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ALLSTAT  March 2019

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Subject:

Seminar: Keele University, 14th March

From:

Ivonne Solis-Trapala <[log in to unmask]>

Reply-To:

Ivonne Solis-Trapala <[log in to unmask]>

Date:

Wed, 6 Mar 2019 14:55:36 +0000

Content-Type:

text/plain

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Biostatistics Group Seminar Series
Research Institute for Primary Care and Health Sciences
Keele University

Title: Meta-analysis of diagnostic test accuracy across the full range 
of possible cut-offs.

Speaker: Dr Hayley Jones, Bristol Medical School, University of Bristol.

Date: Thursday 14th March 13:00-14:00

Venue: Dinwoodie Lecture Theatre, David Weatherall Building
https://www.keele.ac.uk/connect/howtofindus/maps/keele-campus-guide-colour.pdf

Abstract: The optimum threshold or cut-off at which to operate a 
diagnostic test is usually a key question for clinical practice. 
Standard methods for meta-analysis of test accuracy don’t facilitate 
answering this question, since they (i) don’t provide summary estimates 
of accuracy across the full range of thresholds, and (ii) can only 
synthesise a single pair of sensitivity and specificity from each study, 
despite studies often reporting data at more than one threshold. Several 
models have recently been proposed for a unified meta-analysis of all 
available data, via assumptions about the underlying distributional form 
of test results. I will describe a multinomial random effects model, 
fitted in WinBUGS, which synthesises test accuracy data across studies 
reporting at different and varying numbers of cut-offs. The model allows 
for a flexible range of underlying distributions of test results, 
through estimation of a Box-Cox transformation parameter. I will present 
examples including meta-analysis of the accuracy of B-type natriuretic 
peptide in the diagnosis of acute heart failure. In a recent 
collaboration with researchers at McGill University and with Gerta 
Rücker (University of Freiburg), we compared results from three 
alternative models fitted to data from 45 studies reporting on accuracy 
of PHQ-9 in diagnosing major depression. Each model was fitted to two 
alternative versions of the data: (i) that available from the study 
publications, (ii) the full individual participant data (IPD). I will 
present results from this study, in particular showing that our model 
fitted to the ‘published’ dataset well approximated the IPD.


Dr Ivonne Solis-Trapala
Deputy Lead, NIHR Research Design Service, West Midlands (Keele Hub)
Senior Lecturer in Medical Statistics
Research Institute for Primary Care and Health Sciences
and Keele Clinical Trials Unit
Faculty of Medicine and Health Sciences
Keele University
Staffordshire, ST5 5BG
Room DJW1.51, e-mail: [log in to unmask]

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