title: Bayesian meta-analysis of Papanicolaou smear accuracy.
abstract: OBJECTIVE
  To perform a Bayesian analysis of data from a previous meta-analysis of Papanicolaou (Pap) smear accuracy (Fahey et al. Am J Epidemiol 1995; 141:680-689) and compare the results.
  
  
  METHODS
  We considered two Bayesian models for the same data set used in the Fahey et al. study. Model I was a beta-binomial model which considered the number of true positives and false negatives as independent binomial random variables with probability parameters beta (sensitivity) and alpha (one minus specificity), respectively. We assumed that beta and alpha are independent, each following a beta distribution with exponential priors. Model II considered sensitivity and specificity jointly through a bivariate normal distribution on the logits of the sensitivity and specificity. We performed sensitivity analysis to examine the effect of prior selection on the parameter estimates.
  
  
  RESULTS
  We compared the estimates of average sensitivity and specificity from the Bayesian models with those from Fahey et al.'s summary receiver operating characteristics (SROC) approach. Model I produced results similar to those of the SROC approach. Model II produced point estimates higher than those of the SROC approach, although the credible intervals overlapped and were wider. Sensitivity analysis showed that the Bayesian models are somewhat sensitive to the variance of the prior distribution, but their point estimates are more robust than those of the SROC approach.
  
  
  CONCLUSIONS
  The Bayesian approach has advantages over the SROC approach in that it accounts for between-study variation and allows for estimating the sensitivity and specificity for a particular trial, taking into consideration the results of other trials, i.e., "borrowing strength" from other trials.
authors.affiliation: Biometrics and Data Management, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut, USA.
authors.forename: Xiuyu
authors.initials: X
authors.lastname: Cong
authors.forename: Dennis D
authors.initials: DD
authors.lastname: Cox
authors.forename: Scott B
authors.initials: SB
authors.lastname: Cantor
mesh_terms: D001499:Bayes Theorem; D005260:Female; D006801:Humans; D065006:Papanicolaou Test; D012680:Sensitivity and Specificity; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis / Q000473:pathology*; D014626:Vaginal Smears / Q000592:standards*