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      Systematic Review and Meta-Analysis of Studies Evaluating Diagnostic Test Accuracy: A Practical Review for Clinical Researchers-Part II. Statistical Methods of Meta-Analysis

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          Abstract

          Meta-analysis of diagnostic test accuracy studies differs from the usual meta-analysis of therapeutic/interventional studies in that, it is required to simultaneously analyze a pair of two outcome measures such as sensitivity and specificity, instead of a single outcome. Since sensitivity and specificity are generally inversely correlated and could be affected by a threshold effect, more sophisticated statistical methods are required for the meta-analysis of diagnostic test accuracy. Hierarchical models including the bivariate model and the hierarchical summary receiver operating characteristic model are increasingly being accepted as standard methods for meta-analysis of diagnostic test accuracy studies. We provide a conceptual review of statistical methods currently used and recommended for meta-analysis of diagnostic test accuracy studies. This article could serve as a methodological reference for those who perform systematic review and meta-analysis of diagnostic test accuracy studies.

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          • Record: found
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          Meta-DiSc: a software for meta-analysis of test accuracy data

          Javier Zamora, Víctor Abraira, Alfonso Muriel … (2006)
          Background Systematic reviews and meta-analyses of test accuracy studies are increasingly being recognised as central in guiding clinical practice. However, there is currently no dedicated and comprehensive software for meta-analysis of diagnostic data. In this article, we present Meta-DiSc, a Windows-based, user-friendly, freely available (for academic use) software that we have developed, piloted, and validated to perform diagnostic meta-analysis. Results Meta-DiSc a) allows exploration of heterogeneity, with a variety of statistics including chi-square, I-squared and Spearman correlation tests, b) implements meta-regression techniques to explore the relationships between study characteristics and accuracy estimates, c) performs statistical pooling of sensitivities, specificities, likelihood ratios and diagnostic odds ratios using fixed and random effects models, both overall and in subgroups and d) produces high quality figures, including forest plots and summary receiver operating characteristic curves that can be exported for use in manuscripts for publication. All computational algorithms have been validated through comparison with different statistical tools and published meta-analyses. Meta-DiSc has a Graphical User Interface with roll-down menus, dialog boxes, and online help facilities. Conclusion Meta-DiSc is a comprehensive and dedicated test accuracy meta-analysis software. It has already been used and cited in several meta-analyses published in high-ranking journals. The software is publicly available at .
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            Combining independent studies of a diagnostic test into a summary ROC curve: data-analytic approaches and some additional considerations.

            L E Moses, D. Shapiro, B Littenberg (1993)
            We consider how to combine several independent studies of the same diagnostic test, where each study reports an estimated false positive rate (FPR) and an estimated true positive rate (TPR). We propose constructing a summary receiver operating characteristic (ROC) curve by the following steps. (i) Convert each FPR to its logistic transform U and each TPR to its logistic transform V after increasing each observed frequency by adding 1/2. (ii) For each study calculate D = V - U, which is the log odds ratio of TPR and FPR, and S = V + U, an implied function of test threshold; then plot each study's point (Si, Di). (iii) Fit a robust-resistant regression line to these points (or an equally weighted least-squares regression line), with V - U as the dependent variable. (iv) Back-transform the line to ROC space. To avoid model-dependent extrapolation from irrelevant regions of ROC space we propose defining a priori a value of FPR so large that the test simply would not be used at that FPR, and a value of TPR so low that the test would not be used at that TPR. Then (a) only data points lying in the thus defined north-west rectangle of the unit square are used in the data analysis, and (b) the estimated summary ROC is depicted only within that subregion of the unit square. We illustrate the methods using simulated and real data sets, and we point to ways of comparing different tests and of taking into account the effects of covariates.
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              A unification of models for meta-analysis of diagnostic accuracy studies.

              Roger Harbord, Jonathan J. Deeks, Matthias Egger … (2007)
              Studies of diagnostic accuracy require more sophisticated methods for their meta-analysis than studies of therapeutic interventions. A number of different, and apparently divergent, methods for meta-analysis of diagnostic studies have been proposed, including two alternative approaches that are statistically rigorous and allow for between-study variability: the hierarchical summary receiver operating characteristic (ROC) model (Rutter and Gatsonis, 2001) and bivariate random-effects meta-analysis (van Houwelingen and others, 1993), (van Houwelingen and others, 2002), (Reitsma and others, 2005). We show that these two models are very closely related, and define the circumstances in which they are identical. We discuss the different forms of summary model output suggested by the two approaches, including summary ROC curves, summary points, confidence regions, and prediction regions.
              Article 0 comments Cited 177 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Korean J Radiol
                Journal ID (iso-abbrev): Korean J Radiol
                Journal ID (publisher-id): KJR
                Title: Korean Journal of Radiology
                Publisher: The Korean Society of Radiology
                ISSN (Print): 1229-6929
                ISSN (Electronic): 2005-8330
                Publication date (Print): Nov-Dec 2015
                Publication date (Electronic): 26 October 2015
                Volume: 16
                Issue: 6
                Pages: 1188-1196
                Affiliations
                [1 ]Department of Biostatistics, Korea University College of Medicine, Seoul 02841, Korea.
                [2 ]Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea.
                Author notes
                Corresponding author: Seong Ho Park, MD, PhD, Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Korea. Tel: (822) 3010-5984, Fax: (822) 476-4719, parksh.radiology@ 123456gmail.com

                *Juneyoung Lee and Kyung Won Kim contributed equally to this work.

                Article
                DOI: 10.3348/kjr.2015.16.6.1188
                PMC ID: 4644739
                PubMed ID: 26576107
                SO-VID: a02b8a51-6dd9-403c-8abf-bd549cbf1503
                Copyright © Copyright © 2015 The Korean Society of Radiology
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 07 July 2015
                Date accepted : 28 August 2015
                Funding
                Funded by: Korea Health Industry Development Institute
                Funded by: Ministry of Health and Welfare
                Award ID: HI14C1090
                Categories
                Subject: Experimental and Others
                Subject: Review Article

                ScienceOpen disciplines: Radiology & Imaging
                Keywords: systematic review,meta-analysis,diagnostic test accuracy
                Data availability:
                ScienceOpen disciplines: Radiology & Imaging
                Keywords: systematic review, meta-analysis, diagnostic test accuracy

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