Literature DB >> 16410261

Analysis of epidemiological cohort data on smoking effects and lung cancer with a multi-stage cancer model.

H Schöllnberger1, M Manuguerra, H Bijwaard, H Boshuizen, H P Altenburg, S M Rispens, M J P Brugmans, P Vineis.   

Abstract

A stochastic two-stage cancer model is used to analyse the relation between lung cancer and cigarette smoking. The model contains the main rate-limiting stages of carcinogenesis, which include initiation, promotion (clonal expansion of initiated cells), malignant transformation and a lag time for tumour formation. Various data sets were used to test the model. These include the data of a large prospective collaborative project carried out in 10 different European countries, the European Prospective Investigation into Cancer and Nutrition (EPIC). This new data set has not been modelled before. The model is also tested on other published data from CPS-II (Cancer Prevention Study II) of the American Cancer Society and the British doctors' study. The analyses indicate that the EPIC data are best described with smoking dependence on the rates of malignant transformation and clonal expansion. With increasing smoking rates, saturation effects in the two exposure rate-dependent model parameters were observed. The results find confirmation in the biological literature, where both mutational effects and promotional effects of cigarette smoke are documented.

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Year:  2006        PMID: 16410261      PMCID: PMC3085129          DOI: 10.1093/carcin/bgi345

Source DB:  PubMed          Journal:  Carcinogenesis        ISSN: 0143-3334            Impact factor:   4.944


  60 in total

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8.  Mutation and cancer: statistical study of retinoblastoma.

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Authors:  P ARMITAGE; R DOLL
Journal:  Br J Cancer       Date:  1957-06       Impact factor: 7.640

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  15 in total

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Review 4.  Models of carcinogenesis: an overview.

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5.  Dose-responses from multi-model inference for the non-cancer disease mortality of atomic bomb survivors.

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7.  Comparative analysis of 5 lung cancer natural history and screening models that reproduce outcomes of the NLST and PLCO trials.

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8.  Estimation of the effects of smoking and DNA repair capacity on coefficients of a carcinogenesis model for lung cancer.

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9.  Small suitability of the DLEC1, MLH1 and TUSC4 mRNA expression analysis as potential prognostic or differentiating markers for NSCLC patients in the Polish population.

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Review 10.  Tumor heterogeneity: mechanisms and bases for a reliable application of molecular marker design.

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