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Understanding bias when estimating life expectancy from age at death: a simulation approach applied to Morquio syndrome A

OBJECTIVE: Life expectancy can be estimated accurately from a cohort of individuals born in the same year and followed from birth to death. However, due to the resource-consuming nature of following a cohort prospectively, life expectancy is often assessed based upon retrospective death record revie...

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Autores principales: Yin, Xue, Ahn, Jaeil, Boca, Simina M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8760562/
https://www.ncbi.nlm.nih.gov/pubmed/35033196
http://dx.doi.org/10.1186/s13104-021-05894-0
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author Yin, Xue
Ahn, Jaeil
Boca, Simina M.
author_facet Yin, Xue
Ahn, Jaeil
Boca, Simina M.
author_sort Yin, Xue
collection PubMed
description OBJECTIVE: Life expectancy can be estimated accurately from a cohort of individuals born in the same year and followed from birth to death. However, due to the resource-consuming nature of following a cohort prospectively, life expectancy is often assessed based upon retrospective death record reviews. This conventional approach may lead to potentially biased estimates, in particular when estimating life expectancy of rare diseases such as Morquio syndrome A. We investigated the accuracy of life expectancy estimation using death records by simulating the survival of individuals with Morquio syndrome A under four different scenarios. RESULTS: When life expectancy was constant during the entire period, using death data did not result in a biased estimate. However, when life expectancy increased over time, as is often expected to be the case in rare diseases, using only death data led to a substantial underestimation of life expectancy. We emphasize that it is therefore crucial to understand how estimates of life expectancy are obtained, to interpret them in an appropriate context, and to assess estimation methods within a sensitivity analysis framework, similar to the simulations performed herein. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13104-021-05894-0.
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spelling pubmed-87605622022-01-18 Understanding bias when estimating life expectancy from age at death: a simulation approach applied to Morquio syndrome A Yin, Xue Ahn, Jaeil Boca, Simina M. BMC Res Notes Research Note OBJECTIVE: Life expectancy can be estimated accurately from a cohort of individuals born in the same year and followed from birth to death. However, due to the resource-consuming nature of following a cohort prospectively, life expectancy is often assessed based upon retrospective death record reviews. This conventional approach may lead to potentially biased estimates, in particular when estimating life expectancy of rare diseases such as Morquio syndrome A. We investigated the accuracy of life expectancy estimation using death records by simulating the survival of individuals with Morquio syndrome A under four different scenarios. RESULTS: When life expectancy was constant during the entire period, using death data did not result in a biased estimate. However, when life expectancy increased over time, as is often expected to be the case in rare diseases, using only death data led to a substantial underestimation of life expectancy. We emphasize that it is therefore crucial to understand how estimates of life expectancy are obtained, to interpret them in an appropriate context, and to assess estimation methods within a sensitivity analysis framework, similar to the simulations performed herein. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13104-021-05894-0. BioMed Central 2022-01-15 /pmc/articles/PMC8760562/ /pubmed/35033196 http://dx.doi.org/10.1186/s13104-021-05894-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Note
Yin, Xue
Ahn, Jaeil
Boca, Simina M.
Understanding bias when estimating life expectancy from age at death: a simulation approach applied to Morquio syndrome A
title Understanding bias when estimating life expectancy from age at death: a simulation approach applied to Morquio syndrome A
title_full Understanding bias when estimating life expectancy from age at death: a simulation approach applied to Morquio syndrome A
title_fullStr Understanding bias when estimating life expectancy from age at death: a simulation approach applied to Morquio syndrome A
title_full_unstemmed Understanding bias when estimating life expectancy from age at death: a simulation approach applied to Morquio syndrome A
title_short Understanding bias when estimating life expectancy from age at death: a simulation approach applied to Morquio syndrome A
title_sort understanding bias when estimating life expectancy from age at death: a simulation approach applied to morquio syndrome a
topic Research Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8760562/
https://www.ncbi.nlm.nih.gov/pubmed/35033196
http://dx.doi.org/10.1186/s13104-021-05894-0
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