Evidence map›Paper›PMID 31344234›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2020

Methylation in Predicting Progression of Untreated High-grade Cervical Intraepithelial Neoplasia.

Karolina Louvanto, Karoliina Aro, Belinda Nedjai, Ralf Bützow, Maija Jakobsson, Ilkka Kalliala, Joakim Dillner, Pekka Nieminen, Attila Lorincz

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Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 2 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

47 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Karolina LouvantoDepartment of Obstetrics and Gynecology, Turku University Hospital, University of Turku, Turku, Finland.
Karoliina AroDepartment of Obstetrics and Gynecology, Finland.
Belinda NedjaiCenter for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, United Kingdom.
Ralf BützowDepartment of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Maija JakobssonDepartment of Obstetrics and Gynecology, Finland.
Ilkka KallialaDepartment of Obstetrics and Gynecology, Finland.
Joakim DillnerDepartment of Laboratory Medicine, Karolinska Institute, Stockholm, Sweden.
Pekka NieminenDepartment of Obstetrics and Gynecology, Finland.
Attila LorinczCenter for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, United Kingdom.

Funding

Cancer Research UK 21070Cancer Research UK 27046Cancer Research UK C569/A10404
6 · The paper itself

Abstract

backgroundThere is no prognostic test to ascertain whether cervical intraepithelial neoplasias (CINs) regress or progress. The majority of CINs regress in young women, and treatments increase the risk of adverse pregnancy outcomes. We investigated the ability of a DNA methylation panel (the S5 classifier) to discriminate between outcomes among young women with untreated CIN grade 2 (CIN2).

methodsBaseline pyrosequencing methylation and human papillomavirus (HPV) genotyping assays were performed on cervical cells from 149 women with CIN2 in a 2-year cohort study of active surveillance.

resultsTwenty-five lesions progressed to CIN grade 3 or worse, 88 regressed to less than CIN grade 1, and 36 persisted as CIN1/2. When cytology, HPV16/18 and HPV16/18/31/33 genotyping, and the S5 classifier were compared to outcomes, the S5 classifier was the strongest biomarker associated with regression vs progression. The S5 classifier alone or in combination with HPV16/18/31/33 genotyping also showed significantly increased sensitivity vs cytology when comparing regression vs persistence/progression. With both the S5 classifier and cytology set at a specificity of 38.6% (95% confidence interval [CI], 28.4-49.6), the sensitivity of the S5 classifier was significantly higher (83.6%; 95% CI, 71.9-91.8) than of cytology (62.3%; 95% CI, 49.0-74.4; P = 0.005). The highest area under the curve was 0.735 (95% CI, 0.621-0.849) in comparing regression vs progression with a combination of the S5 classifier and cytology, whereas HPV genotyping did not provide additional information.

conclusionsThe S5 classifier shows high potential as a prognostic biomarker to identify progressive CIN2.

Indexed as

PapillomaviridaePapillomavirus InfectionsUterine Cervical DysplasiaUterine Cervical NeoplasmsCohort StudiesFemaleHuman papillomavirus 16Human papillomavirus 18HumansMethylationPregnancycervical intraepithelial neoplasiaCINDNA methylationhigh-grade squamous intraepithelial lesionHSIL

Identifiers

PMID31344234
PMCPMC7286376

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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.