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Estimating the standardized incidence ratio (SIR) with incomplete follow-up data
BACKGROUND: A standard parameter to compare the disease incidence of a cohort relative to the population is the standardized incidence ratio (SIR). For statistical inference is commonly assumed that the denominator, the expected number of cases, is fixed. If a disease registry is available, incident...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5389158/ https://www.ncbi.nlm.nih.gov/pubmed/28403811 http://dx.doi.org/10.1186/s12874-017-0335-3 |
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author | Becher, Heiko Winkler, Volker |
author_facet | Becher, Heiko Winkler, Volker |
author_sort | Becher, Heiko |
collection | PubMed |
description | BACKGROUND: A standard parameter to compare the disease incidence of a cohort relative to the population is the standardized incidence ratio (SIR). For statistical inference is commonly assumed that the denominator, the expected number of cases, is fixed. If a disease registry is available, incident cases can sometimes be identified by linkage with the registry, however, registries may not contain information on migration or death from other causes. A complete follow-up with a population registry may not be possible. In that case, end-of-follow-up date and therefore, exact person-years of observation are unknown. METHODS: We have developed a method to estimate the observation times and to derive the expected number of cases using population data on mortality and migration rates. We investigate the impact of the underlying assumptions with a sensitivity analysis. RESULTS: The method provides a useful estimate of the SIR. We illustrate the method with a numerical example, a simulation study and with a study on standardized cancer incidence ratios in a cohort of migrants relative to the German population. We show that the additional variance induced by the estimation method is small, so that standard methods for inference can be applied. CONCLUSIONS: Estimation of the observation time is possible for cohort studies with incomplete follow-up. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12874-017-0335-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5389158 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53891582017-04-14 Estimating the standardized incidence ratio (SIR) with incomplete follow-up data Becher, Heiko Winkler, Volker BMC Med Res Methodol Research Article BACKGROUND: A standard parameter to compare the disease incidence of a cohort relative to the population is the standardized incidence ratio (SIR). For statistical inference is commonly assumed that the denominator, the expected number of cases, is fixed. If a disease registry is available, incident cases can sometimes be identified by linkage with the registry, however, registries may not contain information on migration or death from other causes. A complete follow-up with a population registry may not be possible. In that case, end-of-follow-up date and therefore, exact person-years of observation are unknown. METHODS: We have developed a method to estimate the observation times and to derive the expected number of cases using population data on mortality and migration rates. We investigate the impact of the underlying assumptions with a sensitivity analysis. RESULTS: The method provides a useful estimate of the SIR. We illustrate the method with a numerical example, a simulation study and with a study on standardized cancer incidence ratios in a cohort of migrants relative to the German population. We show that the additional variance induced by the estimation method is small, so that standard methods for inference can be applied. CONCLUSIONS: Estimation of the observation time is possible for cohort studies with incomplete follow-up. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12874-017-0335-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-04-12 /pmc/articles/PMC5389158/ /pubmed/28403811 http://dx.doi.org/10.1186/s12874-017-0335-3 Text en © The Author(s). 2017 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 Article Becher, Heiko Winkler, Volker Estimating the standardized incidence ratio (SIR) with incomplete follow-up data |
title | Estimating the standardized incidence ratio (SIR) with incomplete follow-up data |
title_full | Estimating the standardized incidence ratio (SIR) with incomplete follow-up data |
title_fullStr | Estimating the standardized incidence ratio (SIR) with incomplete follow-up data |
title_full_unstemmed | Estimating the standardized incidence ratio (SIR) with incomplete follow-up data |
title_short | Estimating the standardized incidence ratio (SIR) with incomplete follow-up data |
title_sort | estimating the standardized incidence ratio (sir) with incomplete follow-up data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5389158/ https://www.ncbi.nlm.nih.gov/pubmed/28403811 http://dx.doi.org/10.1186/s12874-017-0335-3 |
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