Methodological challenges identified for the evaluation of clinical effectiveness in the context of accelerated regulatory approval: an overview

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BACKGROUND: Regulatory authorities are approving innovative therapies with limited evidence. Whilst this level of data is sufficient for the regulator to establish an acceptable risk-benefit balance, it is problematic for downstream health technology assessment, where assessment of cost-effectiveness requires reliable estimates of effectiveness relative to existing clinical practice. Some key issues associated with a limited evidence base include using data, from non-randomised studies, from small single-arm trials, or from single-centre trials; and using surrogate endpoints.

METHODS: We examined these methodological challenges through a pragmatic review of the available literature.

RESULTS: Methods to adjust non-randomised studies for confounding are imperfect. The relative treatment effect generated from single-arm trials is uncertain and may be optimistic. Single-centre trial results may not be generalisable. Surrogate endpoints, on average, overestimate treatment effects. Current methods for analysing such data are limited and effectiveness claims based on these sub-optimal forms of evidence are likely to be subject to significant uncertainty.

CONCLUSIONS: Assessments of cost-effectiveness, based on the modelling of such data, are likely to be subject to considerable uncertainty. This uncertainty must not be underestimated by decision makers: methods for its quantification are required and schemes to protect payers from the cost of uncertainty should be implemented.

Original languageEnglish
Pages (from-to)1-25
Number of pages25
JournalJournal of Clinical Epidemiology
Early online date12 Jul 2017
Publication statusE-pub ahead of print - 12 Jul 2017

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© 2017 Published by Elsevier Inc. All rights reserved. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy.


  • Journal Article
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