Assessing breast cancer risk estimates based on the gail model and its predictors in qatari women

Bener A., Çatan F., El Ayoubi H. R., Acar A., Ibrahim W. H.

Journal of Primary Care and Community Health, vol.8, no.3, pp.180-187, 2017 (Scopus) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 8 Issue: 3
  • Publication Date: 2017
  • Doi Number: 10.1177/2150131917696941
  • Journal Name: Journal of Primary Care and Community Health
  • Journal Indexes: Scopus
  • Page Numbers: pp.180-187
  • Keywords: breast cancer, Gail model risk assessment, lifestyle, predictor, risk factors, consanguinity, Arab women
  • Istanbul Medipol University Affiliated: Yes


Background: The Gail model is the most widely used breast cancer risk assessment tool. An accurate assessment of individual’s breast cancer risk is very important for prevention of the disease and for the health care providers to make decision on taking chemoprevention for high-risk women in clinical practice in Qatar. Aim: To assess the breast cancer risk among Arab women population in Qatar using the Gail model and provide a global comparison of risk assessment. Subjects and Methods: In this cross-sectional study of 1488 women (aged 35 years and older), we used the Gail Risk Assessment Tool to assess the risk of developing breast cancer. Sociodemographic features such as age, lifestyle habits, body mass index, breast-feeding duration, consanguinity among parents, and family history of breast cancer were considered as possible risks. Results: The mean age of the study population was 47.8 ± 10.8 years. Qatari women and Arab women constituted 64.7% and 35.3% of the study population, respectively. The mean 5-year and lifetime breast cancer risks were 1.12 ± 0.52 and 10.57 ± 3.1, respectively. Consanguineous marriage among parents was seen in 30.6% of participants. We found a relationship between the 5-year and lifetime risks of breast cancer and variables such as age, age at menarche, gravidity, parity, body mass index, family history of cancer, menopause age, occupation, and level of education. The linear regression analysis identified the predictors for breast cancer in women such as age, age at menarche, age of first birth, family history and age of menopausal were considered the strong predictors and significant contributing risk factors for breast cancer after adjusting for ethnicity, parity and other variables. Conclusion: The current study is the first to evaluate the performance of the Gail model for Arab women population in the Gulf Cooperation Council. Gail model is an appropriate breast cancer risk assessment tool for female population in Qatar.