Threshold regression methodology has demonstrated its value in studies of cancer studies and occupational risk. The methodology is based on the concept that health degradation follows a stochastic process and death occurs when the latent health process first reaches a failure state or threshold (a first hitting time). The model is intuitive and generally does not require the proportional hazards assumption and thus provides an important alternative for analyzing time-to-event data. Using the Nurses Health Study, we will discuss applications of this model to assess the effect of smoking on lung cancer. Also, using the US railroad workers’ data, we will discuss the effect of diesel exhaust on lung cancer.