Literature DB >> 19692208

A statistical method was used for the meta-analysis of tests for latent TB in the absence of a gold standard, combining random-effect and latent-class methods to estimate test accuracy.

Mohsen Sadatsafavi1, Neal Shahidi, Fawziah Marra, Mark J FitzGerald, Kevin R Elwood, Na Guo, Carlo A Marra.   

Abstract

OBJECTIVE: Because of the lack of a gold standard, the diagnostic performance of tests for the detection of latent tuberculosis infection (LTBI) is not known. However, statistical methods can be used to estimate the accuracy from the studies reporting the concordance among the tests. STUDY DESIGN AND
SETTING: We developed a random-effect latent-class model to estimate performance characteristics of three LTBI diagnostic tests: tuberculin skin test (TST, at 10-mm cutoff), QuantiFERON-TB gold (QFG), and TSPOT-TB from the studies evaluating agreement among the tests.
RESULTS: Nineteen studies were included. QFG had a sensitivity of 0.642 (95% confidence interval [CI]: 0.593-0.691) and specificity of 0.996 (95% CI: 0.989-1.000), TSPOT-TB had a sensitivity of 0.500 (95% CI: 0.334-0.666) and specificity of 0.906 (95% CI: 0.882-0.929), and TST had a sensitivity of 0.709 (95% CI: 0.658-0.761) and specificity of 0.683 (95% CI: 0.522-0.844). Results were not sensitive to the inclusion of any single study. When only the three studies that reported on TSPOT were removed, estimates for the other two tests varied minimally.
CONCLUSIONS: Statistical methods can help estimate the accuracy of LTBI tests. Although the specificities were close to their reported values in the literature, the estimates for sensitivities were low; a finding that should be carefully evaluated.

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Year:  2009        PMID: 19692208     DOI: 10.1016/j.jclinepi.2009.04.008

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  17 in total

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

Authors:  Nandini Dendukuri; Ian Schiller; Lawrence Joseph; Madhukar Pai
Journal:  Biometrics       Date:  2012-05-08       Impact factor: 2.571

2.  Effective tuberculosis and hepatitis screening prior to anti-TNF-α therapy: are we there yet?

Authors:  Neal Shahidi; Brian Bressler
Journal:  Dig Dis Sci       Date:  2014-03       Impact factor: 3.199

Review 3.  Statistical methods for multivariate meta-analysis of diagnostic tests: An overview and tutorial.

Authors:  Xiaoye Ma; Lei Nie; Stephen R Cole; Haitao Chu
Journal:  Stat Methods Med Res       Date:  2013-06-26       Impact factor: 3.021

4.  Copas-like selection model to correct publication bias in systematic review of diagnostic test studies.

Authors:  Jin Piao; Yulun Liu; Yong Chen; Jing Ning
Journal:  Stat Methods Med Res       Date:  2018-07-31       Impact factor: 3.021

5.  A Bayesian Hierarchical Summary Receiver Operating Characteristic Model for Network Meta-analysis of Diagnostic Tests.

Authors:  Qinshu Lian; James S Hodges; Haitao Chu
Journal:  J Am Stat Assoc       Date:  2018-08-07       Impact factor: 5.033

6.  A hybrid Bayesian hierarchical model combining cohort and case-control studies for meta-analysis of diagnostic tests: Accounting for partial verification bias.

Authors:  Xiaoye Ma; Yong Chen; Stephen R Cole; Haitao Chu
Journal:  Stat Methods Med Res       Date:  2014-05-26       Impact factor: 3.021

7.  Classifying Injuries in Young Children as Abusive or Accidental: Reliability and Accuracy of an Expert Panel Approach.

Authors:  Douglas J Lorenz; Mary Clyde Pierce; Kim Kaczor; Rachel P Berger; Gina Bertocci; Bruce E Herman; Sandra Herr; Kent P Hymel; Carole Jenny; John M Leventhal; Karen Sheehan; Noel Zuckerbraun
Journal:  J Pediatr       Date:  2018-03-15       Impact factor: 4.406

Review 8.  Summary diagnostic validity of commonly used maternal major depression disorder case finding instruments in the United States: A meta-analysis.

Authors:  Arthur H Owora; Hélène Carabin; Jessica Reese; Tabitha Garwe
Journal:  J Affect Disord       Date:  2016-08-16       Impact factor: 4.839

9.  Using a web-based application to define the accuracy of diagnostic tests when the gold standard is imperfect.

Authors:  Cherry Lim; Prapass Wannapinij; Lisa White; Nicholas P J Day; Ben S Cooper; Sharon J Peacock; Direk Limmathurotsakul
Journal:  PLoS One       Date:  2013-11-12       Impact factor: 3.240

Review 10.  Estimation of diagnostic test accuracy without full verification: a review of latent class methods.

Authors:  John Collins; Minh Huynh
Journal:  Stat Med       Date:  2014-06-09       Impact factor: 2.373

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