A Comparison of Standard Methods With G-estimation of Accelerated Failure-time Models to Address The Healthy-worker Survivor Effect Application in a Cohort of Autoworkers Exposed to Metalworking Fluids
A Comparison of Standard Methods With G-estimation of Accelerated Failure-time Models to Address The Healthy-worker Survivor Effect Application in a Cohort of Autoworkers Exposed to Metalworking Fluids
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DOI：
10.1097/ede.0b013e318245fc06
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发表时间：
2012-03-01
期刊：
影响因子：
5.4
通讯作者：
Eisen, Ellen A.
中科院分区：
文献类型：
--
作者：
Chevrier, Jonathan;Picciotto, Sally;Eisen, Ellen A.
背景：研究表明，接触直金属加工液的汽车工人患几种癌症的风险过高。然而，这些研究并没有解决卫生工作者的幸存者效应。大多数提出的解决这种偏差的方法都没有考虑到它可能是由受先前暴露影响的时变混杂因素引起的。加速失效时间模型的g估计是为了处理这一问题而开发的，但从未用于解释卫生工作者幸存者效应。方法：我们比较了38,747名接触直金属加工液的汽车工人的Cox模型和g估计结果。暴露程度是根据工作记录和空气样本确定的。我们研究了暴露时间与各种原因死亡率、癌症、缺血性心脏病和慢性阻塞性肺疾病（COPD）之间的关系。结果：在标准模型中，喉癌、前列腺癌和直肠癌的风险比升高，但在考虑的所有其他结果中，风险比低于或近似等于1.0。利用休假时间、就业状况、受雇以来的时间以及15年后对不活动工人的限制来调整健康工作者幸存者效应并没有实质性地改变风险比。然而，对于大多数结果，g估计比标准Cox模型产生更高的风险比。暴露与各种原因导致的死亡风险增加有关，包括心脏病、慢性阻塞性肺病和所有癌症，以及肺癌和前列腺癌。结论：与标准方法相比，g估计法可以更好地控制卫生工作者的幸存者效应。
Background: Studies of autoworkers exposed to straight metalworking fluids report excess risks of several cancers. These studies, however, have not addressed the healthy-worker survivor effect. Most methods proposed to address this bias do not consider that it may be caused by time-varying confounders affected by prior exposure. G-estimation of accelerated failure-time models was developed to handle this issue but has never been applied to account for the healthy-worker survivor effect.Methods: We compare results from Cox models and g-estimation in 38,747 autoworkers exposed to straight metalworking fluids. Exposure was defined based on job records and air samples. We examine relationships between duration of exposure and mortality from all causes, cancers, ischemic heart disease, and chronic obstructive pulmonary disease (COPD).Results: In standard models, hazard ratios were elevated for cancers of the larynx, prostate, and rectum, but below or approximately equal to 1.0 for all other outcomes considered. Adjustment for the healthy-worker survivor effect using time off work, employment status, time since hire, and restriction to inactive workers after 15 years of follow-up did not substantially change the hazard ratios. However, g-estimation yielded higher hazard ratios than standard Cox models for most outcomes. Exposure was related to increased risks of mortality from all causes combined, heart disease, COPD, and all cancers, as well as lung and prostate cancers.Conclusions: G-estimation may provide a better control for the healthy-worker survivor effect than standard methods.