From Framework to Practice: Evaluating the Uptake of Sensitivity Analyses in The National Institute for Health and...

Growing reliance on single-arm trials (SATs) is driving increased real-world external control arm (RW-ECA) use in health technology assessment submissions. However, concerns over residual confounding and unmeasured bias often limit acceptability. The National Institute for Health and Care Excellence (NICE) real-world evidence framework encourages the use of sensitivity analyses, including quantitative bias analysis (QBA), to explore this uncertainty. This study describes the use of QBA methods and sensitivity analyses in NICE submissions using RW-ECAs before and in the early period after publication of the NICE real-world evidence Framework and discusses steps to encourage future adoption.

A targeted review of NICE single technology appraisals from 2019 to 2024 was conducted to identify submissions incorporating RW-ECAs. Data on the use of sensitivity analyses, including QBA, were extracted, with additional insights drawn from Evidence Assessment Group reports.

Of 334 submissions reviewed, 23 included a RW-ECA alongside an SAT, mostly in oncology. One submission implemented formal QBA methods for the RW-ECA, whereas 17 conducted broader sensitivity analyses, for example, sensitivity to different model specifications. The one submission that implemented QBA, methods were limited in scope and lacked structured methodology. In most cases, companies acknowledged residual confounding without formally quantifying its impact, and Evidence Assessment Groups frequently highlighted this as a source of residual uncertainty.

Uptake of structured bias analyses in submissions using SATs with RW-ECAs remains minimal. There is a clear opportunity for companies to enhance the robustness of their submissions by incorporating structured sensitivity or bias analyses to address residual bias.