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Factors associated with positive and negative recommendations for cancer and non-cancer drugs for rare diseases in Canada
BACKGROUND: In Canada, reimbursement recommendations on drugs for common and rare diseases are overseen by the Canadian Agency for Drugs and Technologies in Health (CADTH) and made through the pan-Canadian Oncology Drug Review (pCODR) and the Common Drug Review (CDR). While the agency specifies info...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6555917/ https://www.ncbi.nlm.nih.gov/pubmed/31174574 http://dx.doi.org/10.1186/s13023-019-1104-7 |
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author | Nagase, Fernanda Naomi Inagaki Stafinski, Tania Sun, Jian Jhangri, Gian Menon, Devidas |
author_facet | Nagase, Fernanda Naomi Inagaki Stafinski, Tania Sun, Jian Jhangri, Gian Menon, Devidas |
author_sort | Nagase, Fernanda Naomi Inagaki |
collection | PubMed |
description | BACKGROUND: In Canada, reimbursement recommendations on drugs for common and rare diseases are overseen by the Canadian Agency for Drugs and Technologies in Health (CADTH) and made through the pan-Canadian Oncology Drug Review (pCODR) and the Common Drug Review (CDR). While the agency specifies information requirements for the review of drug submissions, how that information is used by each process to formulate final reimbursement recommendations, particularly on drugs for rare diseases (DRDs) in which per patient treatment costs are often high, is unclear. The purpose of this study was to determine which factors contribute to recommendation type for DRDs. METHODS: Information was extracted from CDR and pCODR recommendations on drugs for diseases with a prevalence < 1 in 2000 from January 2012 to April 2018. Data were tabulated and multiple logistic regression was applied to explore the association between recommendation type and the following factors: condition/review process (cancer vs non-cancer), year, prevalence, clinical effectiveness (improvements in surrogate, clinical and patient reported outcomes), safety, quality of evidence (availability of comparative data, consistency between population in trial and indication, and bias), clinical need, treatment cost, and incremental cost-effective ratio (ICER). Two-way interactions were also explored. RESULTS: A total of 103 recommendations were included. Eleven were resubmissions, all of which received a positive recommendation. Among new submissions (n = 92), DRDs that were safe or offered improvements in clinical or patient reported outcomes were more likely to receive positive reimbursement recommendations. No associations between recommendation type and daily treatment cost, cost-effectiveness, or condition (cancer or non-cancer) were found. CONCLUSIONS: Clinical effectiveness, as opposed to economic considerations or whether the drug is indicated for cancer or non-cancer, determine the type of reimbursement recommendation. |
format | Online Article Text |
id | pubmed-6555917 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-65559172019-06-10 Factors associated with positive and negative recommendations for cancer and non-cancer drugs for rare diseases in Canada Nagase, Fernanda Naomi Inagaki Stafinski, Tania Sun, Jian Jhangri, Gian Menon, Devidas Orphanet J Rare Dis Research BACKGROUND: In Canada, reimbursement recommendations on drugs for common and rare diseases are overseen by the Canadian Agency for Drugs and Technologies in Health (CADTH) and made through the pan-Canadian Oncology Drug Review (pCODR) and the Common Drug Review (CDR). While the agency specifies information requirements for the review of drug submissions, how that information is used by each process to formulate final reimbursement recommendations, particularly on drugs for rare diseases (DRDs) in which per patient treatment costs are often high, is unclear. The purpose of this study was to determine which factors contribute to recommendation type for DRDs. METHODS: Information was extracted from CDR and pCODR recommendations on drugs for diseases with a prevalence < 1 in 2000 from January 2012 to April 2018. Data were tabulated and multiple logistic regression was applied to explore the association between recommendation type and the following factors: condition/review process (cancer vs non-cancer), year, prevalence, clinical effectiveness (improvements in surrogate, clinical and patient reported outcomes), safety, quality of evidence (availability of comparative data, consistency between population in trial and indication, and bias), clinical need, treatment cost, and incremental cost-effective ratio (ICER). Two-way interactions were also explored. RESULTS: A total of 103 recommendations were included. Eleven were resubmissions, all of which received a positive recommendation. Among new submissions (n = 92), DRDs that were safe or offered improvements in clinical or patient reported outcomes were more likely to receive positive reimbursement recommendations. No associations between recommendation type and daily treatment cost, cost-effectiveness, or condition (cancer or non-cancer) were found. CONCLUSIONS: Clinical effectiveness, as opposed to economic considerations or whether the drug is indicated for cancer or non-cancer, determine the type of reimbursement recommendation. BioMed Central 2019-06-07 /pmc/articles/PMC6555917/ /pubmed/31174574 http://dx.doi.org/10.1186/s13023-019-1104-7 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Nagase, Fernanda Naomi Inagaki Stafinski, Tania Sun, Jian Jhangri, Gian Menon, Devidas Factors associated with positive and negative recommendations for cancer and non-cancer drugs for rare diseases in Canada |
title | Factors associated with positive and negative recommendations for cancer and non-cancer drugs for rare diseases in Canada |
title_full | Factors associated with positive and negative recommendations for cancer and non-cancer drugs for rare diseases in Canada |
title_fullStr | Factors associated with positive and negative recommendations for cancer and non-cancer drugs for rare diseases in Canada |
title_full_unstemmed | Factors associated with positive and negative recommendations for cancer and non-cancer drugs for rare diseases in Canada |
title_short | Factors associated with positive and negative recommendations for cancer and non-cancer drugs for rare diseases in Canada |
title_sort | factors associated with positive and negative recommendations for cancer and non-cancer drugs for rare diseases in canada |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6555917/ https://www.ncbi.nlm.nih.gov/pubmed/31174574 http://dx.doi.org/10.1186/s13023-019-1104-7 |
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