Estimating the relative risk of pancreatic cancer associated with exposure agents in job title data in a hierarchical Bayesian meta-analysis
Objectives The study demonstrates the application of a hierarchical Bayesian meta-analysis of epidemiologic studies that show an association between pancreatic cancer risk and job titles, using a job-exposure matrix to estimate risks for occupational exposure agents.
Methods Altogether 261 studies published from 1969 through 1998 on pancreatic cancer and job titles were identified. When proportional studies are excluded, 77 studies were informative for 9 selected occupational agents. These studies included more than 3799 observed pancreatic cancer cases. Hierarchical Bayesian models were used for job titles (lower-level data) and agents (higher-level data), the latter from a Finnish job-exposure matrix. Non-Bayesian random effects models were applied for job titles to check consistency with the Bayesian results.
Results The results suggest that occupational exposures to chlorinated hydrocarbon compounds may increase the risk of pancreatic cancer; the meta-relative risk (MRR) was 2.21 [95% credible interval (CrI) 1.31–3.68]. A suggestive weak excess was found for exposure to insecticides (MRR 1.95, 95% CrI 0.51–7.41).
Conclusions Hierarchical models are applicable in meta-analyses when studies addressing the agent(s) under study are lacking or are very few, but several studies address job titles with potential exposure to these agents. Hierarchical meta-analytic models involving durations and intensities of exposure to occupational agents from a job-exposure matrix should be developed.