Land Charles E, Kwon Deukwoo, Hoffman F Owen, Moroz Brian, Drozdovitch Vladimir, Bouville André, Beck Harold, Luckyanov Nicholas, Weinstock Robert M, Simon Steven L
National Cancer Institute (retired), Bethesda, Maryland.
Sylvester Comprehensive Cancer Center, University of Miami, Miami, Florida.
Radiat Res. 2015 Feb;183(2):159-173. doi: 10.1667/RR13794.1. Epub 2015 Jan 9.
Dosimetic uncertainties, particularly those that are shared among subgroups of a study population, can bias, distort or reduce the slope or significance of a dose response. Exposure estimates in studies of health risks from environmental radiation exposures are generally highly uncertain and thus, susceptible to these methodological limitations. An analysis was published in 2008 concerning radiation-related thyroid nodule prevalence in a study population of 2,994 villagers under the age of 21 years old between August 1949 and September 1962 and who lived downwind from the Semipalatinsk Nuclear Test Site in Kazakhstan. This dose-response analysis identified a statistically significant association between thyroid nodule prevalence and reconstructed doses of fallout-related internal and external radiation to the thyroid gland; however, the effects of dosimetric uncertainty were not evaluated since the doses were simple point "best estimates". In this work, we revised the 2008 study by a comprehensive treatment of dosimetric uncertainties. Our present analysis improves upon the previous study, specifically by accounting for shared and unshared uncertainties in dose estimation and risk analysis, and differs from the 2008 analysis in the following ways: 1. The study population size was reduced from 2,994 to 2,376 subjects, removing 618 persons with uncertain residence histories; 2. Simulation of multiple population dose sets (vectors) was performed using a two-dimensional Monte Carlo dose estimation method; and 3. A Bayesian model averaging approach was employed for evaluating the dose response, explicitly accounting for large and complex uncertainty in dose estimation. The results were compared against conventional regression techniques. The Bayesian approach utilizes 5,000 independent realizations of population dose vectors, each of which corresponds to a set of conditional individual median internal and external doses for the 2,376 subjects. These 5,000 population dose vectors reflect uncertainties in dosimetric parameters, partly shared and partly independent, among individual members of the study population. Risk estimates for thyroid nodules from internal irradiation were higher than those published in 2008, which results, to the best of our knowledge, from explicitly accounting for dose uncertainty. In contrast to earlier findings, the use of Bayesian methods led to the conclusion that the biological effectiveness for internal and external dose was similar. Estimates of excess relative risk per unit dose (ERR/Gy) for males (177 thyroid nodule cases) were almost 30 times those for females (571 cases) and were similar to those reported for thyroid cancers related to childhood exposures to external and internal sources in other studies. For confirmed cases of papillary thyroid cancers (3 in males, 18 in females), the ERR/Gy was also comparable to risk estimates from other studies, but not significantly different from zero. These findings represent the first reported dose response for a radiation epidemiologic study considering all known sources of shared and unshared errors in dose estimation and using a Bayesian model averaging (BMA) method for analysis of the dose response.
剂量测定的不确定性,尤其是那些在研究人群亚组中共同存在的不确定性,可能会使剂量反应的斜率产生偏差、扭曲或降低,或影响其显著性。在环境辐射暴露健康风险研究中,暴露估计通常具有高度不确定性,因此容易受到这些方法学限制的影响。2008年发表了一项分析,涉及1949年8月至1962年9月期间居住在哈萨克斯坦塞米巴拉金斯克核试验场下风向、年龄在21岁以下的2994名村民的研究人群中与辐射相关的甲状腺结节患病率。这项剂量反应分析确定了甲状腺结节患病率与重建的甲状腺相关沉降物内外辐射剂量之间存在统计学上的显著关联;然而,由于剂量是简单的点“最佳估计值”,因此未评估剂量测定不确定性的影响。在这项工作中,我们通过全面处理剂量测定不确定性对2008年的研究进行了修订。我们目前的分析在先前研究的基础上有所改进,具体而言是考虑了剂量估计和风险分析中的共同和非共同不确定性,并且在以下方面与2008年的分析有所不同:一是研究人群规模从2994人减少到2376人,排除了618名居住史不确定的人;二是使用二维蒙特卡罗剂量估计方法对多组人群剂量集(向量)进行了模拟;三是采用贝叶斯模型平均方法评估剂量反应,明确考虑了剂量估计中的巨大和复杂不确定性。并将结果与传统回归技术进行了比较。贝叶斯方法利用了5000个独立的人群剂量向量实现,每个实现对应于2376名受试者的一组条件个体中位内外剂量。这5000个人群剂量向量反映了研究人群个体成员之间剂量测定参数的不确定性,部分是共同的,部分是独立的。内部照射导致甲状腺结节的风险估计高于2008年发表的结果,据我们所知,这是因为明确考虑了剂量不确定性。与早期研究结果相反,使用贝叶斯方法得出的结论是,内部和外部剂量的生物学有效性相似。男性(177例甲状腺结节病例)每单位剂量的超额相对风险(ERR/Gy)估计值几乎是女性(571例)的30倍,与其他研究中报告的与儿童时期内外源暴露相关的甲状腺癌的估计值相似。对于确诊的乳头状甲状腺癌病例(男性3例,女性18例),ERR/Gy也与其他研究的风险估计值相当,但与零无显著差异。这些发现代表了首次报道的辐射流行病学研究的剂量反应,该研究考虑了剂量估计中所有已知的共同和非共同误差来源,并使用贝叶斯模型平均(BMA)方法分析剂量反应。