Evidence map›Paper›PMID 28073308›Full record

ArticleJournal of medical screening2017

High lifetime probability of screen-detected cervical abnormalities.

Maiju Pankakoski, Sirpa Heinävaara, Tytti Sarkeala, Ahti Anttila

Abstract read
In one paragraph

Article in Journal of medical screening, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Maiju Pankakoski1 Finnish Cancer Registry, Helsinki, Finland.
Sirpa Heinävaara1 Finnish Cancer Registry, Helsinki, Finland.
Tytti Sarkeala1 Finnish Cancer Registry, Helsinki, Finland.
Ahti Anttila1 Finnish Cancer Registry, Helsinki, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective Regular screening and follow-up is an important key to cervical cancer prevention; however, screening inevitably detects mild or borderline abnormalities that would never progress to a more severe stage. We analysed the cumulative probability and recurrence of cervical abnormalities in the Finnish organized screening programme during a 22-year follow-up. Methods Screening histories were collected for 364,487 women born between 1950 and 1965. Data consisted of 1 207,017 routine screens and 88,143 follow-up screens between 1991 and 2012. Probabilities of cervical abnormalities by age were estimated using logistic regression and generalized estimating equations methodology. Results The probability of experiencing any abnormality at least once at ages 30-64 was 34.0% (95% confidence interval [CI]: 33.3-34.6%) . Probability was 5.4% (95% CI: 5.0-5.8%) for results warranting referral and 2.2% (95% CI: 2.0-2.4%) for results with histologically confirmed findings. Previous occurrences were associated with an increased risk of detecting new ones, specifically in older women. Conclusion A considerable proportion of women experience at least one abnormal screening result during their lifetime, and yet very few eventually develop an actual precancerous lesion. Re-evaluation of diagnostic criteria concerning mild abnormalities might improve the balance of harms and benefits of screening. Special monitoring of women with recurrent abnormalities especially at older ages may also be needed.

Indexed as

AdultAgedAge FactorsEarly Detection of CancerFemaleFinlandFollow-Up StudiesHumansMass ScreeningMiddle AgedPrecancerous ConditionsProbabilityRecurrenceReferral and ConsultationUterine Cervical NeoplasmsVaginal Smearsborderline abnormalitiescervical cancerlongitudinal studyScreening

Identifiers

PMID28073308
PMCPMC5661699

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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.