Evidence map›Paper›PMID 24130223›Full record

ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2014

Characterizing the temporal dynamics of human papillomavirus DNA detectability using short-interval sampling.

Su-Hsun Liu, Derek A T Cummings, Jonathan M Zenilman, Patti E Gravitt, Rebecca M Brotman

Abstract read
In one paragraph

Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Observational
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. HPV and the Risk of HIV Acquisition in Women.Frontiers in cellular and infection microbiology · 2022
    Review
  12. Article
  13. Screening for cervical cancer: Choices & dilemmas.The Indian journal of medical research · 2021
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
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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

5 authors.

Su-Hsun LiuAuthors' Affiliations: Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University; Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine; Institute for Genome Sciences; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland; Department of Family Medicine, Chang Gung Memorial Hospital, Linkou, Taiwan; and Perdana University Graduate School of Medicine, Serdang, Malaysia.
Derek A T Cummings
Jonathan M Zenilman
Patti E Gravitt
Rebecca M Brotman

Funding

HPV Infection Among Perimenopausal Women in the 1945-64 Birth CohorR01CA123467 · NCI · JOHNS HOPKINS UNIVERSITY · PI GRAVITT, PATTI E · 2007 to 2012
$3.1M
Molecular Epidemiology of the Vaginal MicrobiomeK01AI080974 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI BROTMAN, REBECCA M. · 2010 to 2014
$644k
Recovery of Vaginal Flora after Douching CessationR03AI061131 · NIAID · JOHNS HOPKINS UNIVERSITY · PI ZENILMAN, JONATHAN M · 2005 to 2006
$125k
NCI NIH HHS R01 CA123467NIAID NIH HHS K01 AI080974NIAID NIH HHS R03 AI061131
6 · The paper itself

Abstract

backgroundVariable detection of human papillomavirus (HPV) DNA can result in misclassification of infection status, but the extent of misclassification has not been quantitatively evaluated.

methodsIn 2005-2007, 33 women of ages 22 to 53 years self-collected vaginal swabs twice per week for 16 consecutive weeks. Each of the 955 swabs collected was tested for 37 HPV types/subtypes. Assuming that a woman's underlying infection status did not change over the short study period, biases in prevalence estimates obtained from single versus multiple swabs were calculated. Using event history analysis methods, time to recurrent gain and loss of at least one HPV type was determined, separately. Baseline any-type and high risk-type HPV prevalence was 60.6% and 24.2%, respectively. Cumulative any-HPV and high-risk HPV prevalence over the 16-week period was 84.8% and 60.6%, separately.

resultsOverall, there were 319 events of detection and 313 events of loss of detection. Median times to a recurrent detection and loss of detection were 11 and seven days, respectively. Neither vaginal sex nor condom use during follow-up was associated with recurrent viral detection or loss of detection. Assuming the cumulative 16-week prevalence reflects the true prevalence of infection, the baseline any-HPV prevalence underestimated infection status by 24.2%, with a bootstrapped mean of 20.2% [95% confidence interval (CI), 8.9%-29.6%].

conclusionsThese findings suggest that a substantial proportion of HPV-infected women are misclassified as being uninfected when using a single-time DNA measurement. IMPACT: Short-term variation in detectable HPV DNA needs to be considered while interpreting the natural history of infections using single samples collected at long intervals.

Indexed as

AdultCervix UteriDNA, ViralFemaleHumansPapillomaviridaePapillomavirus InfectionsVaginal SmearsDNA, Viral

Identifiers

PMID24130223
PMCPMC3947138

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Registered trials

None linked

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.