A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer.
A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer.
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DOI：
10.1186/1471-2288-13-129
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发表时间：
2013-10-23
影响因子：
4
通讯作者：
Stücker I
中科院分区：
文献类型：
--
作者：
Hastie DI;Liverani S;Azizi L;Richardson S;Stücker I
环境流行病学的一个共同特点是接触模式的多维度方面，为了简化分析，经常简化为累积接触。通过采用灵活的贝叶斯聚类方法，我们探讨了风险函数联系暴露史的疾病。本文采用病例对照研究的方法，探讨不同吸烟特征与肺癌的关系。我们的研究包括4658名男性（1995例，2663例对照），他们有完整的吸烟史（强度，持续时间，戒烟时间，包年），来自2001-2007年进行的ICARE多中心研究。我们扩展贝叶斯聚类技术，探索预测风险面的协变量配置文件的利益。我们能够将人群划分为12个具有不同吸烟特征和肺癌风险的聚类。我们的研究结果证实，与强度相比，持续时间是风险的主要驱动因素。另一方面，使用包年吸烟作为一个单一的总结导致相当大的信息损失。我们的方法通过稳健地考虑暴露的不同维度来估计与特定暴露特征相关的疾病风险，并且通常有助于进一步了解通过不同时间模式积累的暴露的影响。
A common characteristic of environmental epidemiology is the multi-dimensional aspect of exposure patterns, frequently reduced to a cumulative exposure for simplicity of analysis. By adopting a flexible Bayesian clustering approach, we explore the risk function linking exposure history to disease. This approach is applied here to study the relationship between different smoking characteristics and lung cancer in the framework of a population based case control study. Our study includes 4658 males (1995 cases, 2663 controls) with full smoking history (intensity, duration, time since cessation, pack-years) from the ICARE multi-centre study conducted from 2001-2007. We extend Bayesian clustering techniques to explore predictive risk surfaces for covariate profiles of interest. We were able to partition the population into 12 clusters with different smoking profiles and lung cancer risk. Our results confirm that when compared to intensity, duration is the predominant driver of risk. On the other hand, using pack-years of cigarette smoking as a single summary leads to a considerable loss of information. Our method estimates a disease risk associated to a specific exposure profile by robustly accounting for the different dimensions of exposure and will be helpful in general to give further insight into the effect of exposures that are accumulated through different time patterns.
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影响因子：
4.5
作者：
Luce D;Stücker I;ICARE Study Group
通讯作者：
ICARE Study Group
影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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作者：
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通讯作者：
ANTONIAK, CE
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作者：
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