Evidence map›Paper›PMID 32639531›Full record

ArticleAmerican journal of epidemiology2021

Differing Age-Specific Cervical Cancer Incidence Between Different Types of Human Papillomavirus: Implications for Predicting the Impact of Elimination Programs.

Simopekka Vänskä, Tapio Luostarinen, Camilla Lagheden, Carina Eklund, Sara Nordqvist Kleppe, Bengt Andrae, Pär Sparén, Karin Sundström, Matti Lehtinen, Joakim Dillner

Open access · hybridAbstract read
In one paragraph

Article in American journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.9field-weighted citation impact, top 8% of its field
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

12 citing papers in PubMed, 25 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Simopekka Vänskä
Tapio Luostarinen
Camilla Lagheden
Carina Eklund
Sara Nordqvist Kleppe
Bengt Andrae
Pär Sparén
Karin Sundström
Matti Lehtinen
Joakim Dillner
Karolinska Institutet · SEKarolinska University Hospital · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The elimination of cervical cancer rests on high efficacy of human papillomavirus (HPV) vaccines. The HPV type distribution among cases of invasive cervical cancer (ICC) is used to make predictions about the impact of eliminating different types of HPV, but accumulating evidence of differences in age-specific cancer incidence by HPV type exists. We used one of the largest population-based series of HPV genotyping of ICCs (n = 2,850; Sweden, 2002-2011) to estimate age-specific ICC incidence by HPV type and obtain estimates of the cancer-protective impact of the removal of different HPV types. In the base case, the age-specific ICC incidence had 2 peaks, and the standardized lifetime risk (SLTR, the lifetime number of cases per birth cohort of 100,000 females) for HPV-positive ICC was 651 per 100,000 female births. In the absence of vaccine types HPV 16 and HPV 18, the SLTR for ICC was reduced to 157 per 100,000 female births (24% of HPV-positive SLTR). Elimination of all 9 types that can currently be vaccinated against reduced the remaining SLTR to 47 per 100,000 female births (7%), the remaining ICC incidence only slowly increasing with age. In conclusion, after elimination of vaccine-protected HPV types, very few cases of ICC will be left, especially among fertile, reproductive-age women.

Indexed as

RegistriesAdultAge FactorsFemaleFollow-Up StudiesHumansIncidencePapillomaviridaePapillomavirus InfectionsRetrospective StudiesSwedenUterine Cervical NeoplasmsVaccinationage-specific cervical cancer incidencecervical cancerdisease eradicationHPV vaccinehuman papillomavirusvaccination

Identifiers

PMID32639531
PMCPMC8024050
OpenAlexW3040826070

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.