↓ Skip to main content

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

Overview of attention for article published in BMC Infectious Diseases, March 2015
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
10 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Evaluation of using composite HPV genotyping assay results to monitor human papillomavirus infection burden through simulation
Published in
BMC Infectious Diseases, March 2015
DOI 10.1186/s12879-015-0851-x
Pubmed ID
Authors

Carol Y Lin

Abstract

Researchers 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. A 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. When "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. Composite 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.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Professor 2 20%
Other 1 10%
Student > Doctoral Student 1 10%
Student > Ph. D. Student 1 10%
Student > Master 1 10%
Other 1 10%
Unknown 3 30%
Readers by discipline Count As %
Medicine and Dentistry 2 20%
Nursing and Health Professions 1 10%
Biochemistry, Genetics and Molecular Biology 1 10%
Social Sciences 1 10%
Agricultural and Biological Sciences 1 10%
Other 0 0%
Unknown 4 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 March 2015.
All research outputs
#18,402,666
of 22,794,367 outputs
Outputs from BMC Infectious Diseases
#5,598
of 7,674 outputs
Outputs of similar age
#188,694
of 259,041 outputs
Outputs of similar age from BMC Infectious Diseases
#106
of 158 outputs
Altmetric has tracked 22,794,367 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,674 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 259,041 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 158 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.