Evidence map›Paper›PMID 38589763›Full record

ReviewInfectious diseases and therapy2024

Structured Literature Review to Identify Human Papillomavirus's Natural History Parameters for Dynamic Population Models of Vaccine Impacts.

Ibrahim Diakite, Bruno Martins, Kwame Owusu-Edusei, Cody Palmer, Oscar Patterson-Lomba, Andres Gomez-Lievano, Abigail Zion, Ryan Simpson, Vincent Daniels, Elamin Elbasha

Abstract readReview
In one paragraph

Review in Infectious diseases and therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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

10 authors.

Ibrahim DiakiteHealth Economic and Decision Sciences, Merck & Co., Inc., Rahway, NJ, 07065, USA. ibrahim.diakite@merck.com.ORCID http://orcid.org/0000-0001-7151-4330
Bruno MartinsAnalysis Group, Inc, 111 Huntington Avenue, 14th Floor, Boston, MA, 02199, USA.ORCID http://orcid.org/0000-0001-7484-1011
Kwame Owusu-EduseiHealth Economic and Decision Sciences, Merck & Co., Inc., Rahway, NJ, 07065, USA.ORCID http://orcid.org/0000-0002-4519-2857
Cody PalmerHealth Economic and Decision Sciences, Merck & Co., Inc., Rahway, NJ, 07065, USA.ORCID http://orcid.org/0000-0002-9060-5999
Oscar Patterson-LombaAnalysis Group, Inc, 111 Huntington Avenue, 14th Floor, Boston, MA, 02199, USA.ORCID http://orcid.org/0009-0000-3764-8191
Andres Gomez-LievanoAnalysis Group, Inc, 111 Huntington Avenue, 14th Floor, Boston, MA, 02199, USA.ORCID http://orcid.org/0000-0001-8320-0857
Abigail ZionAnalysis Group, Inc, 111 Huntington Avenue, 14th Floor, Boston, MA, 02199, USA.ORCID http://orcid.org/0000-0001-6598-394X
Ryan SimpsonAnalysis Group, Inc, 111 Huntington Avenue, 14th Floor, Boston, MA, 02199, USA.ORCID http://orcid.org/0000-0002-1375-5387
Vincent DanielsHealth Economic and Decision Sciences, Merck & Co., Inc., Rahway, NJ, 07065, USA.ORCID http://orcid.org/0000-0002-3226-7231
Elamin ElbashaHealth Economic and Decision Sciences, Merck & Co., Inc., Rahway, NJ, 07065, USA.ORCID http://orcid.org/0000-0002-9993-8036

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human papillomavirus (HPV) is a common sexually transmitted virus that can cause cervical cancer and other diseases. Dynamic transmission models (DTMs) have been developed to evaluate the health and economic impacts of HPV vaccination. These models typically include many parameters, such as natural history of the disease, transmission, demographic, behavioral, and screening. To ensure the accuracy of DTM projections, it is important to parameterize them with the best available evidence. This study aimed to identify and synthesize data needed to parametrize DTMs on the natural history of HPV infection and related diseases. Parameters describing data of interest were grouped by their anatomical location (genital warts, recurrent respiratory papillomatosis, and cervical, anal, vaginal, vulvar, head and neck, and penile cancers), and natural history (progression, regression, death, cure, recurrence, detection), and were identified through a systematic literature review (SLR) and complementary targeted literature reviews (TLRs). The extracted data were then synthesized by pooling parameter values across publications, and summarized using the range of values across studies reporting each parameter and the median value from the most relevant study. Data were extracted and synthesized from 223 studies identified in the SLR and TLRs. Parameters frequently reported pertained to cervical cancer outcomes, while data for other anatomical locations were less available. The synthesis of the data provides a large volume of parameter values to inform HPV DTMs, such as annual progression rates from cervical intraepithelial neoplasia (CIN) 1 to CIN 2+ (median of highest quality estimate 0.0836), CIN 2 to CIN 3+ (0.0418), carcinoma in situ (CIS) 2 to local cancer+ (0.0396), and regional to distant cancer (0.0474). Our findings suggest that while there is a large body of evidence on cervical cancer, parameter values featured substantial heterogeneity across studies, and further studies are needed to better parametrize the non-cervical components of HPV DTMs.

Indexed as

Anal cancerCervical cancerDisease transmission modelsGenital wartsHead and neck cancerHPVPenile cancerRRPVaginal cancerVulvar cancer

Identifiers

PMID38589763
PMCPMC11098984

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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.