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Document ID (ISN)111345
CIS number 11-0074
ISSN - Serial title 1745-6673 - Journal of Occupational Medicine and Toxicology
Year 2010
Convention or series no.
Author(s) Morfeld P., McCunney R.J.
Title Bayesian bias adjustments of the lung cancer SMR in a cohort of German carbon black production workers
Bibliographic information 2010, 5:23, 14p. Illus. 66 ref.
Internet access Bayesian_bias_adjustments.pdf [in English]
Abstract A German cohort study on 1,528 carbon black production workers estimated an elevated lung cancer SMR ranging from 1.8-2.2 depending on the reference population. No positive trends with carbon black exposures were noted in the analyses. A nested case control study, however, identified smoking and previous exposures to known carcinogens, such as crystalline silica, received prior to work in the carbon black industry as important risk factors. This study used a Bayesian procedure to adjust the SMR, based on seven independent parameter distributions describing smoking behaviour and crystalline silica dust exposure (as indicator of a group of correlated carcinogen exposures received previously) in the cohort and population as well as the strength of the relationship of these factors with lung cancer mortality. The Markov Chain Monte Carlo Methods (MCMC) was implemented. When putting a flat prior to the SMR a Markov chain of length 1,000,000 returned a median posterior SMR estimate (that is, the adjusted SMR) in the range between 1.32 and 1.00 depending on the method of assessing previous exposures. It is concluded that Bayesian bias adjustment is an excellent tool to effectively combine data about confounders from different sources. Quantitative bias adjustment should become a regular tool in occupational epidemiology.
Descriptors (primary) carbon black; mortality; evaluation of results; reliability; chemical industry; risk factors
Descriptors (secondary) Germany; silica; carcinogens; smoking; case-control study; confounding factors; cohort study; statistical evaluation; description of technique
Document type D - Periodical articles
Subject(s) Occupational pathology
Broad subject area(s) Chemical safety
Browse category(ies) Epidemiology
Statistical methods