Estimating the standardized incidence ratio (SIR) with incomplete follow-up data

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Estimating the standardized incidence ratio (SIR) with incomplete follow-up data. / Becher, Heiko; Winkler, Volker.

in: BMC MED RES METHODOL, Jahrgang 17, Nr. 1, 12.04.2017, S. 55.

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@article{2207cfd6792849458f6724e69ea4d95a,
title = "Estimating the standardized incidence ratio (SIR) with incomplete follow-up data",
abstract = "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.",
author = "Heiko Becher and Volker Winkler",
year = "2017",
month = apr,
day = "12",
doi = "10.1186/s12874-017-0335-3",
language = "English",
volume = "17",
pages = "55",
journal = "BMC MED RES METHODOL",
issn = "1471-2288",
publisher = "BioMed Central Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - Estimating the standardized incidence ratio (SIR) with incomplete follow-up data

AU - Becher, Heiko

AU - Winkler, Volker

PY - 2017/4/12

Y1 - 2017/4/12

N2 - 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.

AB - 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.

U2 - 10.1186/s12874-017-0335-3

DO - 10.1186/s12874-017-0335-3

M3 - SCORING: Journal article

C2 - 28403811

VL - 17

SP - 55

JO - BMC MED RES METHODOL

JF - BMC MED RES METHODOL

SN - 1471-2288

IS - 1

ER -