Abstract Quality of life is a central concern in medicine. Thus estimation of the number of years of life free of some disease lost due to an occupational exposure is frequently required. The amount of compensation due to the worker relies upon this estimation. The motivating example is a French case-control study on the occurrence of lung cancer for workers exposed to asbestos (J.C. Pairon et al, 2009)[4]. For a case-control study the most usual model is the logistic. Several models, though, can be used in order to solve our problem. One of the simplest is the Cox model involving the occupational exposure as a covariate at the same level as other risk factors that could also induce lung cancer, like for example family history of cancer and tobacco consumption. But we can also treat differently the occupational exposure and the other covariates : we adapt to case-control study (A. Chambaz et al. 2013 [1]) the threshold regression (TR) model, also named first hitting time model (FHT), which was initially developed for cohort studies. This model allows us to treat the occupational exposure as an accelerator of the time to onset of the disease, while the other covariates are divided into two classes, acting differently on the time to onset: the built-in ones (like genetic factors for example) and the lifelong ones (like tobacco consumption for example). The time T of occurrence of the disease is modeled thanks to a stochastic process that represents the amount of health of the subject at time t : the disease occurs when this amount of health hits the boundary 0 for the first time. Considering that, actually, the covariates are not all of the same kind, we use the first hitting time model.