Evidence map›Paper›PMID 36832098›Full record

ReviewDiagnostics (Basel, Switzerland)2023

Prevention Strategies and Early Diagnosis of Cervical Cancer: Current State and Prospects.

Viktor V Kakotkin, Ekaterina V Semina, Tatiana G Zadorkina, Mikhail A Agapov

Open access · goldAbstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
8.4field-weighted citation impact, top 2% 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

22 citing papers in PubMed, 39 citations in OpenAlex.

  1. High-Risk Human Papillomavirus Clearance with aDiseases (Basel, Switzerland) · 2026
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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

4 authors at 2 institutions in 1 country.

Viktor V KakotkinScientific and Educational Cluster MEDBIO, Immanuel Kant Baltic Federal University, A. Nevskogo St., 14, 236041 Kaliningrad, Russia.ORCID 0000-0003-0352-2317
Ekaterina V SeminaScientific and Educational Cluster MEDBIO, Immanuel Kant Baltic Federal University, A. Nevskogo St., 14, 236041 Kaliningrad, Russia.ORCID 0000-0002-3927-9286
Tatiana G ZadorkinaKaliningrad Regional Centre for Specialised Medical Care, Barnaulskaia Street, 6, 236006 Kaliningrad, Russia.
Mikhail A AgapovScientific and Educational Cluster MEDBIO, Immanuel Kant Baltic Federal University, A. Nevskogo St., 14, 236041 Kaliningrad, Russia.
Immanuel Kant Baltic Federal University · RUKaliningrad State Technical University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cervical cancer ranks third among all new cancer cases and causes of cancer deaths in females. The paper provides an overview of cervical cancer prevention strategies employed in different regions, with incidence and mortality rates ranging from high to low. It assesses the effectiveness of approaches proposed by national healthcare systems by analysing data published in the National Library of Medicine (Pubmed) since 2018 featuring the following keywords: "cervical cancer prevention", "cervical cancer screening", "barriers to cervical cancer prevention", "premalignant cervical lesions" and "current strategies". WHO's 90-70-90 global strategy for cervical cancer prevention and early screening has proven effective in different countries in both mathematical models and clinical practice. The data analysis carried out within this study identified promising approaches to cervical cancer screening and prevention, which can further enhance the effectiveness of the existing WHO strategy and national healthcare systems. One such approach is the application of AI technologies for detecting precancerous cervical lesions and choosing treatment strategies. As such studies show, the use of AI can not only increase detection accuracy but also ease the burden on primary care.

Indexed as

artificial intelligencecervical cancerdiagnosticsmicrobiomeprecision medicineprevention strategies

Identifiers

PMID36832098
PMCPMC9955852
OpenAlexW4319597821

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.