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Title: Multiple criteria decision analysis in the context of health technology assessment: A simulation exercise on metastatic colorectal cancer with multiple stakeholders in the English setting
Authors: Angelis, Aris
Montibeller, Gilberto
Hochhauser, Daniel
Kanavos, Panos
Keywords: Multiple criteria decision analysis (MCDA)
Health technology assessment (HTA)
Advance Value Framework (AVF)
Metastatic colorectal cancer (mCRC)
England
National Institute for Health and Care Excellence (NICE)
Value assessment
New medicines
Issue Date: 2017
Publisher: © the Authors. Published by BioMed Central
Citation: ANGELIS, A. ...et al., 2017. Multiple criteria decision analysis in the context of health technology assessment: A simulation exercise on metastatic colorectal cancer with multiple stakeholders in the English setting. BMC Medical Informatics and Decision Making, 17: 149.
Abstract: © 2017 The Author(s). Background: Multiple criteria decision analysis (MCDA) has appeared as a methodology to address limitations of economic evaluation in health technology assessment (HTA), however there are limited empirical evidence from real world applications. The aim of this study is to test in practice a recently developed MCDA methodological framework known as Advance Value Framework (AVF) through a proof-of-concept case study engaging multiple stakeholders. Methods: A multi-attribute value theory methodological process was adopted involving problem structuring, model building, model assessment and model appraisal phases. A facilitated decision analysis modelling approach was used as part of a decision conference with thirteen participants. An expanded scope of the National Institute for Health and Care Excellence (NICE) remit acted as the study setting with the use of supplementary value concerns. Second-line biological treatments were evaluated for metastatic colorectal cancer (mCRC) patients having received prior chemotherapy, including cetuximab monotherapy, panitumumab monotherapy and aflibercept in combination with FOLFIRI chemotherapy. Initially 18 criteria attributes were considered spanning four value domains relating to therapeutic impact, safety profile, innovation level and socioeconomic impact. Results: Nine criteria attributes were finally included. Cetuximab scored the highest overall weighted preference value score of 45.7 out of 100, followed by panitumumab with 42.3, and aflibercept plus FOLFIRI with 14.4. The relative weights of the two most important criteria (overall survival and Grade 4 adverse events) added up to more than the relative weight of all other criteria together (52.1%). Main methodological limitation was the lack of comparative clinical effects across treatments and challenges included the selection of "lower" and "higher" reference levels on criteria attributes, eliciting preferences across attributes where participants had less experience, and ensuring that all attributes possess the right decision theory properties. Conclusions: This first application of AVF produced transparent rankings for three mCRC treatments based on their value, by assessing an explicit set of evaluation criteria while allowing for the elicitation and construction of participants' value preferences and their trade-offs. It proved it can aid the evaluation process and value communication of the alternative treatments for the group participants. Further research is needed to optimise its use as part of policy-making.
Description: This is an Open Access Article. It is published by BioMed Central under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/
Sponsor: Financial support for this study was provided in part by a grant from the European Commission, DG Research under the auspices of the Advance-HTA project (grant agreement number: 3059
Version: Published
DOI: 10.1186/s12911-017-0524-3
URI: https://dspace.lboro.ac.uk/2134/27701
Publisher Link: https://doi.org/10.1186/s12911-017-0524-3
Appears in Collections:Published Articles (Business)

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