Statistical methods for analyzing effects of temporal patterns of exposure on cancer risks.

Two approaches to the inclusion of temporal factors in the analysis of exposure-response relations are compared: multivariate logistic analysis incorporating simple exposure indices, together with additional temporal variables and their interactions, and direct fitting to models of the disease process.

Abstract

Two approaches to the inclusion of temporal factors in the analysis of exposure-response relations are compared: (i) multivariate logistic analysis incorporating simple exposure indices, together with additional temporal variables and their interactions, and (ii) direct fitting to models of the disease process. These approaches are illustrated on case-referent data relating lung cancer to asbestos and smoking. From approach i average age at exposure, age at risk, and duration of exposure were found to contribute direct or interaction effects. Two models of carcinogenesis were fit. In a two-stage initiation-latency model the median latency period was estimated at 11.0 years overall, but was somewhat longer for asbestos-induced and shorter for smoking-induced tumors. When this difference was allowed for, latency periods seemed to be inversely related to the average intensities of both asbestos and smoking. In the multistage model, the best fit was obtained with asbestos acting at the fourth and smoking at the fifth of six stages. Lifetime risks of lung cancer are projected under the different models.