ArticleBMC surgery2020
Survival analysis in gastric cancer: a multi-center study among Iranian patients.
Article in BMC surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 29 citations in OpenAlex.
- Survival analysis of time-to-death for under-five children in Somalia: Application of AFT modeling approach.Public health in practice (Oxford, England) · 2026Article
- Current status of neoadjuvant immunotherapy for the treatment of gastric cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2024Review
- Machine learning-based classifiers to predict metastasis in colorectal cancer patients.Frontiers in artificial intelligence · 2024Article
- Three possible diagnostic biomarkers for gastric cancer: miR-362-3p, miR-362-5p and miR-363-5p.Biomarkers in medicine · 2024Article
- Prediction of five-year survival among esophageal cancer patients using machine learning.Heliyon · 2023Article
- Clinical and endoscopic features of metachronous gastric cancer with possible lymph node metastasis after endoscopic submucosal dissection and Helicobacter pylori eradication.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2023Article
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- Evaluation of Pathological Response Rate and Complications of FOLFOX versus FLOT Regimen in Perioperative Chemotherapy for Resectable Gastric Cancer: A Prospective Study.Asian Pacific journal of cancer prevention : APJCP · 2023Article
- Correlation analysis of lipid metabolism genes with the immune microenvironment in gastric cancer and the construction of a novel gene signature.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023Article
- Predictors of survival outcomes among patients with gastric cancer in a leading tertiary, teaching and referral hospital in Kenya.Cancer medicine · 2023Article
- Study of LncRNA BANCR Expression in Tumor Tissues and Adjacent Normal Tissues in Gastric Cancer Patients.Advanced biomedical research · 2023Article
- Survival of gastric cancer patients in Iran: a systematic review and meta-analysis.Gastroenterology and hepatology from bed to bench · 2023Review
- Prognostic Ability of Tumor Budding Outperforms Poorly Differentiated Clusters in Gastric Cancer.Cancers · 2022Article
- Predictors of survival rate in patients with pancreatic cancer: A multi-center analytical study in Iran.Cancer reports (Hoboken, N.J.) · 2022Article
- Development of web-based dynamic nomogram to predict survival in patients with gastric cancer: a population-based study.Scientific reports · 2022Article
- Nomogram to Predict the Overall Survival of Colorectal Cancer Patients: A Multicenter National Study.International journal of environmental research and public health · 2021Article
- Impact of Clinicopathological Features on Gastric Cancer Stage According to TNM Classification.In vivo (Athens, Greece)Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGastric cancer (GC) has been considered as the 5th most common type of cancer and the third leading cause of cancer-associated death worldwide. The aim of this historical cohort study was to evaluate the survival predictors for all patients with GC using the Cox proportional hazards, extended Cox, and gamma-frailty models.
methodsThis historical cohort study was performed according to documents of 1695 individuals having GC referred to three medical centers in Iran from 2001 to 2018. First, most significant prognostic risk factors on survival were selected, Cox proportional hazards, extended Cox, gamma-frailty models were applied to evaluate the effects of the risk factors, and then these models were compared with the Akaike information criterion.
resultsThe age of patients, body mass index (BMI), tumor size, type of treatment and grade of the tumor increased the hazard rate (HR) of GC patients in both the Cox and frailty models (P < 0.05). Also, the size of the tumor and BMI were considered as time-varying variables in the extended Cox model. Moreover, the frailty model showed that there is at least an unknown factor, genetic or environmental factors, in the model that is not measured (P < 0.05).
conclusionsSome prognostic factors, including age, tumor size, the grade of the tumor, type of treatment and BMI, were regarded as indispensable predictors in patients of GC. Frailty model revealed that there are unknown or latent factors, genetic and environmental factors, resulting in the biased estimates of the regression coefficients.
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