Volume 7, Issue 2 (Spring 2019)                   Iran J Health Sci 2019, 7(2): 1-8 | Back to browse issues page

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Ghavami N, Ansari H, Gharibi M, Tirgarfakheri K, Yousefzadeh A. The Relationship between Medications and Estimated Risk of Breast Cancer using Gail Model in Women Living in Southeastern Iran . Iran J Health Sci 2019; 7 (2) :1-8
URL: http://jhs.mazums.ac.ir/article-1-627-en.html
Zahedan University of Medical Sciences, Zahedan, Iran , ansarih88@gmail.com
Abstract:   (2793 Views)
Background and purpose: Breast cancer is one of the most common cancers in women all over the world. The death rate of this cancer is also increasing. It seems that medication is related to this cancer. The present study aimed at estimating the risk of this cancer using Gail Model and its relationship with medication in women.
Materials and Methods: In this cross-sectional study, 260 35-year-old women and more were selected from healthcare centers in Zahedan. The data were collected using interview and questionnaire. The risk of breast cancer was estimated by Gail Model. The medication conditions were estimated by interviewing the employees in healthcare center. The data were analyzed using independent sample t-test and linear regression.
Results: The average age of women was 49.3±8.3 years old with five-year risk, and the life time of breast cancer were 0.37±0.24 and 5.5±0.79 percent, respectively. Self-medication (P=0.043) and medication (p=0.035) had a significant relationship with estimated risk of breast cancer.
Conclusion: The risk of breast cancer in women can be influenced by medication along with socioeconomic and menstrual-reproductive factors and variables, such as ethnicity, body mass index, education, age, marriage age, nursing period, and menstrual age. The final analysis showed that consuming contraceptive pills, painkillers, and anti-inflammatory pills are the most important predictive factors in 5-year risk with cancer based on Gail Model. On the other hand, consuming painkillers and contraceptive pills were found to be the most important predictive factors in lifetime risk with cancer based on Gail Model.
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