title: Application of credibility ceilings probes the robustness of meta-analyses of biomarkers and cancer risk.
abstract: OBJECTIVE
  Meta-analyses of biomarkers often present spurious significant results and large effects. We applied sensitivity analyses with the use of credibility ceilings to assess whether and how the results of meta-analyses of biomarkers and cancer risk would change.
  
  
  METHODS
  We evaluated 98 meta-analyses, 43 (44%) of which had nominally statistically significant results. We assumed that any single study cannot give more than a maximum certainty 100 - c% (c, credibility ceiling) that the effect estimate [odds ratio (OR)] exceeds 1 (null) or 1.2.
  
  
  RESULTS
  Nominal statistical significance was maintained for 21 (21%) meta-analyses, for c = 10% and OR >1, and these proportions changed to 7%, 3%, and 6% with ceilings of 20%, 30%, and 40%, respectively. For ceilings for OR >1.2, the respective proportions were 37%, 21%, 7%, and 3%. Seven meta-analyses on infectious agents retained statistical significance even with a high ceiling of c = 20% for OR >1.00. Meta-analyses without other hints of bias (large between-study heterogeneity, small-study effects, excess significance) were more likely to retain statistical significance than those that had such hints of bias.
  
  
  CONCLUSIONS
  Credibility ceilings may be helpful in meta-analyses of biomarkers to understand the robustness of the results to different levels of uncertainty.
authors.affiliation: Department of Health Sciences, Cyprus Institute for Environmental and Public Health, Cyprus University of Technology, Eirinis 95 Str, 3041, Limassol, Cyprus.
authors.forename: Stefania I
authors.initials: SI
authors.lastname: Papatheodorou
authors.affiliation: Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, University Campus, 45110 Ioannina, Greece.
authors.forename: Konstantinos K
authors.initials: KK
authors.lastname: Tsilidis
authors.affiliation: Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, University Campus, 45110 Ioannina, Greece.
authors.forename: Evangelos
authors.initials: E
authors.lastname: Evangelou
authors.affiliation: Stanford Prevention Research Center, Department of Medicine, Stanford University School of Medicine, Stanford 94305, CA, USA; Department of Health Research and Policy, Stanford University School of Medicine, Stanford 94305, CA, USA; Department of Statistics, Stanford University School of Humanities and Sciences, Stanford 94305, CA, USA. Electronic address: jioannid@stanford.edu.
authors.forename: John P A
authors.initials: JP
authors.lastname: Ioannidis
mesh_terms: D015982:Bias; D014408:Biomarkers, Tumor / Q000032:analysis*; D002986:Clinical Trials as Topic / Q000592:standards; D015986:Confounding Factors, Epidemiologic; D003627:Data Interpretation, Statistical; D006801:Humans; D015201:Meta-Analysis as Topic; D009369:Neoplasms / Q000737:chemistry* / Q000453:epidemiology; D016017:Odds Ratio; D012107:Research Design; D012307:Risk Factors; D015983:Selection Bias
chemical_list: D014408:Biomarkers, Tumor
keywords: Biomarkers; Cancer; Credibility ceiling; Meta-analyses; Predictive intervals