Informed decision‐making: statistical methodology for surrogacy evaluation and its role in licensing and reimbursement assessments

Weir, C. J. and Taylor, R. S. (2022) Informed decision‐making: statistical methodology for surrogacy evaluation and its role in licensing and reimbursement assessments. Pharmaceutical Statistics, 21(4), pp. 740-756. (doi: 10.1002/pst.2219) (PMID:35819121)

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The desire, by patients and society, for faster access to therapies has driven a long tradition of the use of surrogate endpoints in the evaluation of pharmaceuticals and, more recently, biologics and other innovative medical technologies. The consequent need for statistical validation of potential surrogate outcome measures is a prime example on the theme of statistical support for decision-making in health technology assessment (HTA). Following the pioneering methodology based on hypothesis testing that Prentice presented in 1989, a host of further methods, both frequentist and Bayesian, have been developed to enable the value of a putative surrogate outcome to be determined. This rich methodological seam has generated practical methods for surrogate evaluation, the most recent of which are based on the principles of information theory and bring together ideas from the causal effects and causal association paradigms. Following our synopsis of statistical methods, we then consider how regulatory authorities (on licensing) and payer and HTA agencies (on reimbursement) use clinical trial evidence based on surrogate outcomes. We review existing HTA surrogate outcome evaluative frameworks. We conclude with recommendations for further steps: (1) prioritisation by regulators and payers of the application of formal surrogate outcome evaluative frameworks, (2) application of formal Bayesian decision-analytic methods to support reimbursement decisions, and (3) greater utilization of conditional surrogate-based licensing and reimbursement approvals, with subsequent reassessment of treatments in confirmatory trials based on final patient-relevant outcomes.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Taylor, Professor Rod
Authors: Weir, C. J., and Taylor, R. S.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU
Journal Name:Pharmaceutical Statistics
ISSN (Online):1539-1612
Published Online:12 July 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in Pharmaceutical Statistics 21(4): 740-756
Publisher Policy:Reproduced under a Creative Commons License
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
313399Reporting of randomised trials using surrogate outcomes: development of extensions to the CONSORT 2010 and SPIRIT 2013 guidance statementsRodney Stephen TaylorMedical Research Council (MRC)MR/V038400/1HW - MRC/CSO Social and Public Health Sciences Unit