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Industry sponsorship bias in cost effectiveness analysis: registry based analysis
OBJECTIVE: To assess the association between industry sponsorship (drug, medical device, and biotechnology companies) and cost effectiveness results in cost effectiveness analysis (CEA). DESIGN: Registry based analysis DATA SOURCE: The Tufts Cost-Effectiveness Analysis Registry was used to identify...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group Ltd.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9214880/ https://www.ncbi.nlm.nih.gov/pubmed/35732297 http://dx.doi.org/10.1136/bmj-2021-069573 |
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author | Xie, Feng Zhou, Ting |
author_facet | Xie, Feng Zhou, Ting |
author_sort | Xie, Feng |
collection | PubMed |
description | OBJECTIVE: To assess the association between industry sponsorship (drug, medical device, and biotechnology companies) and cost effectiveness results in cost effectiveness analysis (CEA). DESIGN: Registry based analysis DATA SOURCE: The Tufts Cost-Effectiveness Analysis Registry was used to identify all CEAs published in Medline between 1976 and 2021. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: CEAs that reported incremental cost effectiveness ratio (ICER) using quality adjusted life year and provided sufficient information about the magnitude or location of the ICER. METHODS: Descriptive analyses were used to describe and compare the characteristics of CEAs with and without industry sponsorship. Logistic regression was used to identify the association between industry sponsorship and the cost effective conclusion using selected threshold values ($50 000 (£40 511; €47 405), $100 000, and $150 000). Robust linear regression was used to assess the association between industry sponsorship and the magnitude of ICER. All regression analyses were adjusted for disease and study design characteristics. RESULTS: 8192 CEAs were eligible and included in the analysis, with 2437 (29.7%) sponsored by industry. Industry sponsored CEAs were more likely to publish ICERs below $50 000 (adjusted odds ratio 2.06, 95% confidence interval 1.82 to 2.33), $100 000 (2.95, 2.52 to 3.44), and $150 000 (3.34, 2.80 to 3.99) than non-industry sponsored studies. Among 5877 CEAs that reported positive incremental costs and quality adjusted life years, ICERs from industry sponsored studies were 33% lower (95% confidence interval −40 to −26) than those from non-industry sponsored studies. CONCLUSIONS: Sponsorship bias in CEAs is significant, systemic, and present across a range of diseases and study designs. Use of CEAs conducted by independent bodies could provide payers with more ability to negotiate lower prices. This impartiality is especially important for countries that rely on published CEAs to inform policy making for insurance coverage because of limited capacity for independent economic analysis. |
format | Online Article Text |
id | pubmed-9214880 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92148802022-07-07 Industry sponsorship bias in cost effectiveness analysis: registry based analysis Xie, Feng Zhou, Ting BMJ Research OBJECTIVE: To assess the association between industry sponsorship (drug, medical device, and biotechnology companies) and cost effectiveness results in cost effectiveness analysis (CEA). DESIGN: Registry based analysis DATA SOURCE: The Tufts Cost-Effectiveness Analysis Registry was used to identify all CEAs published in Medline between 1976 and 2021. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: CEAs that reported incremental cost effectiveness ratio (ICER) using quality adjusted life year and provided sufficient information about the magnitude or location of the ICER. METHODS: Descriptive analyses were used to describe and compare the characteristics of CEAs with and without industry sponsorship. Logistic regression was used to identify the association between industry sponsorship and the cost effective conclusion using selected threshold values ($50 000 (£40 511; €47 405), $100 000, and $150 000). Robust linear regression was used to assess the association between industry sponsorship and the magnitude of ICER. All regression analyses were adjusted for disease and study design characteristics. RESULTS: 8192 CEAs were eligible and included in the analysis, with 2437 (29.7%) sponsored by industry. Industry sponsored CEAs were more likely to publish ICERs below $50 000 (adjusted odds ratio 2.06, 95% confidence interval 1.82 to 2.33), $100 000 (2.95, 2.52 to 3.44), and $150 000 (3.34, 2.80 to 3.99) than non-industry sponsored studies. Among 5877 CEAs that reported positive incremental costs and quality adjusted life years, ICERs from industry sponsored studies were 33% lower (95% confidence interval −40 to −26) than those from non-industry sponsored studies. CONCLUSIONS: Sponsorship bias in CEAs is significant, systemic, and present across a range of diseases and study designs. Use of CEAs conducted by independent bodies could provide payers with more ability to negotiate lower prices. This impartiality is especially important for countries that rely on published CEAs to inform policy making for insurance coverage because of limited capacity for independent economic analysis. BMJ Publishing Group Ltd. 2022-06-22 /pmc/articles/PMC9214880/ /pubmed/35732297 http://dx.doi.org/10.1136/bmj-2021-069573 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Research Xie, Feng Zhou, Ting Industry sponsorship bias in cost effectiveness analysis: registry based analysis |
title | Industry sponsorship bias in cost effectiveness analysis: registry based analysis |
title_full | Industry sponsorship bias in cost effectiveness analysis: registry based analysis |
title_fullStr | Industry sponsorship bias in cost effectiveness analysis: registry based analysis |
title_full_unstemmed | Industry sponsorship bias in cost effectiveness analysis: registry based analysis |
title_short | Industry sponsorship bias in cost effectiveness analysis: registry based analysis |
title_sort | industry sponsorship bias in cost effectiveness analysis: registry based analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9214880/ https://www.ncbi.nlm.nih.gov/pubmed/35732297 http://dx.doi.org/10.1136/bmj-2021-069573 |
work_keys_str_mv | AT xiefeng industrysponsorshipbiasincosteffectivenessanalysisregistrybasedanalysis AT zhouting industrysponsorshipbiasincosteffectivenessanalysisregistrybasedanalysis |