Volume 1, Number 2 (4-2017)                   MCI 2017, 1(2): 13-19 | Back to browse issues page



DOI: 10.21859/mci-01023

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Farahmand L, Shojamoradi M H, Najafi M, Majidzadeh-A K. The Applicability of the Gail Model in Iranian Population. MCI. 2017; 1 (2) :13-19
URL: http://mcijournal.com/article-1-23-en.html

Abstract:   (648 Views)

Introduction: Gail model is one of the most important models for the evaluation of breast cancer risk between US white females. According to genetic diversity, there is a possibility of affecting the efficiency of the Gail model in risk assessment of breast cancer among Iranian populations. In this study, the Gail model efficiency in specifying the risk of breast cancer in Iranian population was evaluated.
Methods: This was a case-control study. The case group was formed of the referrals to Breast Cancer Research Center, Academic Center for Education Culture and Research (ACECR), who were affected by different types of aggressive cancer.
Results: A total of 416 patients with breast cancer and the same number in the control group were considered during the study. There were no meaningful statistical differences in age at menarche, age at first live birth, and nulliparous women between case and control groups. The average of five-year risk of breast cancer in the case and control groups had no statistically significant difference. Chemoprevention was only eligible for 7.2% of the patients based on 1.67% five-year risk. In addition, there was no statistically meaningful difference between comparative risk and breast cancer risk in a lifetime.
Conclusions: The low risks estimated by the Gail model among patients with breast cancer as well as the absence of meaningful statistical difference in the estimated risks by this model between the case and control groups showed that the Gail model had insufficient efficiency in determining breast cancer risk in the Iranian society.

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Type of Study: Original/Research Article | Subject: basic and translational research
Received: 2016/07/5 | Revised: 2016/11/26 | Accepted: 2016/12/2 | ePublished ahead of print: 2017/03/8

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