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Reliable risk prediction tools for estimating individual probability of lung cancer have important public health implications. We constructed and validated a comprehensive clinical tool for lung cancer risk prediction by smoking status.

Epidemiologic data from 1851 lung cancer patients and 2001 matched control subjects were randomly divided into separate training (75% of the data) and validation (25% of the data) sets for never, former, and current smokers, and multivariable models were constructed from the training sets. The discriminatory ability of the models was assessed in the validation sets by examining the areas under the receiver operating characteristic curves and with concordance statistics. Absolute 1-year risks of lung cancer were computed using national incidence and mortality data. An ordinal risk index was constructed for each smoking …