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 dataset 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 β (sensitivity) and a (one minus specificity), respectively. We assumed that β and a 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 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-TheBayesian 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.

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