title: Independent validation test of the vote-counting strategy used to rank biomarkers from published studies.
abstract: OBJECTIVE
  Vote counting is frequently used in meta-analyses to rank biomarker candidates, but to our knowledge, there have been no independent assessments of its validity. Here, we used predictions from a recent meta-analysis to determine how well number of supporting studies, combined sample size and mean fold change performed as vote-counting strategy criteria.
  
  
  METHODS
  Fifty miRNAs previously ranked for their ability to distinguish lung cancer tissue from normal were assayed by RT-qPCR using 45 paired tumor-normal samples.
  
  
  RESULTS
  Number of supporting studies predicted biomarker performance (p = 0.0006; r = 0.44), but sample size and fold change did not (p > 0.2).
  
  
  CONCLUSIONS
  Despite limitations, counting the number supporting studies appears to be an effective criterion for ranking biomarkers. Predictions based on sample size and fold change provided little added value. External validation studies should be conducted to establish the performance characteristics of strategies used to rank biomarkers.
authors.affiliation: Division of Medical Oncology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
authors.forename: Brad A
authors.initials: BA
authors.lastname: Rikke
authors.affiliation: Division of Medical Oncology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
authors.forename: Murry W
authors.initials: MW
authors.lastname: Wynes
authors.affiliation: Division of Medical Oncology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
authors.forename: Leslie M
authors.initials: LM
authors.lastname: Rozeboom
authors.affiliation: Department of Biostatistics & Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
authors.forename: Anna E
authors.initials: AE
authors.lastname: Barón
authors.affiliation: Division of Medical Oncology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.|Department of Pathology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
authors.forename: Fred R
authors.initials: FR
authors.lastname: Hirsch
mesh_terms: D000230:Adenocarcinoma / Q000175:diagnosis / Q000235:genetics*; D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics*; D002289:Carcinoma, Non-Small-Cell Lung / Q000175:diagnosis / Q000235:genetics*; D002294:Carcinoma, Squamous Cell / Q000175:diagnosis / Q000235:genetics*; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis / Q000235:genetics*; D008297:Male; D015201:Meta-Analysis as Topic; D035683:MicroRNAs / Q000235:genetics*; D008875:Middle Aged; D015203:Reproducibility of Results; D020133:Reverse Transcriptase Polymerase Chain Reaction; D018401:Sample Size; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D035683:MicroRNAs
keywords: biomarkers; lung cancer; meta-analysis; miRNAs; microRNAs; statistical methods