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dc.contributor.authorAghil Mollaei
dc.contributor.authorNouraddin Mousavinasab
dc.contributor.authorJamshid Yazdani-Charati
dc.contributor.authorMohammad Eslami-Jouibari
dc.contributor.otherMSc Student in Biostatistics, Faculty of Health, Mazandaran University of Medical Sciences, Sari, Iran
dc.contributor.otherAssociate Professor, Department of Biostatistics, Health Sciences Research Center, Mazandaran University of Medical Sciences, Sari, Iran
dc.contributor.otherProfessor, Department of Biostatistics, Health Sciences Research Center, Mazandaran University of Medical Sciences, Sari, Iran
dc.contributor.otherAssistant Professor, Department of Internal Medicine, Sari Imam Khomeini Hospital, Cancer Research Center, Mazandaran University of Medical Sciences, Sari, Iran
dc.date.accessioned2023-12-11T09:06:01Z
dc.date.accessioned2025-10-08T08:24:36Z
dc.date.available2025-10-08T08:24:36Z
dc.date.issued01-12-2023
dc.identifier.urihttp://digilib.fisipol.ugm.ac.id/repo/handle/15717717/35821
dc.description.abstractBackground and purpose: Stomach cancer is a multifactorial disease that may be influenced by many factors, including environmental and genetic factors. Therefore, it is important to investigate and recognize the prognostic factors in the survival of this disease. The purpose of this study was to investigate the factors affecting the survival of gastric cancer by parametric and semi-parametric regression methods and finally to fit the best model among these models. Materials and methods: A historical cohort study on 193 patients with gastric cancer in Mazandaran province 2011-2014 was carried out. Demographic, clinical and therapeutic information of patients were collected. The Schoenfeld test was utilized to evaluate the assumption of proportional hazards, while Cox-Snell residuals were employed to assess the adequacy of the model. The STATA software (v. 14) was used to analyze the data. The significance level of the tests was considered 0.25 for univariate analysis. Results: 30% and 70% of the patients were women and men, respectively. The average age at diagnosis of the patients was 64.92±14.04 years. The mean and median survival time were 21.92 and 8.06 months, respectively, with a standard error of 2.57 and 1.20. Based on Akanke’s information criterion and Cox-Snell's residuals, the log-logistic model was selected as the optimal model. The results of the log-logistic model showed that the variables of body mass index (acceleration factor= 1.11 and P= 0.003) and in terms of the type of treatment, the combination of chemotherapy and surgery compared to surgery (acceleration factor=3.12 and P=0.028) and three types of combined treatment of radiotherapy, chemotherapy and surgery to surgery (acceleration factor=7.58 and P=0.020) and kidney disease (acceleration factor=0.20 and P=0.014) were factors affecting survival. Conclusion: Despite the preference of the majority of researchers to utilize the Cox model, accelerated failure models can serve as a viable alternative to the Cox model in comparable circumstances
dc.language.isoEN
dc.publisherMazandaran University of Medical Sciences
dc.subject.lccMedicine
dc.titleComparison of efficiency of Cox Proportional Hazards Model and Accelerated Failure Time Models in Determining Survival Factors in Gastric Cancer Patients
dc.typeArticle
dc.description.keywordscox proportional hazards model
dc.description.keywordsaccelerated failure model
dc.description.keywordsakanke’s information criterion
dc.description.keywordscox snell residuals
dc.description.keywordssurvival
dc.description.keywordsgastric cancer
dc.description.keywordsparametric regression
dc.description.pages192-202
dc.title.journalJournal of Mazandaran University of Medical Sciences
dc.identifier.e-issn1735-9279
dc.identifier.oai3b341ae3e2b7428ca2123fdeb0a186a9
dc.journal.infoVolume 33, Issue 2


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