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Abstract
Following a metaanalysis of test accuracy studies, the translation of summary results into clinical practice is potentially problematic. The sensitivity, specificity and positive (PPV) and negative (NPV) predictive values of a test may differ substantially from the average metaanalysis findings, because of heterogeneity. Clinicians thus need more guidance: given the metaanalysis, is a test likely to be useful in new populations, and if so, how should test results inform the probability of existing disease (for a diagnostic test) or future adverse outcome (for a prognostic test)? We propose ways to address this. Firstly, following a metaanalysis, we suggest deriving prediction intervals and probability statements about the potential accuracy of a test in a new population. Secondly, we suggest strategies on how clinicians should derive posttest probabilities (PPV and NPV) in a new population based on existing metaanalysis results and propose a crossvalidation approach for examining and comparing their calibration performance. Application is made to two clinical examples. In the first example, the joint probability that both sensitivity and specificity will be >80% in a new population is just 0.19, because of a low sensitivity. However, the summary PPV of 0.97 is high and calibrates well in new populations, with a probability of 0.78 that the true PPV will be at least 0.95. In the second example, posttest probabilities calibrate better when tailored to the prevalence in the new population, with crossvalidation revealing a probability of 0.97 that the observed NPV will be within 10% of the predicted NPV.
Original language  English 

Pages (fromto)  20812103 
Number of pages  23 
Journal  Statistics in Medicine 
Volume  34 
Issue number  13 
DOIs  
Publication status  Published  15 Jun 2015 
Bibliographical note
© 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.Fingerprint
Dive into the research topics of 'Summarising and validating test accuracy results across multiple studies for use in clinical practice'. Together they form a unique fingerprint.Projects
 1 Finished

Multivariate MetaAnalysis of Multiple Correlated Outcomes: Development and Application of Methods, with Empirical Investigation of Clinical Impact
Riley, R., Deeks, J. & Kenyon, S.
1/02/13 → 31/03/16
Project: Research Councils