A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer

BMC Medical Research Methodology

Isabelle Stücker¹  Sylvia Richardson²  Lamiae Azizi³  Silvia Liverani²  David I Hastie⁴ 

[1]Université Paris-Sud, UMRS 1018, F-94807, Villejuif, France

[2]MRC Biostatistics Unit, Cambridge, UK

[3]Unite d’Epidemiologie Animale, INRA-Theix, Saint-Genès-Champanelle, France

[4]Imperial College, London, UK

关键词: Pack-years;    Duration;    Intensity;    Case control study;    Bayesian clustering;    Lung cancer;    Smoking;   

Others  :  866628
DOI  :  10.1186/1471-2288-13-129

 received in 2013-04-09, accepted in 2013-10-14,  发布年份 2013

【 摘 要 】

Background

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.

Methods

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.

Results

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.

Conclusions

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.

【 授权许可】

   
2013 Hastie et al.; licensee BioMed Central Ltd.

【 图 表 】

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