Author/Authors :
Nikbakht, Roya 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 , Bahrampour, Abbas 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
Abstract :
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.
Keywords :
Breast cancer , fuzzy logistic regression , mean degree of membership , survival