Modeling the Spatial Distribution of Cancer and Determining the Associated Risk Factors

Abstract

Background: Cancer is the second leading cause of death globally. Despite developing countries including Ethiopia continuing to shoulder the greatest burden, insufficient research has been conducted to determine geographical and other characteristic effects. The main objective of this study was to assess the distribution and risk of cancer and determine the effects of some common clinical patient characteristics on current patient status by taking into account the spatial effect. Methods: The data for this study were obtained from the oncology ward of Felege Hiwot Referral Hospital, Bahir Dar, Ethiopia. About 415 cancer patients were included in the study. Spatial mixed ordinal logistic regression model was used to explore the geographical patterns of the incidence of cancer and identify the risk factors. Results: The findings of this study show that only 1.45% of patients were cured and 46.02% improved, whereas the rest have shown no change and even worse status after treatment. The estimated odds of patients who received chemotherapy was 4.284 times the estimated odds of patients who received palliative care. Prognostic factor (stage of cancer tumor), complication of cancer such as anemia during diagnosis, and treatment of patients given in the hospital had significant effect on the patient status. Conclusion: Patients without anemia were more likely to be cured and improved than patients with anemia during diagnosis. Most of the patients had advanced stage (IV) of cancer tumor, which dismantles the capability of the treatment to be less effective. There was negative spatial effect on the incidence of cancer, indicating that districts with higher cancer incidence were usually surrounded by districts with lower incidence.