ArticleAsian Pacific journal of cancer prevention : APJCP2018
A Spatial Survival Model in Presence of Competing Risks for Iranian Gastrointestinal Cancer Patients
Article in Asian Pacific journal of cancer prevention : APJCP, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- A Spatial Survival Model for Risk Factors of Under-Five Child Mortality in Kenya.International journal of environmental research and public health · 2021Article
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5 authors.
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Abstract
Background: Gastrointestinal cancer is one of the common causes of death from cancer in Iran. Survival analysis is usually used to detect prognostic factors of time to death from gastrointestinal cancers. The use of ordinary survival models, in the presence of competing risks and/or when data is collected within geographic areas, may lead to distorting the results. Therefore, the aim of this study is to use the spatial survival models in the presence of competing risks to assess the risk factors affecting the survival time of gastrointestinal cancer patients. Methods: The data in this study was collected from 602 patients who were diagnosed with gastrointestinal cancer in Golestan and Mazandaran provinces registered in Iran’s National Institute of Health Research from 2002 through 2007 and were followed up to July 2017. The data was analyzed using the cause-specific hazard frailty model with multivariate conditional autoregressive distribution for frailties in the presence of competing risks (death from gastrointestinal cancer, heart disease, and other causes) via OpenBUGS software. Results: The hazard of death from gastrointestinal cancer in men patients, patients who lived in rural areas, patients whose relatives did not have a history of cancer, patients who did not undergo surgery, and patients with gastric cancer was significantly higher than others. Based on the deviance information criterion (DIC), frailty models and spatial frailty models seemed better than no-frailty model and non-spatial frailty model, respectively. Conclusions: This study showed that the use of the spatial frailty term in the model helps better fit the model. Also, the spatial pattern in the figures suggests the necessity of presence of some still missing, spatially varying covariates relevant for time to death from gastrointestinal cancer, heart disease, or other causes.
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