The use of sliding time windows for the exploratory analysis of temporal effects of smoking histories on lung cancer risk

To examine the time-dependent effects of exposure histories on disease we u se sliding time windows as an exploratory alternative to the analysis of va riables like time since last exposure and duration of exposure. The method fits a series of risk models which contain total cumulative exposure and an additional covariate for exposures received during fixed time intervals. C haracteristics of the fitted models provide insight into the influence of e xposure increments at different times on disease risk. A simulation study i s performed to check the validity of the approach. We apply the method to d ata from a recent German case-control study on smoking and lung cancer risk with about 4300 lung cancer cases and a similiar number of controls. The s liding time window approach indicates that the amount of cigarettes smoked from two to 11 years before disease incidence is most predicitive of lung c ancer incidence. Among different smoking profiles that result in the same l ifelong cumulative number of cigarettes smoked, those with a concentration of smoked cigarettes within 20 years before interview bear substantially la rger risk than others. Copyright (C) 2000 John Wiley & Sons, Ltd.