Methods for Estimation of Radiation Risk in Epidemiological Studies Accounting for Classical and Berkson Errors in Doses

Handle URI:
http://hdl.handle.net/10754/598819
Title:
Methods for Estimation of Radiation Risk in Epidemiological Studies Accounting for Classical and Berkson Errors in Doses
Authors:
Kukush, Alexander; Shklyar, Sergiy; Masiuk, Sergii; Likhtarov, Illya; Kovgan, Lina; Carroll, Raymond J; Bouville, Andre
Abstract:
With a binary response Y, the dose-response model under consideration is logistic in flavor with pr(Y=1 | D) = R (1+R)(-1), R = λ(0) + EAR D, where λ(0) is the baseline incidence rate and EAR is the excess absolute risk per gray. The calculated thyroid dose of a person i is expressed as Dimes=fiQi(mes)/Mi(mes). Here, Qi(mes) is the measured content of radioiodine in the thyroid gland of person i at time t(mes), Mi(mes) is the estimate of the thyroid mass, and f(i) is the normalizing multiplier. The Q(i) and M(i) are measured with multiplicative errors Vi(Q) and ViM, so that Qi(mes)=Qi(tr)Vi(Q) (this is classical measurement error model) and Mi(tr)=Mi(mes)Vi(M) (this is Berkson measurement error model). Here, Qi(tr) is the true content of radioactivity in the thyroid gland, and Mi(tr) is the true value of the thyroid mass. The error in f(i) is much smaller than the errors in ( Qi(mes), Mi(mes)) and ignored in the analysis. By means of Parametric Full Maximum Likelihood and Regression Calibration (under the assumption that the data set of true doses has lognormal distribution), Nonparametric Full Maximum Likelihood, Nonparametric Regression Calibration, and by properly tuned SIMEX method we study the influence of measurement errors in thyroid dose on the estimates of λ(0) and EAR. The simulation study is presented based on a real sample from the epidemiological studies. The doses were reconstructed in the framework of the Ukrainian-American project on the investigation of Post-Chernobyl thyroid cancers in Ukraine, and the underlying subpolulation was artificially enlarged in order to increase the statistical power. The true risk parameters were given by the values to earlier epidemiological studies, and then the binary response was simulated according to the dose-response model.
Citation:
Kukush A, Shklyar S, Masiuk S, Likhtarov I, Kovgan L, et al. (2011) Methods for Estimation of Radiation Risk in Epidemiological Studies Accounting for Classical and Berkson Errors in Doses. The International Journal of Biostatistics 7: 1–30. Available: http://dx.doi.org/10.2202/1557-4679.1281.
Publisher:
Walter de Gruyter GmbH
Journal:
The International Journal of Biostatistics
KAUST Grant Number:
KUSCI-016-04
Issue Date:
16-Jan-2011
DOI:
10.2202/1557-4679.1281
PubMed ID:
21423564
PubMed Central ID:
PMC3058406
Type:
Article
ISSN:
1557-4679
Sponsors:
This work was supported by funds from the U.S. National Cancer Institute and the Radiation Protection Institute ATS of Ukraine. The authors also want to thank their colleges from the Institute of Endocrinology and Metabolism AMS of Ukraine and the Radiation Protection Institute ATS of Ukraine who contributed to the preparation of the results presented in the paper. Alexander Kukush is supported by the Swedish Institute grant SI-01424/2007. Carroll's research was supported by a grant from the National Cancer Institute (CA57030). This publication is based in part on work supported by Award Number KUSCI-016-04, made by King Abdullah University of Science and Technology (KAUST).
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Full metadata record

DC FieldValue Language
dc.contributor.authorKukush, Alexanderen
dc.contributor.authorShklyar, Sergiyen
dc.contributor.authorMasiuk, Sergiien
dc.contributor.authorLikhtarov, Illyaen
dc.contributor.authorKovgan, Linaen
dc.contributor.authorCarroll, Raymond Jen
dc.contributor.authorBouville, Andreen
dc.date.accessioned2016-02-25T13:41:51Zen
dc.date.available2016-02-25T13:41:51Zen
dc.date.issued2011-01-16en
dc.identifier.citationKukush A, Shklyar S, Masiuk S, Likhtarov I, Kovgan L, et al. (2011) Methods for Estimation of Radiation Risk in Epidemiological Studies Accounting for Classical and Berkson Errors in Doses. The International Journal of Biostatistics 7: 1–30. Available: http://dx.doi.org/10.2202/1557-4679.1281.en
dc.identifier.issn1557-4679en
dc.identifier.pmid21423564en
dc.identifier.doi10.2202/1557-4679.1281en
dc.identifier.urihttp://hdl.handle.net/10754/598819en
dc.description.abstractWith a binary response Y, the dose-response model under consideration is logistic in flavor with pr(Y=1 | D) = R (1+R)(-1), R = λ(0) + EAR D, where λ(0) is the baseline incidence rate and EAR is the excess absolute risk per gray. The calculated thyroid dose of a person i is expressed as Dimes=fiQi(mes)/Mi(mes). Here, Qi(mes) is the measured content of radioiodine in the thyroid gland of person i at time t(mes), Mi(mes) is the estimate of the thyroid mass, and f(i) is the normalizing multiplier. The Q(i) and M(i) are measured with multiplicative errors Vi(Q) and ViM, so that Qi(mes)=Qi(tr)Vi(Q) (this is classical measurement error model) and Mi(tr)=Mi(mes)Vi(M) (this is Berkson measurement error model). Here, Qi(tr) is the true content of radioactivity in the thyroid gland, and Mi(tr) is the true value of the thyroid mass. The error in f(i) is much smaller than the errors in ( Qi(mes), Mi(mes)) and ignored in the analysis. By means of Parametric Full Maximum Likelihood and Regression Calibration (under the assumption that the data set of true doses has lognormal distribution), Nonparametric Full Maximum Likelihood, Nonparametric Regression Calibration, and by properly tuned SIMEX method we study the influence of measurement errors in thyroid dose on the estimates of λ(0) and EAR. The simulation study is presented based on a real sample from the epidemiological studies. The doses were reconstructed in the framework of the Ukrainian-American project on the investigation of Post-Chernobyl thyroid cancers in Ukraine, and the underlying subpolulation was artificially enlarged in order to increase the statistical power. The true risk parameters were given by the values to earlier epidemiological studies, and then the binary response was simulated according to the dose-response model.en
dc.description.sponsorshipThis work was supported by funds from the U.S. National Cancer Institute and the Radiation Protection Institute ATS of Ukraine. The authors also want to thank their colleges from the Institute of Endocrinology and Metabolism AMS of Ukraine and the Radiation Protection Institute ATS of Ukraine who contributed to the preparation of the results presented in the paper. Alexander Kukush is supported by the Swedish Institute grant SI-01424/2007. Carroll's research was supported by a grant from the National Cancer Institute (CA57030). This publication is based in part on work supported by Award Number KUSCI-016-04, made by King Abdullah University of Science and Technology (KAUST).en
dc.publisherWalter de Gruyter GmbHen
dc.subjectRegression calibrationen
dc.subjectBerkson Measurement Erroren
dc.subjectChornobyl Accidenten
dc.subjectSimex Estimatoren
dc.subjectClassical Measurement Erroren
dc.subjectEstimation Of Radiation Risken
dc.subjectFull Maximum Likelihood Estimating Procedureen
dc.subjectUncertainties In Thyroid Doseen
dc.subject.meshRadiation Dosageen
dc.subject.meshChernobyl Nuclear Accidenten
dc.subject.meshComputer Simulationen
dc.subject.meshRadioactive Hazard Releaseen
dc.titleMethods for Estimation of Radiation Risk in Epidemiological Studies Accounting for Classical and Berkson Errors in Dosesen
dc.typeArticleen
dc.identifier.journalThe International Journal of Biostatisticsen
dc.identifier.pmcidPMC3058406en
dc.contributor.institutionUkraine Radiation Protection Institute.en
kaust.grant.numberKUSCI-016-04en

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