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Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value

BACKGROUND: Demonstrating safety and efficacy of new medical treatments requires clinical trials but clinical trials are costly and may not provide value proportionate to their costs. As most health systems have limited resources, it is therefore important to identify the trials with the highest val...

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Autores principales: Gillett, Piers, Mahar, Robert K, Tran, Nancy R, Rosenthal, Mark, IJzerman, Maarten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647033/
https://www.ncbi.nlm.nih.gov/pubmed/37964269
http://dx.doi.org/10.1186/s12962-023-00496-y
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author Gillett, Piers
Mahar, Robert K
Tran, Nancy R
Rosenthal, Mark
IJzerman, Maarten
author_facet Gillett, Piers
Mahar, Robert K
Tran, Nancy R
Rosenthal, Mark
IJzerman, Maarten
author_sort Gillett, Piers
collection PubMed
description BACKGROUND: Demonstrating safety and efficacy of new medical treatments requires clinical trials but clinical trials are costly and may not provide value proportionate to their costs. As most health systems have limited resources, it is therefore important to identify the trials with the highest value. Tools exist to assess elements of a clinical trial such as statistical validity but are not wholistic in their valuation of a clinical trial. This study aims to develop a measure of clinical trials value and provide an online tool for clinical trial prioritisation. METHODS: A search of the academic and grey literature and stakeholder consultation was undertaken to identify a set of criteria to aid clinical trial valuation using multi-criteria decision analysis. Swing weighting and ranking exercises were used to calculate appropriate weights of each of the included criteria and to estimate the partial-value function for each underlying metric. The set of criteria and their respective weights were applied to the results of six different clinical trials to calculate their value. RESULTS: Seven criteria were identified: ‘unmet need’, ‘size of target population’, ‘eligible participants can access the trial’, ‘patient outcomes’, ‘total trial cost’, ‘academic impact’ and ‘use of trial results’. The survey had 80 complete sets of responses (51% response rate). A trial designed to address an ‘Unmet Need’ was most commonly ranked as the most important with a weight of 24.4%, followed by trials demonstrating improved ‘Patient Outcomes’ with a weight of 21.2%. The value calculated for each trial allowed for their clear delineation and thus a final value ranking for each of the six trials. CONCLUSION: We confirmed that the use of the decision tool for valuing clinical trials is feasible and that the results are face valid based on the evaluation of six trials. A proof-of-concept applying this tool to a larger set of trials with an external validation is currently underway. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12962-023-00496-y.
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spelling pubmed-106470332023-11-14 Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value Gillett, Piers Mahar, Robert K Tran, Nancy R Rosenthal, Mark IJzerman, Maarten Cost Eff Resour Alloc Research BACKGROUND: Demonstrating safety and efficacy of new medical treatments requires clinical trials but clinical trials are costly and may not provide value proportionate to their costs. As most health systems have limited resources, it is therefore important to identify the trials with the highest value. Tools exist to assess elements of a clinical trial such as statistical validity but are not wholistic in their valuation of a clinical trial. This study aims to develop a measure of clinical trials value and provide an online tool for clinical trial prioritisation. METHODS: A search of the academic and grey literature and stakeholder consultation was undertaken to identify a set of criteria to aid clinical trial valuation using multi-criteria decision analysis. Swing weighting and ranking exercises were used to calculate appropriate weights of each of the included criteria and to estimate the partial-value function for each underlying metric. The set of criteria and their respective weights were applied to the results of six different clinical trials to calculate their value. RESULTS: Seven criteria were identified: ‘unmet need’, ‘size of target population’, ‘eligible participants can access the trial’, ‘patient outcomes’, ‘total trial cost’, ‘academic impact’ and ‘use of trial results’. The survey had 80 complete sets of responses (51% response rate). A trial designed to address an ‘Unmet Need’ was most commonly ranked as the most important with a weight of 24.4%, followed by trials demonstrating improved ‘Patient Outcomes’ with a weight of 21.2%. The value calculated for each trial allowed for their clear delineation and thus a final value ranking for each of the six trials. CONCLUSION: We confirmed that the use of the decision tool for valuing clinical trials is feasible and that the results are face valid based on the evaluation of six trials. A proof-of-concept applying this tool to a larger set of trials with an external validation is currently underway. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12962-023-00496-y. BioMed Central 2023-11-14 /pmc/articles/PMC10647033/ /pubmed/37964269 http://dx.doi.org/10.1186/s12962-023-00496-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Gillett, Piers
Mahar, Robert K
Tran, Nancy R
Rosenthal, Mark
IJzerman, Maarten
Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value
title Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value
title_full Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value
title_fullStr Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value
title_full_unstemmed Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value
title_short Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value
title_sort developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647033/
https://www.ncbi.nlm.nih.gov/pubmed/37964269
http://dx.doi.org/10.1186/s12962-023-00496-y
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