Evidence map›Paper›PMID 17989336›Full record

ArticleClinical and vaccine immunology : CVI2008

Utility of composite reference standards and latent class analysis in evaluating the clinical accuracy of diagnostic tests for pertussis.

Andrew L Baughman, Kristine M Bisgard, Margaret M Cortese, William W Thompson, Gary N Sanden, Peter M Strebel

Abstract read
In one paragraph

Article in Clinical and vaccine immunology : CVI, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 5 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

41 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
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  5. Pooled it
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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

6 authors.

Andrew L BaughmanNational Center for Immunization and Respiratory Diseases,Centers for Disease Control and Prevention, Atlanta, Georgia 30329, USA. ALB1@cdc.gov
Kristine M Bisgard
Margaret M Cortese
William W Thompson
Gary N Sanden
Peter M Strebel

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Numerous evaluations of the clinical sensitivity and specificity of PCR and serologic assays for Bordetella pertussis have been hampered by the low sensitivity of culture, the gold standard test, which leads to biased accuracy estimates. The bias can be reduced by using statistical approaches such as the composite reference standard (CRS) (e.g., positive if culture or serology positive; negative otherwise) or latent class analysis (LCA), an internal reference standard based on a statistical model. We illustrated the benefits of the CRS and LCA approaches by reanalyzing data from a 1995 to 1996 study of cough illness among 212 patients. The accuracy of PCR in this study was evaluated using three reference standards: culture, CRS, and LCA. Using specimens obtained 0 to 34 days after cough onset, estimates of the sensitivity of PCR obtained using CRS (47%) and LCA (34%) were lower than the culture-based estimate (62%). The CRS and LCA approaches, which utilized more than one diagnostic marker of pertussis, likely produced more accurate reference standards than culture alone. In general, the CRS approach is simple, with a well-defined disease status. LCA requires statistical modeling but incorporates more indicators of disease than CRS. When three or more indicators of pertussis are available, these approaches should be used in evaluations of pertussis diagnostic tests.

Indexed as

AdolescentAdultBacteriological TechniquesBordetella pertussisChildHumansMiddle AgedModels, StatisticalPolymerase Chain ReactionPredictive Value of TestsReference StandardsSensitivity and SpecificitySerologic TestsWhooping Cough

Identifiers

PMID17989336
PMCPMC2223853

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.