Oak Ridge Associated Universities, Oak Ridge, TN, USA.
EpidStat Institute, Ann Arbor, MI, USA.
Int J Radiat Biol. 2022;98(4):572-579. doi: 10.1080/09553002.2018.1554924. Epub 2019 Jan 7.
A substantial body of epidemiologic literature addresses risks associated with occupational radiation exposure but comparing results between studies is often difficult as different statistical models are commonly used. It is unclear whether different methods produce similar results for estimates of radiation risk when applied to the same data. The goal of this study was to compare the radiation risk estimates for leukemia other than chronic lymphocytic leukemia (non-CLL) and ischemic heart disease (IHD) produced by both Cox and Poisson regression models for time-dependent dose-response analyses of occupational exposure.
For brevity, this methods paper presents the results from one cohort, the Nuclear Power Plant workers (NPP), though the evaluation considered five cohorts of varying size and exposure as part of the Million Worker Study. Cox Proportional Hazards models, with age as the underlying timescale for hazard, were conducted using three computer software programs: SAS, R, and Epicure. Doses lagged 2 years for non-CLL and 10 years for ischemic heart disease were treated as time-dependent exposures at the annual level and were examined both in categories and as a continuous term. Hazard ratios (HR) and 95% confidence intervals (CI) were reported for each model in SAS and R, while the Peanuts program of Epicure was utilized to produce Excess Relative Risk (ERR) estimates and 95% CI. All models were adjusted for gender and year of birth. Four piece-wise exponential Poisson models (log-linear regression for rate) were developed with varying cutpoints for age strata from very fine to broad categories using both R and the Amfit program in Epicure for ERR estimates.
Comparable estimates of risk (both RR and ERR) were observed from Cox and Poisson models, regardless of software utilized, as long as appropriately narrow categories of age were utilized to control the confounding of age in Poisson models. The ERR estimates produced in Epicure tended to agree very closely with the HR or RR estimates, and the statistical software program used had no impact to risk estimates for the same model.
As computational power is no longer the burden today as it has been in the past, the results of this evaluation support the use of the Cox proportional hazards or the ungrouped Poisson approach to analyzing time-dependent dose-response relationships to ensure that maximum control over the confounding of age is achieved in studies of mortality for cohorts occupationally exposed to radiation.
大量流行病学文献探讨了与职业辐射暴露相关的风险，但由于通常使用不同的统计模型，因此比较研究结果往往较为困难。目前尚不清楚在应用于相同数据时，不同方法对于辐射风险估计是否会产生相似的结果。本研究的目的是比较应用于职业暴露时间依赖性剂量-反应分析的 Cox 和 Poisson 回归模型对除慢性淋巴细胞白血病（非 CLL）以外的白血病和缺血性心脏病（IHD）的辐射风险估计值。
为简洁起见，本方法论文仅呈现了一个队列的结果，即核电站工作人员（NPP），尽管该评估考虑了五个不同规模和暴露程度的队列，作为百万工人研究的一部分。Cox 比例风险模型使用三种计算机软件程序（SAS、R 和 Epicure）进行，年龄作为危险的基本时间尺度。非 CLL 风险滞后 2 年，缺血性心脏病风险滞后 10 年，作为每年的时间依赖性暴露进行处理，并分别在类别和连续项中进行了检查。每个模型在 SAS 和 R 中报告了危险比（HR）和 95%置信区间（CI），而 Epicure 的 Peanuts 程序则用于生成超额相对风险（ERR）估计值和 95%CI。所有模型均按性别和出生年份进行调整。使用 R 和 Epicure 中的 Amfit 程序开发了四个分段指数 Poisson 模型（对数线性回归率），年龄分层的切点范围从非常细到非常宽，用于 ERR 估计。
只要使用适当狭窄的年龄类别来控制 Poisson 模型中年龄的混杂，就可以从 Cox 和 Poisson 模型中观察到风险（RR 和 ERR）的可比估计值，无论使用哪种软件。在 Epicure 中生成的 ERR 估计值与 HR 或 RR 估计值非常吻合，并且使用的统计软件程序对同一模型的风险估计值没有影响。
由于当今的计算能力不再像过去那样成为负担，因此该评估结果支持使用 Cox 比例风险或未分组 Poisson 方法来分析时间依赖性剂量-反应关系，以确保在研究职业辐射暴露队列的死亡率时，对年龄的混杂因素进行最大控制。
