Evidence map›Paper›PMID 25880688›Full record

ArticleBMC infectious diseases2015

Evaluation of using composite HPV genotyping assay results to monitor human papillomavirus infection burden through simulation.

Carol Y Lin

Abstract read
In one paragraph

Article in BMC infectious diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

1 author.

Carol Y LinDivision of STD Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, 1600 Clifton Road, NE, MS E-63, Atlanta, GA, 30333, USA. clin@cdc.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundResearchers often group various HPV types into composite measures based on vaccine subtypes, oncogenic potential, or phylogenetic position. Composite prevalence estimates based on PCR genotyping assay results have been calculated to assess HPV infection burden and to monitor HPV vaccine effectiveness. While prevention and intervention strategies can be made based on these prevalence estimates, the discussion on how well these prevalence estimates measure the true underlying infection burdens is limited.

methodsA simulation study was conducted to evaluate accuracy of using composite genotyping assay results to monitor HPV infection burden. Data were generated based on mathematical algorithms with prespecified type-specific infection burdens, assay sensitivity, specificity, and correlations between various HPV types. Estimated-to-true prevalence rate ratios and percent reduction of vaccine types were calculated.

resultsWhen "true" underlying type-specific infection burdens were prespecified as the reported prevalence in U.S. and genotyping assay with sensitivity and specificity (0.95, 0.95) was used, estimated-to-true infection prevalence ratios were 2.35, 2.29, 2.18, and 1.46, for the composite measures with 2 high-risk vaccine, 4 vaccine, 14 high-risk and 37 HPV types, respectively. Estimated-to-true prevalence ratios increased when prespecified "true" underlying infection burdens or assay specificity declined. When prespecified "true" type-specific infections of HPV 6, 11, 16 and 18 were reduced by 50%, the composite prevalence estimate of 4 vaccine types only decreased by 17% which is much lower than 48% reduction in the prespecified "true" composite prevalence.

conclusionsComposite prevalence estimates calculated based on panels of genotyping assay results generally over-estimate the "true" underlying infection burdens and could under-estimate vaccine effectiveness. Analytical specificity of genotyping assay is as or more important than analytical sensitivity and should be considered in selecting assay to monitor HPV.

Indexed as

AlgorithmsComputer SimulationGenotypeHumansPapillomaviridaePapillomavirus InfectionsPapillomavirus VaccinesPhylogenyPolymerase Chain ReactionPrevalenceUnited StatesPapillomavirus Vaccines

Identifiers

PMID25880688
PMCPMC4362818

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