title: False positive outcomes and design characteristics in occupational cancer epidemiology studies.
abstract: BACKGROUND
  Recently there has been considerable debate about possible false positive study outcomes. Several well-known epidemiologists have expressed their concern and the possibility that epidemiological research may loose credibility with policy makers as well as the general public.
  
  
  METHODS
  We have identified 75 false positive studies and 150 true positive studies, all published reports and all epidemiological studies reporting results on substances or work processes generally recognized as being carcinogenic to humans. All studies were scored on a number of design characteristics and factors relating to the specificity of the research objective. These factors included type of study design, use of cancer registry data, adjustment for smoking and other factors, availability of exposure data, dose- and duration-effect relationship, magnitude of the reported relative risk, whether the study was considered a 'fishing expedition', affiliation and country of the first author.
  
  
  RESULTS
  The strongest factor associated with the false positive or true positive study outcome was if the study had a specific a priori hypothesis. Fishing expeditions had an over threefold odds ratio of being false positive. Factors that decreased the odds ratio of a false positive outcome included observing a dose-effect relationship, adjusting for smoking and not using cancer registry data.
  
  
  CONCLUSIONS
  The results of the analysis reported here clearly indicate that a study with a specific a priori study objective should be valued more highly in establishing a causal link between exposure and effect than a mere fishing expedition.
authors.affiliation: Department of Epidemiology, University of Maastricht, The Netherlands. g.swaen@epid.unimaas.nl
authors.forename: G G
authors.initials: GG
authors.lastname: Swaen
authors.forename: O
authors.initials: O
authors.lastname: Teggeler
authors.forename: L G
authors.initials: LG
authors.lastname: van Amelsvoort
mesh_terms: D015982:Bias; D015984:Causality; D016001:Confidence Intervals; D015340:Epidemiologic Research Design; D006801:Humans; D016015:Logistic Models; D009369:Neoplasms / Q000453:epidemiology*; D009784:Occupational Diseases / Q000453:epidemiology*; D016017:Odds Ratio; D012307:Risk Factors