Modelling smoking history using a comprehensive smoking index: application to lung cancer

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Abstract
The mathematical representation of smoking history is an important tool in analysis of epidemiological and clinical data. Hoffmann and colleagues recently proposed a single aggregate measure of smoking exposure that incorporates intensity, duration, and time since cessation. This comprehensive smoking index (CSI), which may be incorporated in any regression model, depends on a half‐life (τ) and a lag (δ) parameters that have to be fixed a priori, or estimated by maximizing the fit. The CSI has not previously been used for analysis of cancer data. Following some preliminary results on smoking and lung cancer, the authors proposed a new version of the CSI for lung cancer. The aim of this study was to investigate the performance of the original and the new versions of the CSI in the analysis of three data sets from two case–control studies of lung cancer undertaken in Montreal, in 1979–1985 in males, and in 1996–2000 in both males and females. The estimates of τ and δ for both versions of the CSI were similar across data sets. The new version of the CSI fitted the three data sets systematically although moderately better than the original version, and at least as well as other representations of lifetime smoking history that used separate variables for time since cessation and cumulative amount of cigarettes smoked. The results suggest that the CSI may be an attractive and parsimonious alternative to conventional modelling of different aspects of smoking history for lung cancer. Copyright © 2006 John Wiley & Sons, Ltd.