ArticleJournal of gastrointestinal cancer2022
A Case Study on Modeling the Time to Recurrence of Gastric Cancer Patients.
Article in Journal of gastrointestinal cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Identifying risk factors for recurrent multidrug resistant tuberculosis based on patient's record data from 2016 to 2021: retrospective study.Scientific reports · 2024Article
- A practical recurrence risk model based on Lasso-Cox regression for gastric cancer.Journal of cancer research and clinical oncology · 2023Article
- Herbal therapies in gastrointestinal and hepatic disorders: An evidence-based clinical review.Frontiers in pharmacology · 2022Review
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGastric cancer is a malignant tumor of the stomach and it is one of the leading causes of death worldwide. The study aimed to model the time to first recurrence of gastric cancer patients at the Tikur Anbesa specialized hospital.
methodsThe data for this study were gastric cancer patients followed up from January 1, 2013 to February 29, 2020 at Tikur Anbesa Specialized Hospital, Oncology Center, Addis Ababa. We used Weibull, log-logistic and lognormal as baseline hazard functions with the gamma and the inverse Gaussian frailty distributions. Data analyzed with the statistical software R.
resultsThe median recurrence time of the patients was about 23.96 months with a maximum recurrence time of 60.81 months, of which about 61.2% had first recurrences of gastric cancer. The clustering effect is significant in modeling the time to recurrence of gastric cancer. According to the result of the log-logistic inverse Gaussian frailty model, the sex of the patient, the tumor size, smoking habit, the treatment carried out, the vascular invasion, the stage of the disease, the helicobacter pylori infection and the histological type were the significant prognostic factors at 5% level of significance.
conclusionInverse Gaussian frailty model is the model that best describes the time to recurrence of the gastric cancer data set. Gender of the patients, tumor size, treatment taken, vascular invasion, disease stage, helicobacter pylori infection and histological type were the determining prognostic factors. This requires measures to improve patient health and prevent relapse based on significant risk factors, and particular attention should be paid to patients with such factors.
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