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A technique for approximating transition rates from published survival analyses
BACKGROUND: Quality-adjusted-life-years (QALYs) are used to concurrently quantify morbidity and mortality within a single parameter. For this reason, QALYs can facilitate the discussion of risks and benefits during patient counseling regarding treatment options. QALYs are often calculated using part...
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/PMC6604134/ https://www.ncbi.nlm.nih.gov/pubmed/31303865 http://dx.doi.org/10.1186/s12962-019-0182-7 |
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author | Pahuta, Markian A. Werier, Joel Wai, Eugene K. Patchell, Roy A. Coyle, Doug |
author_facet | Pahuta, Markian A. Werier, Joel Wai, Eugene K. Patchell, Roy A. Coyle, Doug |
author_sort | Pahuta, Markian A. |
collection | PubMed |
description | BACKGROUND: Quality-adjusted-life-years (QALYs) are used to concurrently quantify morbidity and mortality within a single parameter. For this reason, QALYs can facilitate the discussion of risks and benefits during patient counseling regarding treatment options. QALYs are often calculated using partitioned-survival modelling. Alternatively, QALYs can be calculated using more flexible and informative state-transition models populated with transition rates estimated using multistate modelling (MSM) techniques. Unfortunately the latter approach is considered not possible when only progression-free survival (PFS) and overall survival (OS) analyses are reported. METHODS: We have developed a method that can be used to estimate approximate transition rates from published PFS and OS analyses (we will refer to transition rates estimated using full multistate methods as true transition rates). RESULTS: The approximation method is more accurate for estimating the transition rates out of health than the transition rate out of illness. The method tends to under-estimate true transition rates as censoring increases. CONCLUSIONS: In this article we present the basis for and use of the transition rate approximation method. We then apply the method to a case study and evaluate the method in a simulation study. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12962-019-0182-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6604134 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-66041342019-07-12 A technique for approximating transition rates from published survival analyses Pahuta, Markian A. Werier, Joel Wai, Eugene K. Patchell, Roy A. Coyle, Doug Cost Eff Resour Alloc Methodology BACKGROUND: Quality-adjusted-life-years (QALYs) are used to concurrently quantify morbidity and mortality within a single parameter. For this reason, QALYs can facilitate the discussion of risks and benefits during patient counseling regarding treatment options. QALYs are often calculated using partitioned-survival modelling. Alternatively, QALYs can be calculated using more flexible and informative state-transition models populated with transition rates estimated using multistate modelling (MSM) techniques. Unfortunately the latter approach is considered not possible when only progression-free survival (PFS) and overall survival (OS) analyses are reported. METHODS: We have developed a method that can be used to estimate approximate transition rates from published PFS and OS analyses (we will refer to transition rates estimated using full multistate methods as true transition rates). RESULTS: The approximation method is more accurate for estimating the transition rates out of health than the transition rate out of illness. The method tends to under-estimate true transition rates as censoring increases. CONCLUSIONS: In this article we present the basis for and use of the transition rate approximation method. We then apply the method to a case study and evaluate the method in a simulation study. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12962-019-0182-7) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-01 /pmc/articles/PMC6604134/ /pubmed/31303865 http://dx.doi.org/10.1186/s12962-019-0182-7 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 | Methodology Pahuta, Markian A. Werier, Joel Wai, Eugene K. Patchell, Roy A. Coyle, Doug A technique for approximating transition rates from published survival analyses |
title | A technique for approximating transition rates from published survival analyses |
title_full | A technique for approximating transition rates from published survival analyses |
title_fullStr | A technique for approximating transition rates from published survival analyses |
title_full_unstemmed | A technique for approximating transition rates from published survival analyses |
title_short | A technique for approximating transition rates from published survival analyses |
title_sort | technique for approximating transition rates from published survival analyses |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6604134/ https://www.ncbi.nlm.nih.gov/pubmed/31303865 http://dx.doi.org/10.1186/s12962-019-0182-7 |
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