OBJECTIVES: Randomized, placebo-controlled clinical trials represent the gold standard for evaluating the clinical benefits of a new therapy. However, these are expensive, time-consuming, and may not be feasible/ethical in several situations. Alternatively, synthetic control arm data (SCA) uses real-world evidence (RWE) outside the trial setting to provide a control. Potential sources of bias can be addressed through identification of control candidates, statistical cohort balancing methods, and endpoint validation studies, inter alia. Regulators have issued guidance on incorporating RWE for regulatory decision-making. This research evaluates how payers have appraised drugs using SCA data.

METHODS: Publicly-available Food and Drug Administration (FDA) documents were screened for any FDA- approved therapy lacking Phase 3 comparative data that leveraged SCA. Payer appraisal guidance of these therapies were screened (NICE, SMC, CADTH, PBAC) (01/01/2014-31/12/2019).

RESULTS: Two FDA-approved therapies leveraged SCA data in the absence of any comparative trial data: avelumab (Merkel cell carcinoma, 2017) and blinatumomab (r/r Philadelphia-chromosome-negative acute lymphoblastic leukemia, 2014). Both were evaluated by all four payers. In all appraisals, SCA data was used. Only 2/8 mentioned/discussed any statistical cohort balancing (PBAC/blinatumomab and NICE/avelumab, others used naïve comparisons). Avelumab was approved/recommended by all four payers (though one was restricted [NICE] and another conditional [CADTH]). Blinatumomab was recommended/accepted by 3/4 payers–but preliminary/full Phase 3 data was available in 2/3 approvals. 6/7 recommendations were conditional on discounting/risk-sharing scheme. In all appraisals, the lack of any controlled data was discussed as a limitation.

CONCLUSIONS: The only two examples where SCAs with single-arm trials supported FDA approvals were very rare oncology indications. These data have generally been deemed sufficient to support payer approvals in obligate cost-utility payer bodies using simple naïve comparisons. Nevertheless, to offset uncertainties in conducting economic modelling whilst lacking direct comparative trial data some pricing discounts may have been required.