|Year : 2015 | Volume
| Issue : 3 | Page : 207-211
Lifetime and 5 years risk of breast cancer and attributable risk factor according to Gail model in Iranian women
Abolfazl Mohammadbeigi1, Narges Mohammadsalehi2, Razieh Valizadeh3, Zeinab Momtaheni3, Mohsen Mokhtari4, Hossein Ansari5
1 Department of Epidemiology and Biostatistics, School of Health, Health Policy and Promotion Research Center, Qom University of Medical Sciences, Qom, Iran
2 Department of Research Vice-chancellor, Qom University of Medical Sciences, Qom, Iran
3 Student Research Committee, Qom University of Medical Sciences, Qom, Iran
4 Department Health Vice-Chancellor, Arak University of Medical Sciences, Arak, Iran
5 Health Promotion Research Center, Department of Epidemiology and biostatistics, Zahedan University of Medical Sciences, Zahedan, Iran
|Date of Submission||31-Mar-2015|
|Date of Decision||16-May-2015|
|Date of Acceptance||21-May-2015|
|Date of Web Publication||6-Jul-2015|
Health Promotion Research Center, Department of Epidemiology and biostatistics, Zahedan University of Medical Sciences, Zahedan
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Introduction: Breast cancer is the most commonly diagnosed cancers in women worldwide and in Iran. It is expected to account for 29% of all new cancers in women at 2015. This study aimed to assess the 5 years and lifetime risk of breast cancer according to Gail model, and to evaluate the effect of other additional risk factors on the Gail risk. Materials and Methods: A cross sectional study conducted on 296 women aged more than 34-year-old in Qom, Center of Iran. Breast Cancer Risk Assessment Tool calculated the Gail risk for each subject. Data were analyzed by paired t-test, independent t-test, and analysis of variance in bivariate approach to evaluate the effect of each factor on Gail risk. Multiple linear regression models with stepwise method were used to predict the effect of each variable on the Gail risk. Results: The mean age of the participants was 47.8 ± 8.8-year-old and 47% have Fars ethnicity. The 5 years and lifetime risk was 0.37 ± 0.18 and 4.48 ± 0.925%, respectively. It was lower than the average risk in same race and age women (P < 0.001). Being single, positive family history of breast cancer, positive history of biopsy, and radiotherapy as well as using nonhormonal contraceptives were related to higher lifetime risk (P < 0.05). Moreover, a significant direct correlation observed between lifetime risk and body mass index, age of first live birth, and menarche age. While an inversely correlation observed between lifetimes risk of breast cancer and total month of breast feeding duration and age. Conclusion: Based on our results, the 5 years and lifetime risk of breast cancer according to Gail model was lower than the same race and age. Moreover, by comparison with national epidemiologic indicators about morbidity and mortality of breast cancer, it seems that the Gail model overestimate the risk of breast cancer in Iranian women.
Keywords: Breast cancer, Gail model, Iran, malignancy, predictor, risk factors
|How to cite this article:|
Mohammadbeigi A, Mohammadsalehi N, Valizadeh R, Momtaheni Z, Mokhtari M, Ansari H. Lifetime and 5 years risk of breast cancer and attributable risk factor according to Gail model in Iranian women. J Pharm Bioall Sci 2015;7:207-11
|How to cite this URL:|
Mohammadbeigi A, Mohammadsalehi N, Valizadeh R, Momtaheni Z, Mokhtari M, Ansari H. Lifetime and 5 years risk of breast cancer and attributable risk factor according to Gail model in Iranian women. J Pharm Bioall Sci [serial online] 2015 [cited 2019 Oct 22];7:207-11. Available from: http://www.jpbsonline.org/text.asp?2015/7/3/207/160020
Breast cancer is the most commonly diagnosed cancers in women worldwide and it is alone expected to account for 29% of all new cancers in women at 2015, ,, but there is wide variation in breast cancer incidence rate internationally.  It is estimated that more than 2,31,000 new cases including 60,290 cases of carcinoma in situ of the female breast and 63,440 cases of melanoma in situ will be diagnosed annually. Moreover, more than 40,000 deaths occurred due to breast cancer in United States at 2015.  In Iranian women, breast cancer is the most common malignancy,  and responsible for more than 24% of all cancers. , There is an increasing trend in breast cancer mortality in Iran in recent decades. , Moreover, Iranian women affect to breast cancer at least one decade younger than their counterparts in developed countries and 96% of breast cancer cases were diagnosed in stage II or III. ,
Todays, there has been a growing interest in developing methods to estimate the risk of breast cancer based on women's risk factors profile as other chronic diseases. The Gail et al., model  is one the first model that is used for risk assessment of breast cancer.  This model is helpful to aid in decision making regarding potential breast cancer prevention options, including chemoprevention with tamoxifen.  The Gail model had used a baseline age-specific breast cancer risks beside a multivariate relative risk component to estimate the absolute risk of invasive or in situ breast cancer. Woman's age at first live birth, her menarche' age, the number of previous benign breast biopsies, whether or not atypical hyperplasia had been identified on any of the biopsies, and the total number of breast cancer in first-degree relatives are the factors used in risk assessment. , This model is validated in some studies with different demographic characteristics such as race, age and cultural ethnicity and nationality. ,,, Nevertheless, the accuracy of the model in Asian women is needed to be assessed. Since, according to the other results some risk factors including breast density,  could be weighted in Gail model. Therefore, due to the breast cancer is the most important leading cause of cancer death in women aged 20-59 years. ,, This model is helpful and used to estimate the expected breast cancers morbidity in defined populations.  Therefore, this study aimed to assess the 5 years and lifetime risk of breast cancer according to Gail model, and to evaluate effect of body mass index (BMI), using hormone contraceptives, Iranian ethnicity, live and death birth number, having breastfeeding and months of breastfeeding on the Gail risk as additional risk factors.
| Materials and Methods|| |
A cross-sectional study conducted on 296 women aged more than 34-year-old at winter of 2014 in Qom, Center of Iran. The study population was women that referring to health centers for seeking the health cares. To select a random sample, multistage sampling method was used. First according to cluster sampling, the city divided into four districts, and one of the health centers in each district had been selected randomly. Then eligible women entered in the study at the selected health centers according to systematic sampling among all health folders. Women who have more than 34-year-old were eligible for the study and whose with diagnosed breast and ovarian cancers were excluded. According to Gail model, data of influencing factors including age, menarche age, age at the first live birth, number of biopsies and biopsy history, family history of breast cancer, other cancer history and race on absolute risk of breast cancer collected. Moreover, data of other related factors such as BMI, breastfeeding, using hormone contraceptives and total month of breastfeeding collected.
The Gail risk was for each subject was calculated by breast cancer risk assessment tool (BCRAT),  that is an interactive tools designed by National Cancer Institute and National Surgical Adjuvant Breast and Bowel Project for estimating the women's risk of developing invasive breast cancer. ,, The Gail risk for each study subjects calculated as four types including 5 years Gail risk, lifetimes Gail risk, 5 years risk and lifetimes risk for same age and race. Data were analyzed by paired t-test, independent t-test, and analysis of variance in bivariate approach. Multiple linear regression model was used to predict the effect of each variable on the Gail risk. Forward stepwise method was applied in entering variables in the model after checking the collinearity. The goodness of fitness of the multivariate model had checked by residual plots and R square. All statistical analysis was conducted in the SPSS software (Chicago Inc.).
Informed consent was taken from all the eligible subjects and the study protocol approved by Ethical Committee of Qom University of Medical Sciences.
| Results|| |
The mean age of the participants in the study was 47.8 ± 8.8 years old with minimum and maximum as 35 and 73 years, respectively. From the total participants in the study, 89.2% (264 mothers) were households and 47% were Fars and 42.9% Turkish. The prevalence of using overall contraceptive prevalence and intrauterine device was 34.8% and 7.1%, respectively. As described in the [Table 1], the 5 years and lifetime Gail risk was 0.37 ± 0.18 and 4.48 ± 0.925, respectively. Moreover, the paired t-test showed that the 5 years and lifetime Gail risk was lower than the average risk in the same race and age women (P < 0.001). More details about studied variables and demographic characteristics are showed in [Table 1].
According to results of [Table 2], history of breast cancer in family and Fars ethnicity were related to higher 5 years Gail risk. But being single, positive family history of breast cancer, positive history of biopsy, and radiotherapy as well as using nonhormonal contraceptives were related to higher lifetime Gail risk (P < 0.05). Moreover, according to [Table 3], a positive correlation was observed among age, marriage age and age of first live birth with 5 years Gail risk. In addition, a significant direct correlation observed between lifetime Gail risk and age of first live birth and menarche age. While the correlation between lifetimes Gail risk and total month of breastfeeding duration, BMI and age was inversely.
|Table 2: Differences in gail risks of studied women based on demographic characteristics|
Click here to view
According to [Table 3] findings, family history of breast cancer, biopsy history, age, and age of first live birth were the most important predictors of 5 years Gail risk model. Moreover, lifetime Gail risk was associated by family history of breast cancer, biopsy history, age, and age of first live birth, history of radiotherapy, and other cancers. In addition, the effect of family history of breast cancer in lifetime risk was more than two-fold of history of other cancers and three-fold of radiotherapy history.
| Discussion|| |
The 5 years and lifetime Gail risk was 0.37% and 4.48%, respectively. It can interpreted that the risk of affecting to breast cancer in Iranian women with more than 34-year-old is 3.7/1000 women in 5 years and average 74/1,00,000 annually. Moreover, the lifetime risk of incidence for breast cancer is 44.8/1000 women. Thus, the lifetime risk of breast cancer is 44.8/1000. According to the Iranian reports the crude incidence rate of breast cancer was 22.4 in 1,00,000 in the year 1998.  According to a national study the breast cancer mortality increased 151.4% between 1995 and 2004 from 1.40 to 3.52/100,000.  Moreover, according to a review study,  the incidence rate of breast cancer in Iranian women was 22/1,00,000 and the prevalence in this population was calculated as 120/1,00,000 people. , It can be concluded that the risk of breast cancer according to Gail model is higher than the national reports. On the other hand, the Gail model overestimated the risk of breast cancer in Iranian women more than threefold. The mean age of participants in our study was 47.8 years. Other study,  reported the age of breast cancer diagnosis in 48.4 years. Therefore, these differences cannot be because of age of participants. Although based on our results, the 5 years, and lifetime Gail risk was lower than the average risk in same race and age women. In another study, the 5 years invasive breast cancer risks for African American women by using BCRAT calculated 14.5%.  Nevertheless, this overestimation of Gail risk of breast cancer compared to national reports could be because of weak surveillance and under reporting of breast cancer cases.
According to the results, positive family history of breast cancer and Fars ethnicity were related with higher 5 years Gail risk. Moreover, being single, positive family history of breast cancer, positive history of biopsy and radiotherapy as well as using nonhormonal contraceptives were related to higher lifetime Gail risk. Moreover, a significant direct correlation observed between lifetime Gail risk and BMI, age of first live birth and menarche age. While the correlation between lifetimes Gail risk and total month of breastfeeding duration and age was inversely. Therefore, as other studies suggested adding additional risk factors for breast cancer in Gail model can be useful to increase the accuracy of model in different race, ethnicity, and geographical areas.  In addition, differences in morbidity and mortality due to breast cancer also showed in 2015 statistics of cancer.  Due to calculating the Gail risk from specific factors based on Gail model, BMI, total month of breastfeeding duration, and Fars ethnicity removed from the model. It is considerable that risk prediction models for breast cancer that used a small number of risk factors in estimating of absolute risk of breast cancer are better calibrated. Since the prevalence of breast cancer risk factors is different in studied areas, these factors can affect the accuracy of Gail model in different geographic districts.  Moreover, changes in female reproductive patterns and increase in rapid detection by mammography screening are other related factors that increased the number of breast cancer incidence will be include in Gail model for improve in prediction of risk. Our results showed that using hormonal contraceptives are related with lower risk of breast cancer. Barlow et al., suggested that breast density and use of hormone therapy as strongly risk factors should include in Gail model.  Other studies in Iran showed the effect of other factors including education, late menopause, history of induced abortion, BMI as risk factors for breast cancer while, having more episodes of full term pregnancy, longer duration of breastfeeding, and parity more than two are protective factors. ,, Therefore, the effect of these factors on risk estimation based on Gail model is removed and modified model would be needed.
However, since this study conducted in healthy women to evaluate the 5 years and lifetime risk of breast cancer, the validation of Gail model is conducted by comparing the risk of diseases with epidemiological indexes of breast cancer calculated by cancer registry data or population-based studies. Therefore, it suggested that case-control study conducted to estimate the effects of other risk factors of breast cancer such as obesity, marital status, using hormone contraceptives and effects of Fars rather than Turkish ethnicity as well as total month of breastfeeding or number of lived birth.  Therefore, regarding to increasing trend of breast cancer especially in higher stage,  the prevention studies for risk assessment and control of disease is necessary.
| Conclusion|| |
Based on our results, the 5 years, and lifetime risk of breast cancer according to Gail model is lower than the same race and age. Moreover, by comparison with national epidemiologic indicators about morbidity and mortality of breast cancer, it seems that the Gail model overestimate the risk of breast cancer in Iranian women to threefold. In addition, the modified Gail model for Iranian women would be presented by including the effect of known risk factors such as Fars ethnicity, using hormonal contraceptives and breastfeeding month.
| Acknowledgments|| |
The authors are very grateful for research Vice-Chancellor of Qom University of Medical Sciences as well as all women who participate in the study.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin 2015;65:5-29.
Group, U.C.S.W. United States Cancer Statistics: 1999-2010 Incidence and Mortality Web-based Report. Atlanta, GA: Department of Health and Human Services, Centers for Disease Control and Prevention, and National Cancer Institute; 2014.
Moshfeghi K, Mohammadbeigi A. Comparison the effects of two educational methods on knowledge, attitude and practices of Arak physicians about breast cancer. Pak J Biol Sci 2010;13:901-5.
Decarli A, Calza S, Masala G, Specchia C, Palli D, Gail MH. Gail model for prediction of absolute risk of invasive breast cancer: Independent evaluation in the Florence-European Prospective Investigation Into Cancer and Nutrition cohort. J Natl Cancer Inst 2006;98:1686-93.
Kolahdoozan S, Sadjadi A, Radmard AR, Khademi H. Five common cancers in Iran. Arch Iran Med 2010;13:143-6.
Montazeri A, Vahdaninia M, Harirchi I, Harirchi AM, Sajadian A, Khaleghi F, et al.
Breast cancer in Iran: Need for greater women awareness of warning signs and effective screening methods. Asia Pac Fam Med 2008;7:6.
Mousavi SM, Gouya MM, Ramazani R, Davanlou M, Hajsadeghi N, Seddighi Z. Cancer incidence and mortality in Iran. Ann Oncol 2009;20:556-63.
Taghavi A, Fazeli Z, Vahedi M, Baghestani AR, Pourhoseingholi A, Barzegar F, et al.
Increased trend of breast cancer mortality in Iran. Asian Pac J Cancer Prev 2012;13:367-70.
Harirchi I, Kolahdoozan S, Karbakhsh M, Chegini N, Mohseni SM, Montazeri A, et al.
Twenty years of breast cancer in Iran: Downstaging without a formal screening program. Ann Oncol 2011;22:93-7.
Gail MH, Brinton LA, Byar DP, Corle DK, Green SB, Schairer C, et al.
Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst 1989;81:1879-86.
Barlow WE, White E, Ballard-Barbash R, Vacek PM, Titus-Ernstoff L, Carney PA, et al.
Prospective breast cancer risk prediction model for women undergoing screening mammography. J Natl Cancer Inst 2006;98:1204-14.
Rockhill B, Spiegelman D, Byrne C, Hunter DJ, Colditz GA. Validation of the Gail et al.
model of breast cancer risk prediction and implications for chemoprevention. J Natl Cancer Inst 2001;93:358-66.
Chay WY, Ong WS, Tan PH, Jie Leo NQ, Ho GH, Wong CS, et al.
Validation of the Gail model for predicting individual breast cancer risk in a prospective nationwide study of 28,104 Singapore women. Breast Cancer Res 2012;14:R19.
Costantino JP, Gail MH, Pee D, Anderson S, Redmond CK, Benichou J, et al.
Validation studies for models projecting the risk of invasive and total breast cancer incidence. J Natl Cancer Inst 1999;91:1541-8.
Spiegelman D, Colditz GA, Hunter D, Hertzmark E. Validation of the Gail et al.
model for predicting individual breast cancer risk. J Natl Cancer Inst 1994;86:600-7.
Mousavi SM, Montazeri A, Mohagheghi MA, Jarrahi AM, Harirchi I, Najafi M, et al.
Breast cancer in Iran: An epidemiological review. Breast J 2007;13:383-91.
Gail MH, Costantino JP, Pee D, Bondy M, Newman L, Selvan M, et al.
Projecting individualized absolute invasive breast cancer risk in African American women. J Natl Cancer Inst 2007;99:1782-92.
Shamsa A, Mohagheghi M. Final Report of the National Project for Cancer Registry. Tehran: Islamic Republic of Iran, Cancer Institute; 2002.
Etemadi A, Sadjadi A, Semnani S, Nouraie SM, Khademi H, Bahadori M. Cancer registry in Iran: A brief overview. Arch Iran Med 2008;11:577-80.
Sadjadi A, Nouraie M, Ghorbani A, Alimohammadian M, Malekzadeh R. Epidemiology of breast cancer in the Islamic Republic of Iran: First results from a population-based cancer registry. East Mediterr Health J 2009;15:1426-31.
Naieni KH, Ardalan A, Mahmoodi M, Motevalian A, Yahyapoor Y, Yazdizadeh B. Risk factors of breast cancer in north of Iran: A case-control in Mazandaran Province. Asian Pac J Cancer Prev 2007;8:395-8.
Ebrahimi M, Vahdaninia M, Montazeri A. Risk factors for breast cancer in Iran: A case-control study. Breast Cancer Res 2002;4:R10.
Farhadi M, Daneshi A, Tabatabaii A, Sotoudeh M, Salek-Moghaddam A, Shamshiri A. Assessment of certain breast cancer risk factors during reproductive age in women in Mashhad (2002-2003). Razi J Med Sci 2004;11:587-95.
[Table 1], [Table 2], [Table 3]