title: Comparison of exposure assessment methods for occupational carcinogens in a multi-centre lung cancer case-control study.
abstract: OBJECTIVE
  Retrospective exposure assessment remains a problematic aspect of population-based case-control studies. Different methods have been developed, including case-by-case expert assessment and job-exposure matrices (JEM). The present analyses compare exposure prevalence and risk estimates derived by different exposure assessment methods.
  
  
  METHODS
  In the context of a case-control study conducted in seven European countries, exposure was estimated for asbestos, diesel motor emissions (DME) and crystalline silica, using three different assessment methods. First, experts assigned exposures to all reported jobs on a case-by-case basis. Second, a population-specific JEM (PSJEM) was developed using the expert assessments of controls only, and re-applied to all study subjects. Third, an independent general population JEM (GPJEM) was created by occupational exposure experts not involved in the original study, and applied to study subjects. Results from these methods were compared.
  
  
  RESULTS
  There was poor to fair agreement in assigned exposure between expert assessment and the GPJEM (kappas: asbestos 0.17; DME 0.48; silica 0.38). Exposure prevalence was significantly heterogeneous (p<0.01) between countries for all three agents and assessment methods. For asbestos and DME, significant country heterogeneity in risk estimates was observed when using expert assessment. When applying the GPJEM, the heterogeneity in risk estimates for asbestos and, to some extent, silica diminished.
  
  
  CONCLUSIONS
  It has been previously advocated that the expert assessment approach to assign exposures based on detailed questionnaire responses provides more accurate exposure estimates than JEM-based results. However, current results demonstrated little, if any, advantage of case-by-case assessment when compared to a JEM approach.
authors.affiliation: Institute for Risk Assessment Sciences, Environmental Epidemiology Division, Utrecht University, Utrecht, The Netherlands. s.peters@uu.nl
authors.forename: Susan
authors.initials: S
authors.lastname: Peters
authors.forename: Roel
authors.initials: R
authors.lastname: Vermeulen
authors.forename: Adrian
authors.initials: A
authors.lastname: Cassidy
authors.forename: Andrea 't
authors.initials: A'
authors.lastname: Mannetje
authors.forename: Martie
authors.initials: M
authors.lastname: van Tongeren
authors.forename: Paolo
authors.initials: P
authors.lastname: Boffetta
authors.forename: Kurt
authors.initials: K
authors.lastname: Straif
authors.forename: Hans
authors.initials: H
authors.lastname: Kromhout
mesh_terms: D000368:Aged; D001194:Asbestos / Q000633:toxicity; D002273:Carcinogens / Q000633:toxicity*; D004812:Epidemiologic Methods; D005060:Europe / Q000453:epidemiology; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000139:chemically induced* / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D009784:Occupational Diseases / Q000139:chemically induced* / Q000453:epidemiology; D016273:Occupational Exposure / Q000009:adverse effects / Q000032:analysis* / Q000706:statistics & numerical data; D012822:Silicon Dioxide / Q000633:toxicity; D001335:Vehicle Emissions / Q000633:toxicity
chemical_list: D002273:Carcinogens; D001335:Vehicle Emissions; D001194:Asbestos; D012822:Silicon Dioxide