Evidence map›Paper›PMID 35033196›Full record

ArticleBMC research notes2022

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

Xue Yin, Jaeil Ahn, Simina M Boca

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Article in BMC research notes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Xue YinDepartment of Biostatistics, Bioinformatics and Biomathematics, Georgetown University Medical Center, Washington, DC, USA.
Jaeil AhnDepartment of Biostatistics, Bioinformatics and Biomathematics, Georgetown University Medical Center, Washington, DC, USA. ja1030@georgetown.edu.
Simina M BocaDepartment of Biostatistics, Bioinformatics and Biomathematics, Georgetown University Medical Center, Washington, DC, USA. smb310@georgetown.edu.ORCID http://orcid.org/0000-0002-1400-3398

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveLife 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.

resultsWhen 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.

Indexed as

Mucopolysaccharidosis IVBiasCohort StudiesHumansLife ExpectancyRetrospective StudiesKaplan–MeierLife expectancyMorquio syndrome ASimulations

Identifiers

PMID35033196
PMCPMC8760562

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.