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Sampling strategies for selecting general population comparison cohorts

BACKGROUND: For a patient cohort, access to linkable population-based registries permits sampling of a comparison cohort from the general population, thereby contributing to the understanding of the disease in a population context. However, sampling without replacement in random order can lead to im...

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Autores principales: Heide-Jørgensen, Uffe, Adelborg, Kasper, Kahlert, Johnny, Sørensen, Henrik Toft, Pedersen, Lars
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165733/
https://www.ncbi.nlm.nih.gov/pubmed/30310326
http://dx.doi.org/10.2147/CLEP.S164456
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author Heide-Jørgensen, Uffe
Adelborg, Kasper
Kahlert, Johnny
Sørensen, Henrik Toft
Pedersen, Lars
author_facet Heide-Jørgensen, Uffe
Adelborg, Kasper
Kahlert, Johnny
Sørensen, Henrik Toft
Pedersen, Lars
author_sort Heide-Jørgensen, Uffe
collection PubMed
description BACKGROUND: For a patient cohort, access to linkable population-based registries permits sampling of a comparison cohort from the general population, thereby contributing to the understanding of the disease in a population context. However, sampling without replacement in random order can lead to immortal time bias by conditioning on the future. AIM: We compared the following strategies for sampling comparison cohorts in matched cohort studies with respect to time to ischemic stroke and mortality: sampling without replacement in random order; sampling with replacement; and sampling without replacement in chronological order. METHODS: We constructed index cohorts of individuals from the Danish general population with no particular trait, except being alive and without ischemic stroke on the index date. We also constructed index cohorts of persons aged >50 years from the general population. We then applied the sampling strategies to sample comparison cohorts (5:1 or 1:1) from the Danish general population and compared outcome risks between the index and comparison cohorts. Finally, we sampled comparison cohorts for a heart failure cohort using each strategy. RESULTS: We observed increased outcome risks in comparison cohorts sampled 5:1 without replacement in random order compared to the index cohorts. However, these increases were minuscule unless index persons were aged >50 years. In this setting, sampling without replacement in chronological order failed to sample a sufficient number of comparators, and the mortality risks in these comparison cohorts were lower than in the index cohorts. Sampling 1:1 showed no systematic difference between comparison and index cohorts. When we sampled comparison cohorts for the heart failure patients, we observed a pattern similar to when index persons were aged >50 years. CONCLUSION: When index persons were aged >50 years, ie, had high outcome risks, sampling 5:1 without replacement introduced bias. Sampling with replacement or 1:1 did not introduce bias.
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spelling pubmed-61657332018-10-11 Sampling strategies for selecting general population comparison cohorts Heide-Jørgensen, Uffe Adelborg, Kasper Kahlert, Johnny Sørensen, Henrik Toft Pedersen, Lars Clin Epidemiol Original Research BACKGROUND: For a patient cohort, access to linkable population-based registries permits sampling of a comparison cohort from the general population, thereby contributing to the understanding of the disease in a population context. However, sampling without replacement in random order can lead to immortal time bias by conditioning on the future. AIM: We compared the following strategies for sampling comparison cohorts in matched cohort studies with respect to time to ischemic stroke and mortality: sampling without replacement in random order; sampling with replacement; and sampling without replacement in chronological order. METHODS: We constructed index cohorts of individuals from the Danish general population with no particular trait, except being alive and without ischemic stroke on the index date. We also constructed index cohorts of persons aged >50 years from the general population. We then applied the sampling strategies to sample comparison cohorts (5:1 or 1:1) from the Danish general population and compared outcome risks between the index and comparison cohorts. Finally, we sampled comparison cohorts for a heart failure cohort using each strategy. RESULTS: We observed increased outcome risks in comparison cohorts sampled 5:1 without replacement in random order compared to the index cohorts. However, these increases were minuscule unless index persons were aged >50 years. In this setting, sampling without replacement in chronological order failed to sample a sufficient number of comparators, and the mortality risks in these comparison cohorts were lower than in the index cohorts. Sampling 1:1 showed no systematic difference between comparison and index cohorts. When we sampled comparison cohorts for the heart failure patients, we observed a pattern similar to when index persons were aged >50 years. CONCLUSION: When index persons were aged >50 years, ie, had high outcome risks, sampling 5:1 without replacement introduced bias. Sampling with replacement or 1:1 did not introduce bias. Dove Medical Press 2018-09-25 /pmc/articles/PMC6165733/ /pubmed/30310326 http://dx.doi.org/10.2147/CLEP.S164456 Text en © 2018 Heide-Jørgensen et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Heide-Jørgensen, Uffe
Adelborg, Kasper
Kahlert, Johnny
Sørensen, Henrik Toft
Pedersen, Lars
Sampling strategies for selecting general population comparison cohorts
title Sampling strategies for selecting general population comparison cohorts
title_full Sampling strategies for selecting general population comparison cohorts
title_fullStr Sampling strategies for selecting general population comparison cohorts
title_full_unstemmed Sampling strategies for selecting general population comparison cohorts
title_short Sampling strategies for selecting general population comparison cohorts
title_sort sampling strategies for selecting general population comparison cohorts
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165733/
https://www.ncbi.nlm.nih.gov/pubmed/30310326
http://dx.doi.org/10.2147/CLEP.S164456
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