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Network meta-analysis of diagnostic test accuracy studies identifies and ranks the optimal diagnostic tests and thresholds for health care policy and decision-making

journal contribution
posted on 09.04.2018, 10:19 by Rhiannon Owen, Nicola Cooper, T Quinn, R Lees, Alex Sutton
Objectives: Network meta-analyses (NMA) have extensively been used to compare the effectiveness of multiple interventions for health care 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, whereas 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.

History

Citation

Journal of Clinical Epidemiology, 2018, 99, pp. 64-74

Author affiliation

/Organisation/COLLEGE OF LIFE SCIENCES/School of Medicine/Department of Health Sciences

Version

AM (Accepted Manuscript)

Published in

Journal of Clinical Epidemiology

Publisher

Elsevier

issn

0895-4356

eissn

1878-5921

Acceptance date

07/03/2018

Copyright date

2018

Available date

13/03/2019

Publisher version

https://www.sciencedirect.com/science/article/pii/S0895435617309411?via=ihub

Notes

The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.

Language

en

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