ArticleBMC women's health2023
Assessing survival time of outpatients with cervical cancer: at the university of Gondar referral hospital using the Bayesian approach.
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.
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.
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.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Common predictors of cervical cancer related mortality in Ethiopia. A systematic review and meta-analysis.BMC public health · 2024Pooled it
- Burden and predictors of cervical cancer mortality in Sub-Saharan Africa: a systematic review and meta-analysis.Infectious agents and cancer · 2026Review
- Prognostic value of glioma-associated oncogene homolog 1 and SET domain-containing protein 2 immunohistochemical scores in locally advanced cervical cancer.Oncology letters · 2026Article
- Article
- Time to Death and Its Predictor Among Outpatients With COPD: A Retrospective Cohort Study in Northwestern Ethiopia.Health science reports · 2025Article
- Deciphering the Expression, Functional Role, and Prognostic Significance ofJournal of obstetrics and gynaecology of India · 2025Article
- Improving cervical cancer continuum of care towards elimination in Ethiopia: a scoping review.Cancer causes & control : CCC · 2024Article
- Article
- Analysis of the survival time of patients with heart failure with reduced ejection fraction: a Bayesian approach via a competing risk parametric model.BMC cardiovascular disorders · 2024Article
- Predictors of cervical tumour size for outpatients with cervical cancer at the University of Gondar referral hospital: a retrospective study design.European journal of medical research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
What OpenQuestion holds
Registered trials
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.