Multistage carcinogenesis: Impact of age, genetic, and environmental factors on the incidence of malignant mesothelioma.

The current paradigm of carcinogenesis as a cellular evolutionary process driven by mutations of a few critical driver genes has immediate logical implications for the epidemiology of cancer. These include the impact of age on cancer risk, the role played by inherited tumor predisposition syndromes, and the interaction of genetics and environmental exposures on cancer risk. In this paper, we explore the following logical epidemiological consequences of carcinogenesis as a clonal process of mutation accumulation, with special emphasis on asbestos-related cancers, specifically malignant mesothelioma:1 All cancers, including mesothelioma, can and do occur spontaneously, i.

Mechanisms and shapes of causal exposure-response functions for asbestos in mesotheliomas and lung cancers.

This paper summarizes recent insights into causal biological mechanisms underlying the carcinogenicity of asbestos. It addresses their implications for the shapes of exposure-response curves and considers recent epidemiologic trends in malignant mesotheliomas (MMs) and lung fiber burden studies. Since the commercial amphiboles crocidolite and amosite pose the highest risk of MMs and contain high levels of iron, endogenous and exogenous pathways of iron injury and repair are discussed.

Comments on a recent case-control study of malignant mesothelioma of the pericardium and the tunica vaginalis testis.

As the first case-control study of malignant mesothelioma of the pericardium and the tunica vaginalis testis (mTVT), the paper by Marinaccio et al (1) is potentially an important epidemiologic contribution. A careful review of the paper, however, raises a number of methodological issues. Any case-control study can be viewed as being nested within a conceptual cohort, with controls being sampled from the at-risk cohort as cases arise over time.

Smoking, air pollution, and lung cancer risk in the Nurses' Health Study cohort: time-dependent confounding and effect modification.

The proportional hazards (PH) model is commonly used in epidemiology despite the stringent assumption of proportionality of hazards over time. We previously showed, using detailed simulation data, that the impact of a modest risk factor cannot be estimated reliably using the PH model in the presence of confounding by a strong, time-dependent risk factor. Here, we examine the same and related issues using a real dataset.