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Prognostic Factors for Survival in Patients with Breast Cancer Referred to Omitted Cancer Research Center in Iran

  • Baghestani, Ahmad Reza (Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences) ;
  • Shahmirzalou, Parviz (Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences) ;
  • Zayeri, Farid (Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences) ;
  • Akbari, Mohammad Esmaeil (Cancer Research Center, Shahid Beheshti University of Medical Sciences) ;
  • Hadizadeh, Mohammad (Cancer Research Center, Shahid Beheshti University of Medical Sciences)
  • Published : 2015.07.13

Abstract

Background: Breast cancer is a malignant tumor that starts from cells of the breast and is seen mainly in women. It's the most common cancer in women worldwide and is a major threat to health. The purpose of this study was to fit a Cox proportional hazards model for prediction and determination of years of survival in Iranian patients. Materials and Methods: A total of 366 patients with breast cancer in the Cancer Research Center were included in the study. A Cox proportional hazard model was used with variables such as tumor grade, number of removed positive lymph nodes, human epidermal growth factor receptor 2 (HER2) expression and several other variables. Kaplan-Meier curves were plotted and multi-years of survival were evaluated. Results: The mean age of patients was 48.1 years. Consumption of fatty foods (p=0.033), recurrence (p<0.001), tumor grade (p=0.046) and age (p=0.017) were significant variables. The overall 1- year, 3-year and 5-year survival rates were found to be 93%, 75% and 52%. Conclusions: Use of covariates and the Cox proportional hazard model are effective in predicting the survival of individuals and this model distinguished 4 effective factors in the survival of patients.

Keywords

Breast neoplasms;Cox model;proportional hazards models;survival analysis;Iran

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