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) (PMCID:PMC9546435)
![[img]](https://eprints.gla.ac.uk/style/images/fileicons/text.png) |
Text
274868.pdf - Published Version Available under License Creative Commons Attribution. 1MB |
Abstract
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 |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| 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 |
| Publisher: | Wiley |
| ISSN: | 1539-1604 |
| 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 |
| Related URLs: |
University Staff: Request a correction | Enlighten Editors: Update this record
Funder and Project Information
Funder and Project Information