Performance of methods for meta-analysis of diagnostic test accuracy with few studies or sparse data
Open Access
- 26 June 2015
- journal article
- research article
- Published by SAGE Publications in Statistical Methods in Medical Research
- Vol. 26 (4), 1896-1911
- https://doi.org/10.1177/0962280215592269
Abstract
Hierarchical models such as the bivariate and hierarchical summary receiver operating characteristic (HSROC) models are recommended for meta-analysis of test accuracy studies. These models are challenging to fit when there are few studies and/or sparse data (for example zero cells in contingency tables due to studies reporting 100% sensitivity or specificity); the models may not converge, or give unreliable parameter estimates. Using simulation, we investigated the performance of seven hierarchical models incorporating increasing simplifications in scenarios designed to replicate realistic situations for meta-analysis of test accuracy studies. Performance of the models was assessed in terms of estimability (percentage of meta-analyses that successfully converged and percentage where the between study correlation was estimable), bias, mean square error and coverage of the 95% confidence intervals. Our results indicate that simpler hierarchical models are valid in situations with few studies or sparse data. For synthesis of sensitivity and specificity, univariate random effects logistic regression models are appropriate when a bivariate model cannot be fitted. Alternatively, an HSROC model that assumes a symmetric SROC curve (by excluding the shape parameter) can be used if the HSROC model is the chosen meta-analytic approach. In the absence of heterogeneity, fixed effect equivalent of the models can be applied.Keywords
This publication has 28 references indexed in Scilit:
- Meta‐analysis of diagnostic test data: A bivariate Bayesian modeling approachStatistics in Medicine, 2010
- Bivariate Random Effects Meta-Analysis of Diagnostic Studies Using Generalized Linear Mixed ModelsMedical Decision Making, 2009
- Systematic Reviews of Diagnostic Test AccuracyAnnals of Internal Medicine, 2008
- An empirical comparison of methods for meta-analysis of diagnostic accuracy showed hierarchical models are necessaryJournal of Clinical Epidemiology, 2008
- Bivariate Random Effects Meta-Analysis of ROC CurvesMedical Decision Making, 2008
- Meta-Analysis of Diagnostic Studies: A Comparison of Random Intercept, Normal-Normal, and Binomial-Normal Bivariate Summary ROC ApproachesMedical Decision Making, 2008
- The binomial distribution of meta-analysis was preferred to model within-study variabilityJournal of Clinical Epidemiology, 2008
- Bivariate meta-analysis of sensitivity and specificity with sparse data: a generalized linear mixed model approachJournal of Clinical Epidemiology, 2006
- Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviewsJournal of Clinical Epidemiology, 2005
- A hierarchical regression approach to meta‐analysis of diagnostic test accuracy evaluationsStatistics in Medicine, 2001