To quantify and describe the use of real-world data (RWD) in National Institute for Health and Care Excellence (NICE) oncology technology appraisal (TA) final appraisal determination documents.

A systematic literature review was conducted on pharmaceutical NICE oncology TAs published between April 2000 and March 2024 (covering financial years 2000/2001 to 2023/2024 inclusive) extracted on 22 August 2023 (2000/2001 - 2022/2023) and 8 August 2024 (2023/2024).

NICE TA final appraisal determination documents.

All pharmaceutical oncology TAs published between April 2000 and March 2024 (financial years 2000/2001 to 2023/2024) that did not go on to be terminated.

The data required for eligibility screening was extracted from an Excel file directly from the NICE website, where data related to each TA was extracted using an automated script derived from published sources. TAs were assessed based on prespecified review criteria covering whether an RWD submission was reported by the committee, and if so, which RWD sources were used, alongside the methods reported and any feedback from the committee regarding the use of RWD. Bias was not assessed as part of the study.

Of 310 TAs identified, 135 (48.0%) used RWD. A variety of RWD types were used, mostly from UK or US data sources. 47 TAs (34.8%) leveraged RWD from multiple sources. RWD was mostly used in comparisons of survival (41.5%), to inform utility values (26.7%) and to compare baseline characteristics (19.3%), with matched adjusted indirect comparisons (MAICs) and external control arms (ECAs), seen from 2015 and 2018, respectively. The committee expressed concerns around the RWD presented by the company in 53 TAs (39.2%), the most common being a lack of generalisability to the UK population and/or National Health Service practice and comprehensiveness of the RWD.

This study quantifies the increasing use of diverse RWD sources in NICE oncology TAs, as well as the shift towards more complex methods like MAICs and ECAs. The feedback of the NICE committee highlights key areas of improvement as the generalisability and maturity of the RWD presented.