Evidence map›Paper›PMID 31056620›Full record

ArticleSaudi medical journal2019

Modelling risk assessment for cervical cancer in symptomatic Saudi women.

Wedad Al-Madani, Anwar E Ahmed, Haitham Arabi, Sumaiah Al Khodairy, Nashmia Al Mutairi, Abdul Rahman Jazieh

Abstract read
In one paragraph

Article in Saudi medical journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Assessment of an onco-sexology support and follow-up program in cervical or vaginal cancer patients undergoing brachytherapy.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2021
    Article
  6. 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

6 authors.

Wedad Al-MadaniDepartment of National Center for Evidence-Based Health Practice, Saudi Health Council, Riyadh, Kingdom of Saudi Arabia. E-mail. madaniwh@gmail.com.
Anwar E Ahmed
Haitham Arabi
Sumaiah Al Khodairy
Nashmia Al Mutairi
Abdul Rahman Jazieh

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo assess whether the utility of cervical cancer screening could be improved by combining multiple factors in addition to the pap test. Methods: A retrospective cohort study of 300 symptomatic women who were suspected to have cervical cancer and referred for biopsy examination at King Abdulaziz Medical City, Riyadh, Saudi Arabia between February 2017 and December 2017. Results: A high risk of cervical cancer in Saudi women was associated with 4 risk factors: family history (adjusted odds ratio [aOR], 4.216; 95% confidence intervals [CI], 1.433-12.400), vaginal bleeding (aOR, 3.959; 95% CI, 1.272-12.318), hypertension (aOR, 4.554; 95% CI, 1.606-12.912), and an abnormal pap smear test (aOR, 13.985; 95% CI, 5.108-38.284). The model yields an adequate utility (area under the curve, 87.5%, 95% CI, 80.9-94.0%) with acceptable goodness-of-fit (p=0.6915). Conclusion: The pap smear test alone is inadequate to assess high risk for cervical cancer in our center. Early detection of cervical cancer may require consideration of a combination of factors including the pap test. This study has shown that using a combination of abnormal family history, vaginal bleeding, hypertension, and the pap smear test improved the effectiveness of cervical cancer screening.

Indexed as

Cohort StudiesEarly Detection of CancerFemaleHumansHypertensionMass ScreeningPapanicolaou TestRetrospective StudiesRisk AssessmentRisk FactorsSaudi ArabiaUterine Cervical NeoplasmsUterine Hemorrhage

Identifiers

PMID31056620
PMCPMC6535164

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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.