Evidence map›Paper›PMID 19562044›Full record

ArticleJournal of the American Statistical Association2009

Random Effects Models in a Meta-Analysis of the Accuracy of Two Diagnostic Tests Without a Gold Standard.

Haitao Chu, Sining Chen, Thomas A Louis

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Statistical Association, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 20 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 20 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

47 citing papers in PubMed, 20 syntheses or guidelines pooled it.

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  14. XpertThe Cochrane database of systematic reviews · 2018
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  20. Bivariate random effects meta-analysis of diagnostic studies using generalized linear mixed models.Medical decision making : an international journal of the Society for Medical Decision Making
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Haitao ChuResearch Associate Professor, Department of Biostatistics and Lineberger Comprehensive Cancer Center, The Univerity of North Carolina, Chapel Hill, NC 27599 (E-mail: hchu@bios.unc.edu ).
Sining Chen
Thomas A Louis

Funding

Virology Research Program (Program 4)P30CA016086 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Deborah F. Tate · 1985 to 2026
$201.5M
TISSUE PROCUREMENT &ANALYSISP50CA106991 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI TEPPER, JOEL E · 2004 to 2009
$12.1M
Hierarchical Models in Health Services ResearchR01DK061662 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI LOUIS, THOMAS A. · 2002 to 2009
$1.1M
NCI NIH HHS P30 CA016086NCI NIH HHS P50 CA106991NIDDK NIH HHS R01 DK061662
6 · The paper itself

Abstract

In studies of the accuracy of diagnostic tests, it is common that both the diagnostic test itself and the reference test are imperfect. This is the case for the microsatellite instability test, which is routinely used as a prescreening procedure to identify individuals with Lynch syndrome, the most common hereditary colorectal cancer syndrome. The microsatellite instability test is known to have imperfect sensitivity and specificity. Meanwhile, the reference test, mutation analysis, is also imperfect. We evaluate this test via a random effects meta-analysis of 17 studies. Study-specific random effects account for between-study heterogeneity in mutation prevalence, test sensitivities and specificities under a nonlinear mixed effects model and a Bayesian hierarchical model. Using model selection techniques, we explore a range of random effects models to identify a best-fitting model. We also evaluate sensitivity to the conditional independence assumption between the microsatellite instability test and the mutation analysis by allowing for correlation between them. Finally, we use simulations to illustrate the importance of including appropriate random effects and the impact of overfitting, underfitting, and misfitting on model performance. Our approach can be used to estimate the accuracy of two imperfect diagnostic tests from a meta-analysis of multiple studies or a multicenter study when the prevalence of disease, test sensitivities and/or specificities may be heterogeneous among studies or centers.

Identifiers

PMID19562044
PMCPMC2701906

What OpenQuestion holds

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Registered trials

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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.