Impact of uncertainties in exposure assessment on estimates of thyroid cancer risk among Ukrainian children and adolescents exposed from the Chernobyl accident.
The 1986 accident at the Chernobyl nuclear power plant remains the most serious nuclear accident in history, and excess thyroid cancers, particularly among those exposed to releases of iodine-131 remain the best-documented sequelae. Failure to take dose-measurement error into account can lead to bias in assessments of dose-response slope. Although risks in the Ukrainian-US thyroid screening study have been previously evaluated, errors in dose assessments have not been addressed hitherto. Dose-response patterns were examined in a thyroid screening prevalence cohort of 13,127 persons aged <18 at the time of the accident who were resident in the most radioactively contaminated regions of Ukraine. We extended earlier analyses in this cohort by adjusting for dose error in the recently developed TD-10 dosimetry. Three methods of statistical correction, via two types of regression calibration, and Monte Carlo maximum-likelihood, were applied to the doses that can be derived from the ratio of thyroid activity to thyroid mass. The two components that make up this ratio have different types of error, Berkson error for thyroid mass and classical error for thyroid activity. The first regression-calibration method yielded estimates of excess odds ratio of 5.78 Gy(-1) (95% CI 1.92, 27.04), about 7% higher than estimates unadjusted for dose error. The second regression-calibration method gave an excess odds ratio of 4.78 Gy(-1) (95% CI 1.64, 19.69), about 11% lower than unadjusted analysis. The Monte Carlo maximum-likelihood method produced an excess odds ratio of 4.93 Gy(-1) (95% CI 1.67, 19.90), about 8% lower than unadjusted analysis. There are borderline-significant (p = 0.101-0.112) indications of downward curvature in the dose response, allowing for which nearly doubled the low-dose linear coefficient. In conclusion, dose-error adjustment has comparatively modest effects on regression parameters, a consequence of the relatively small errors, of a mixture of Berkson and classical form, associated with thyroid dose assessment.
Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Mark P
MP
Little
Ukrainian Radiation Protection Institute, Kyiv, Ukraine ; Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.
Alexander G
AG
Kukush
Ukrainian Radiation Protection Institute, Kyiv, Ukraine.
Sergii V
SV
Masiuk
Ukrainian Radiation Protection Institute, Kyiv, Ukraine ; Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.
Sergiy
S
Shklyar
Department of Statistics, Blocker Building, Texas A&M University, College Station, Texas, United States of America.
Raymond J
RJ
Carroll
Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Jay H
JH
Lubin
Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America ; Sylvester Comprehensive Cancer Center, University of Miami, Miami, Florida, United States of America.
Deukwoo
D
Kwon
Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Alina V
AV
Brenner
State Institution "Institute of Endocrinology and Metabolism of Academy of Medical Sciences of Ukraine", Kyiv, Ukraine.
Mykola D
MD
Tronko
Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Kiyohiko
K
Mabuchi
State Institution "Institute of Endocrinology and Metabolism of Academy of Medical Sciences of Ukraine", Kyiv, Ukraine.
Tetiana I
TI
Bogdanova
Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Maureen
M
Hatch
Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America.
Lydia B
LB
Zablotska
State Institution "Institute of Endocrinology and Metabolism of Academy of Medical Sciences of Ukraine", Kyiv, Ukraine.
Valeriy P
VP
Tereshchenko
Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Evgenia
E
Ostroumova
Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
André C
AC
Bouville
Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Vladimir
V
Drozdovitch
Ukrainian Radiation Protection Institute, Kyiv, Ukraine.
Mykola I
MI
Chepurny
Ukrainian Radiation Protection Institute, Kyiv, Ukraine.
Lina N
LN
Kovgan
Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Steven L
SL
Simon
State Institution "Institute of Endocrinology and Metabolism of Academy of Medical Sciences of Ukraine", Kyiv, Ukraine.
Victor M
VM
Shpak
Ukrainian Radiation Protection Institute, Kyiv, Ukraine.
Ilya A
IA
Likhtarev
D000293:Adolescent; D047852:Chernobyl Nuclear Accident; D002648:Child; D002675:Child, Preschool; D004307:Dose-Response Relationship, Radiation; D004781:Environmental Exposure; D005260:Female; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D007457:Iodine Radioisotopes; D016013:Likelihood Functions; D008297:Male; D009010:Monte Carlo Method; D009381:Neoplasms, Radiation-Induced / Q000175:diagnosis / Q000453:epidemiology* / Q000473:pathology; D016017:Odds Ratio; D011874:Radiometry; D012307:Risk Factors; D013961:Thyroid Gland / Q000473:pathology / Q000528:radiation effects; D013964:Thyroid Neoplasms / Q000175:diagnosis / Q000453:epidemiology* / Q000473:pathology; D014455:Ukraine / Q000453:epidemiology; D035501:Uncertainty
D007457:Iodine Radioisotopes