Owen, R. K., Cooper, N. J., Quinn, T. J. , Lees, R. and Sutton, A. J. (2018) Network meta-analysis of diagnostic test accuracy studies identifies and ranks the optimal diagnostic tests and thresholds for healthcare policy and decision making. Journal of Clinical Epidemiology, 99, pp. 64-74. (doi: 10.1016/j.jclinepi.2018.03.005) (PMID:29548843)
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Abstract
Objective: Network meta-analyses have extensively been used to compare the effectiveness of multiple interventions for healthcare policy and decision-making. However, methods for evaluating the performance of multiple diagnostic tests are less established. In a decision-making context, we are often interested in comparing and ranking the performance of multiple diagnostic tests, at varying levels of test thresholds, in one simultaneous analysis. Study design and setting: Motivated by an example of cognitive impairment diagnosis following stroke, we synthesized data from 13 studies assessing the efficiency of two diagnostic tests: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), at two test thresholds: MMSE <25/30 and <27/30, and MoCA <22/30 and <26/30. Using Markov Chain Monte Carlo (MCMC) methods, we fitted a bivariate network meta-analysis model incorporating constraints on increasing test threshold, and accounting for the correlations between multiple test accuracy measures from the same study. Results: We developed and successfully fitted a model comparing multiple tests/threshold combinations while imposing threshold constraints. Using this model, we found that MoCA at threshold <26/30 appeared to have the best true positive rate, whilst MMSE at threshold <25/30 appeared to have the best true negative rate. Conclusion: The combined analysis of multiple tests at multiple thresholds allowed for more rigorous comparisons between competing diagnostics tests for decision making.
Item Type: | Articles |
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Keywords: | Network meta-analysis, diagnostic test accuracy, meta-analysis, multiple tests, multiple thresholds. |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Quinn, Professor Terry |
Authors: | Owen, R. K., Cooper, N. J., Quinn, T. J., Lees, R., and Sutton, A. J. |
College/School: | College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health |
Journal Name: | Journal of Clinical Epidemiology |
Publisher: | Elsevier |
ISSN: | 0895-4356 |
ISSN (Online): | 1878-5921 |
Published Online: | 13 March 2018 |
Copyright Holders: | Copyright © 2018 The Authors |
First Published: | First published in Journal of Clinical Epidemiology 99:64-74 |
Publisher Policy: | Reproduced under a Creative Commons License |
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