Evidence map›Paper›PMID 22568612›Full record

ArticleBiometrics2012

Bayesian meta-analysis of the accuracy of a test for tuberculous pleuritis in the absence of a gold standard reference.

Nandini Dendukuri, Ian Schiller, Lawrence Joseph, Madhukar Pai

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In one paragraph

Article in Biometrics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 24 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 24 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

50 citing papers in PubMed, 24 syntheses or guidelines pooled it.

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  16. XpertThe Cochrane database of systematic reviews · 2018
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Nandini DendukuriDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal H3A 1A2, Canada. nandini.dendukuri@mcgill.ca
Ian Schiller
Lawrence Joseph
Madhukar Pai

Funding

CIHR 89857CIHR 89857-1
6 · The paper itself

Abstract

Absence of a perfect reference test is an acknowledged source of bias in diagnostic studies. In the case of tuberculous pleuritis, standard reference tests such as smear microscopy, culture and biopsy have poor sensitivity. Yet meta-analyses of new tests for this disease have always assumed the reference standard is perfect, leading to biased estimates of the new test's accuracy. We describe a method for joint meta-analysis of sensitivity and specificity of the diagnostic test under evaluation, while considering the imperfect nature of the reference standard. We use a Bayesian hierarchical model that takes into account within- and between-study variability. We show how to obtain pooled estimates of sensitivity and specificity, and how to plot a hierarchical summary receiver operating characteristic curve. We describe extensions of the model to situations where multiple reference tests are used, and where index and reference tests are conditionally dependent. The performance of the model is evaluated using simulations and illustrated using data from a meta-analysis of nucleic acid amplification tests (NAATs) for tuberculous pleuritis. The estimate of NAAT specificity was higher and the sensitivity lower compared to a model that assumed that the reference test was perfect.

Indexed as

Bayes TheoremMeta-Analysis as TopicModels, StatisticalComputer SimulationDNA, BacterialHumansInternationalityNucleic Acid Amplification TechniquesTuberculosis, PleuralDNA, Bacterial

Identifiers

PMID22568612
PMCPMC3728030

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.