title: Cochran's Q test was useful to assess heterogeneity in likelihood ratios in studies of diagnostic accuracy.
abstract: OBJECTIVE
  Empirical evaluations have demonstrated that diagnostic accuracy frequently shows significant heterogeneity between subgroups of patients within a study. We propose to use Cochran's Q test to assess heterogeneity in diagnostic likelihood ratios (LRs).
  
  
  METHODS
  We reanalyzed published data of six articles that showed within-study heterogeneity in diagnostic accuracy. We used the Q test to assess heterogeneity in LRs and compared the results of the Q test with those obtained using another method for stratified analysis of LRs, based on subgroup confidence intervals. We also studied the behavior of the Q test using hypothetical data.
  
  
  RESULTS
  The Q test detected significant heterogeneity in LRs in all six example data sets. The Q test detected significant heterogeneity in LRs more frequently than the confidence interval approach (38% vs. 20%). When applied to hypothetical data, the Q test would be able to detect relatively small variations in LRs, of about a twofold increase, in a study including 300 participants.
  
  
  CONCLUSIONS
  Reanalysis of published data using the Q test can be easily performed to assess heterogeneity in diagnostic LRs between subgroups of patients, potentially providing important information to clinicians who base their decisions on published LRs.
authors.affiliation: INSERM U1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team, Center for Epidemiology and Biostatistics Sorbonne Paris Cité (CRESS), Paris Descartes University, 53, avenue de l'Observatoire, 75014 Paris, France; Department of Pediatrics, Necker-Enfants Malades Hospital, Assistance Publique-Hôpitaux de Paris, Paris Descartes University, 149, rue de Sèvres, 75015 Paris, France; Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, The Netherlands. Electronic address: jeremie.cohen@inserm.fr.
authors.forename: Jérémie F
authors.initials: JF
authors.lastname: Cohen
authors.affiliation: INSERM U1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team, Center for Epidemiology and Biostatistics Sorbonne Paris Cité (CRESS), Paris Descartes University, 53, avenue de l'Observatoire, 75014 Paris, France; Department of Pediatrics, Necker-Enfants Malades Hospital, Assistance Publique-Hôpitaux de Paris, Paris Descartes University, 149, rue de Sèvres, 75015 Paris, France.
authors.forename: Martin
authors.initials: M
authors.lastname: Chalumeau
authors.affiliation: Association Clinique et Thérapeutique Infantile du Val-de-Marne (ACTIV), 27, rue d'Inkermann, 94100 Saint-Maur-des-Fossés, France; Unité Court Séjour Nourrissons, Centre Hospitalier Intercommunal de Créteil, 40, avenue de Verdun, 94000 Créteil, France.
authors.forename: Robert
authors.initials: R
authors.lastname: Cohen
authors.affiliation: Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, The Netherlands.
authors.forename: Daniël A
authors.initials: DA
authors.lastname: Korevaar
authors.affiliation: INSERM U1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team, Center for Epidemiology and Biostatistics Sorbonne Paris Cité (CRESS), Paris Descartes University, 53, avenue de l'Observatoire, 75014 Paris, France.
authors.forename: Babak
authors.initials: B
authors.lastname: Khoshnood
authors.affiliation: Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, The Netherlands.
authors.forename: Patrick M M
authors.initials: PM
authors.lastname: Bossuyt
mesh_terms: D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D019937:Diagnostic Techniques and Procedures / Q000592:standards* / Q000706:statistics & numerical data; D006305:Health Status Indicators; D006801:Humans; D016013:Likelihood Functions; D015201:Meta-Analysis as Topic; D011237:Predictive Value of Tests
keywords: Bayes theorem; Data interpretation, statistical; Diagnostic techniques and procedures/statistics and numerical data; Likelihood functions; Predictive value of tests; Sensitivity and specificity