Impact of Uncertainties in Exposure Assessment on Thyroid Cancer Risk among Persons in Belarus Exposed as Children or Adolescents Due to the Chernobyl Accident.
Impact of Uncertainties in Exposure Assessment on Thyroid Cancer Risk among Persons in Belarus Exposed as Children or Adolescents Due to the Chernobyl Accident.
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DOI：
10.1371/journal.pone.0139826
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Drozdovitch V
中科院分区：
文献类型：
--
作者：
Little MP;Kwon D;Zablotska LB;Brenner AV;Cahoon EK;Rozhko AV;Polyanskaya ON;Minenko VF;Golovanov I;Bouville A;Drozdovitch V
切尔诺贝利事故发生几年后，乌克兰和白俄罗斯的甲状腺癌发病率过高，这被认为主要是反应堆释放的131 I的结果。虽然以前分析过白俄罗斯甲状腺癌发病率数据，但没有考虑到剂量测量误差。我们检查了甲状腺筛查患病率队列中的剂量反应模式，该队列包括11，732名事故发生时年龄在18岁以下的人，在1996-2004年期间诊断，他们直接进行甲状腺131 I活性测量，并居住在白俄罗斯放射性污染最严重的地区。应用了三种剂量误差校正方法（回归校准、蒙特卡罗最大似然法、贝叶斯马尔可夫链蒙特卡罗法）。无论使用何种回归调整方法，甲状腺癌患病率的剂量反应均具有统计学显著性（p<0.001）。在未校正剂量误差的情况下，超额比值比为1.51戈伊-（95% CI 0.53，3.86），当使用回归校准校正时，超额比值比降低了13%，为1.31戈伊-（95% CI 0.47，3.31）。蒙特卡罗最大似然法得出的超额比值比为1.48戈伊-（95% CI 0.53，3.87），比未调整分析低约2%。贝叶斯方法得出的最大后验超额比值比为1.16戈伊−（95%BCI 0.20，4.32），比未调整的分析低23%。根据所用的调整方法，剂量反应中存在临界显著性（p = 0.053-0.078）向下弯曲迹象。性别对辐射剂量趋势也有临界显著性（p = 0.102）的修正作用，但事故发生时的年龄或筛选时的年龄对剂量反应的修正作用不显著（p>0.2）。总之，当前研究中非共享经典剂量误差的贡献相对较小，导致对回归参数的影响相对较小。
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. 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. 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). In summary, the relatively small contribution of unshared classical dose error in the current study results in comparatively modest effects on the regression parameters.