Determining factors influencing survival of breast cancer by fuzzy logistic regression model
Background: Fuzzy logistic regression model can be used for determining in?uential factors of disease. Tis 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. Te 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: Te 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 in?uencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good ft 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. Te 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.
Breast cancer, fuzzy logistic regression, mean degree of membership, survival
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