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ORIGINAL ARTICLE
Year : 2017  |  Volume : 22  |  Issue : 1  |  Page : 135

Determining factors influencing survival of breast cancer by fuzzy logistic regression model


Department of Biostatistics and Epidemiology, Modeling in Health Research Center, Faculty of Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

Correspondence Address:
Prof. Abbas Bahrampour
Department of Biostatistics and Epidemiology, Modeling in Health Research Center, Faculty of Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman
Iran
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jrms.JRMS_405_17

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Background: Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. Materials and Methods: We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000–2007. The variables such as morphology, grade, age, and treatments(surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership(MDM). Results: The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data(MDM=0.86). Conclusion: Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.


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