in common cancers, this evidence may potentially be extrapolated to support the use of this therapy in rare cancers sharing the same biomarker and reduce additional evidence requirements for regulatory or reimbursement approval. However, extrapolation may not be appropriate in some settings due to biological differences between cancer types. METHODS: Building on recommendations for core components of extrapolation identified from a scoping review of methodological guidance, we constructed a framework proposing criteria for extrapolating evidence for targeted therapies from common to rare cancers. RESULTS: Criteria reflect key assumptions of disease similarity when defined by the biomarker and similarity of treatment response. Criteria are judged under five extrapolation components: (1) Analytical validity of the test used to identify the biomarker and criteria used to define biomarker status in the rare cancer, (2) Strength of evidence supporting biomarker actionability in the rare cancer and evidence that actionability may differ from the common cancer, (3) Quantitative estimation of the natural history of the biomarker-defined rare cancer as control group, (4) Validity of surrogate endpoints used to extrapolate treatment effect from the common cancer and predictions of clinical benefit in the rare cancer, and (5) Similarity of the safety profile between cancers and methods to augment safety data in the rare cancer. Using these criteria, decision-makers can judge whether sufficient evidence exists to support extrapolation or identify specific knowledge gaps to better target further research to be able to judge whether extrapolation is appropriate or not. Residual uncertainties for fulfilling criteria can also define post-approval commitments. CONCLUSIONS: We outline a pragmatic and systematic approach for selecting and evaluating existing evidence to judge when extrapolation is appropriate. This framework can be used to promote standardized, comprehensive, and transparent decision-making and facilitate discussion between stakeholders in drug development and clinical guideline and health technology assessment groups. Citation Format: Doah Cho, Sarah J. Lord, John R. Simes, Wendy Cooper, Saskia Cheyne, Chee Khoon Lee. A framework for extrapolating evidence for molecularly targeted therapies from common to rare cancers - bridging the gap [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5963. |
