Development of a framework and decision tool for the evaluation of health technologies based on surrogate endpoint evidence

被引:13
作者
Ciani, Oriana [1 ,2 ]
Grigore, Bogdan [3 ]
Taylor, Rod S. [4 ,5 ,6 ]
机构
[1] SDA Bocconi, Ctr Res Hlth & Social Care Management, Milan, Lombardia, Italy
[2] Univ Exeter, Coll Med & Hlth, Evidence Synth & Modelling Hlth Improvement, Exeter, Devon, England
[3] Univ Exeter, Coll Med & Hlth, Exeter Test Grp, Exeter, Devon, England
[4] Univ Glasgow, Inst Hlth & Well Being, MRC CSO Social & Publ Hlth Sci Unit, Glasgow, Lanark, Scotland
[5] Univ Glasgow, Inst Hlth & Well Being, Robertson Ctr Biostat, Glasgow, Lanark, Scotland
[6] Univ Exeter, Coll Med & Hlth, Exeter, Devon, England
关键词
cost-effectiveness; decision tool; health technology assessment; surrogate endpoints; validation; SYSTEMATIC REVIEWS; 1ST-LINE TREATMENT; CLINICAL-TRIALS; METAANALYSIS; OUTCOMES; VALIDATION; BIOMARKERS; SURVIVAL; LEUKEMIA;
D O I
10.1002/hec.4524
中图分类号
F [经济];
学科分类号
02 ;
摘要
In the drive toward faster patient access to treatments, health technology assessment (HTA) agencies and payers are increasingly faced with reliance on evidence based on surrogate endpoints, increasing decision uncertainty. Despite the development of a small number of evaluation frameworks, there remains no consensus on the detailed methodology for handling surrogate endpoints in HTA practice. This research overviews the methods and findings of four empirical studies undertaken as part of COMED (Pushing the Boundaries of Cost and Outcome Analysis of Medical Technologies) program work package 2 with the aim of analyzing international HTA practice of the handling and considerations around the use of surrogate endpoint evidence. We have synthesized the findings of these empirical studies, in context of wider contemporary body of methodological and policy-related literature on surrogate endpoints, to develop a web-based decision tool to support HTA agencies and payers when faced with surrogate endpoint evidence. Our decision tool is intended for use by HTA agencies and their decision-making committees together with the wider community of HTA stakeholders (including clinicians, patient groups, and healthcare manufacturers). Having developed this tool, we will monitor its use and we welcome feedback on its utility.
引用
收藏
页码:44 / 72
页数:29
相关论文
共 49 条
[1]   Use of Intermediate Endpoints in the Economic Evaluation of New Treatments for Advanced Cancer and Methods Adopted When Suitable Overall Survival Data are Not Available [J].
Beauchemin, Catherine ;
Lapierre, Marie-Eve ;
Letarte, Nathalie ;
Yelle, Louise ;
Lachaine, Jean .
PHARMACOECONOMICS, 2016, 34 (09) :889-900
[2]  
Boer J., 2021, J AM COLL CARDIOL, P2021
[3]  
Braun V., 2006, QUAL RES PSYCHOL, V3, P77, DOI [DOI 10.1080/14780887.2020.1769238, DOI 10.1191/1478088706QP063OA, 10.1191/1478088706qp063oa]
[4]   The use of validated and nonvalidated surrogate endpoints in two European Medicines Agency expedited approval pathways: A cross-sectional study of products authorised 2011-2018 [J].
Bruce, Catherine Schuster ;
Brhlikova, Petra ;
Heath, Joseph ;
McGettigan, Patricia .
PLOS MEDICINE, 2019, 16 (09)
[5]   Users' guides to the medical literature XIX. Applying clinical trial results A. How to use an article measuring the effect of an intervention on surrogate end points [J].
Bucher, HC ;
Guyatt, GH ;
Cook, DJ ;
Holbrook, A ;
McAlister, FA .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 1999, 282 (08) :771-778
[6]  
Bujkiewicz S, 2019, NICE DSU TECHNICAL S, V2019
[7]   Bivariate network meta-analysis for surrogate endpoint evaluation [J].
Bujkiewicz, Sylwia ;
Jackson, Dan ;
Thompson, John R. ;
Turner, Rebecca M. ;
Stadler, Nicolas ;
Abrams, Keith R. ;
White, Ian R. .
STATISTICS IN MEDICINE, 2019, 38 (18) :3322-3341
[8]   Uncertainty in the Bayesian meta-analysis of normally distributed surrogate endpoints [J].
Bujkiewicz, Sylwia ;
Thompson, John R. ;
Spata, Enti ;
Abrams, Keith R. .
STATISTICAL METHODS IN MEDICAL RESEARCH, 2017, 26 (05) :2287-2318
[9]   Surrogate threshold effect: An alternative measure for meta-analytic surrogate endpoint validation [J].
Burzykowski, Tomasz ;
Buyse, Marc .
PHARMACEUTICAL STATISTICS, 2006, 5 (03) :173-186
[10]   Biomarkers and surrogate end points-the challenge of statistical validation [J].
Buyse, Marc ;
Sargent, Daniel J. ;
Grothey, Axel ;
Matheson, Alastair ;
De Gramont, Aimery .
NATURE REVIEWS CLINICAL ONCOLOGY, 2010, 7 (06) :309-317