Evidence map›Paper›PMID 36765315›Full record

ArticleBMC women's health2023

Assessing survival time of outpatients with cervical cancer: at the university of Gondar referral hospital using the Bayesian approach.

Chalachew Gashu, Buzuneh Tasfa, Chekol Alemu, Yoseph Kassa

Open access · goldAbstract read
In one paragraph

Article in BMC women's health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 11% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
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  6. Deciphering the Expression, Functional Role, and Prognostic Significance ofJournal of obstetrics and gynaecology of India · 2025
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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.

Chalachew GashuDepartment of Statistics, College of Natural and Computational Science, Oda Bultum University, Chiro, Ethiopia. chalachew154@gmail.com.
Buzuneh TasfaDepartment of Epidemiology, Faculty of Public Health, Jima University, Jima, Ethiopia.
Chekol AlemuDepartment of Statistics, College of Natural and Computational Science, Gambella University, Gambella, Ethiopia.
Yoseph KassaDepartment of Statistics, College of Natural and Computational Science, Oda Bultum University, Chiro, Ethiopia.
Gambella UniversityJimma University · ET

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCervical cancer is the 4th most common cancer in women worldwide. as well as the 4th most common cause of cancer-related death. The main objective of this study was to identify factors that affect the survival time of outpatients with cervical cancer.

methodsA retrolective study including outpatients with cervical cancer was carried out in a hospital. To achieve the aim, 322 outpatients with cervical cancer were included in the study based on the data taken from the medical records of patients enrolled from May 15, 2018, to May 15, 2022, at the University of Gondar referral hospital, Gondar, Ethiopia. The Kaplan-Meier plots and log-rank test were used for the comparison of survival functions; the Cox-PH model and Bayesian parametric survival models were used to analyze the survival times of outpatients with cervical cancer. Integrated nested Laplace approximation methods have been applied.

resultsOut of a total of 322 patients, 118 (36.6%) died as outpatients. The estimated median survival time for patients was 42 months. Using model selection criteria, the Bayesian log-normal accelerated failure time model was found to be appropriate. According to the results of this model, oral contraceptive use, HIV, stage, grade, co-morbid disease, history of abortion, weight, histology type, FIGO stage, radiation, chemotherapy, LVSI, metastatic number, regional nodes examined, and tumor size all have a significant impact on the survival time of outpatients with cervical cancer. The Bayesian log-normal accelerated failure time model accurately predicted the survival time of cervical cancer outpatients.

conclusionsThe findings of this study suggested that reductions in weight, treatment, the presence of comorbid disease, the presence of HIV, squamous cell histology type, having a history of abortion, oral contraceptive use, a large tumor size, an increase in the International Federation of Gynecologists and Obstetricians stage, an increase in metastasis number, an increase in grade, positive regional nodes, lymphatic vascular space invasion, and late stages of cancer all shortened the survival time of cervical cancer outpatients.

Indexed as

HIV InfectionsUterine Cervical NeoplasmsBayes TheoremContraceptives, OralFemaleHumansNeoplasm StagingOutpatientsPrognosisRetrospective StudiesContraceptives, OralBayesianCervical cancerIntegrated nested Laplace approximationSurvival data analysisSurvival time

Identifiers

PMID36765315
PMCPMC9921662
OpenAlexW4319939142

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LicenceCC BY
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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.