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

TY - JOUR

T1 - Methodological challenges identified for the evaluation of clinical effectiveness in the context of accelerated regulatory approval

T2 - an overview

AU - Woolacott, Nerys

AU - Corbett, Mark

AU - Jones-Diette, Julie

AU - Hodgson, Robert

N1 - © 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.

PY - 2017/7/12

Y1 - 2017/7/12

N2 - 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.

AB - 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.

KW - Journal Article

KW - Review

U2 - 10.1016/j.jclinepi.2017.07.002

DO - 10.1016/j.jclinepi.2017.07.002

M3 - Article

C2 - 28709997

SN - 0895-4356

SP - 1

EP - 25

JO - Journal of Clinical Epidemiology

JF - Journal of Clinical Epidemiology

ER -