TY - JOUR
T1 - Impact of uncertainties in exposure assessment on thyroid cancer risk among persons in Belarus exposed as children or adolescents due to the Chernobyl accident
AU - Little, Mark P.
AU - Kwon, Deukwoo
AU - Zablotska, Lydia B.
AU - Brenner, Alina V.
AU - Cahoon, Elizabeth K.
AU - Rozhko, Alexander V.
AU - Polyanskaya, Olga N.
AU - Minenko, Victor F.
AU - Golovanov, Ivan
AU - Bouville, André
AU - Drozdovitch, Vladimir
N1 - Funding Information:
The authors are grateful for the detailed and helpful comments of the three referees. The paper is dedicated to the memory of the late Dr Elaine Ron, who was instrumental in the initiation of the study and guided it to a late stage of its completion. This work was supported by the Intramural Research Program of the National Institutes of Health, the National Cancer Institute, Division of Cancer Epidemiology and Genetics. Dr. Zablotska’s work is supported by NCI contract NO1-CP-21178 and NCI grant 5K07CA132918.
PY - 2015/10/14
Y1 - 2015/10/14
N2 - Background The excess incidence of thyroid cancer in Ukraine and Belarus observed a few years after the Chernobyl accident is considered to be largely the result of 131I released from the reactor. Although the Belarus thyroid cancer prevalence data has been previously analyzed, no account was taken of dose measurement error. Methods We examined dose-response patterns in a thyroid screening prevalence cohort of 11,732 persons aged under 18 at the time of the accident, diagnosed during 1996-2004, who had direct thyroid 131I activity measurement, and were resident in the most radio-actively contaminated regions of Belarus. Three methods of dose-error correction (regression calibration, Monte Carlo maximum likelihood, Bayesian Markov Chain Monte Carlo) were applied. Results There was a statistically significant (p<0.001) increasing dose-response for prevalent thyroid cancer, irrespective of regression-adjustment method used. Without adjustment for dose errors the excess odds ratio was 1.51 Gy- (95% CI 0.53, 3.86), which was reduced by 13% when regression-calibration adjustment was used, 1.31 Gy- (95% CI 0.47, 3.31). A Monte Carlo maximum likelihood method yielded an excess odds ratio of 1.48 Gy- (95% CI 0.53, 3.87), about 2% lower than the unadjusted analysis. The Bayesian method yielded a maximum posterior excess odds ratio of 1.16 Gy- (95% BCI 0.20, 4.32), 23% lower than the unadjusted analysis. There were borderline significant (p = 0.053-0.078) indications of downward curvature in the dose response, depending on the adjustment methods used. There were also borderline significant (p = 0.102) modifying effects of gender on the radiation dose trend, but no significant modifying effects of age at time of accident, or age at screening as modifiers of dose response (p>0.2). Conclusions In summary, the relatively small contribution of unshared classical dose error in the current study results in comparatively modest effects on the regression parameters.
AB - Background The excess incidence of thyroid cancer in Ukraine and Belarus observed a few years after the Chernobyl accident is considered to be largely the result of 131I released from the reactor. Although the Belarus thyroid cancer prevalence data has been previously analyzed, no account was taken of dose measurement error. Methods We examined dose-response patterns in a thyroid screening prevalence cohort of 11,732 persons aged under 18 at the time of the accident, diagnosed during 1996-2004, who had direct thyroid 131I activity measurement, and were resident in the most radio-actively contaminated regions of Belarus. Three methods of dose-error correction (regression calibration, Monte Carlo maximum likelihood, Bayesian Markov Chain Monte Carlo) were applied. Results There was a statistically significant (p<0.001) increasing dose-response for prevalent thyroid cancer, irrespective of regression-adjustment method used. Without adjustment for dose errors the excess odds ratio was 1.51 Gy- (95% CI 0.53, 3.86), which was reduced by 13% when regression-calibration adjustment was used, 1.31 Gy- (95% CI 0.47, 3.31). A Monte Carlo maximum likelihood method yielded an excess odds ratio of 1.48 Gy- (95% CI 0.53, 3.87), about 2% lower than the unadjusted analysis. The Bayesian method yielded a maximum posterior excess odds ratio of 1.16 Gy- (95% BCI 0.20, 4.32), 23% lower than the unadjusted analysis. There were borderline significant (p = 0.053-0.078) indications of downward curvature in the dose response, depending on the adjustment methods used. There were also borderline significant (p = 0.102) modifying effects of gender on the radiation dose trend, but no significant modifying effects of age at time of accident, or age at screening as modifiers of dose response (p>0.2). Conclusions In summary, the relatively small contribution of unshared classical dose error in the current study results in comparatively modest effects on the regression parameters.
UR - https://www.scopus.com/pages/publications/84949033125
U2 - 10.1371/journal.pone.0139826
DO - 10.1371/journal.pone.0139826
M3 - Article
C2 - 26465339
AN - SCOPUS:84949033125
SN - 1932-6203
VL - 10
JO - PLoS ONE
JF - PLoS ONE
IS - 10
M1 - e0139826
ER -