Abstract : Abstract
Quality of life is a central concern in medicine. Thus estimation of the number of ex-pected 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 was a French case-cohort study on the occurrence of lung cancer for workers exposed to asbestos (J.C. Pairon et al, 2009). For a case-cohort study the most usual models are the logistic ones. But this is adequate only if the aim is to evaluate the
risks of developing the disease, which is not our objective. Several models, though, can be used in order to solve our problem. One of the simplest and most frequently used model 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 think of adapting to case-control
study the threshold regression model, also named first hitting time model (fht), which was initially developed for cohort studies. This model allows us to treat the professional 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).
Moreover, as is now well ackowledged for, survival data analysis in medicine can be applied to industrial reliability assessment, so that the methods described here can be adapted to industrial complex systems.