Discriminatory Accuracy of the Gail Model for Breast Cancer Risk Assessment among Iranian Women
Abstract
Background: The Gail model is the most well-known tool for breast cancer risk assessment worldwide. Although it was validated in various Western populations, inconsistent results were reported from Asian populations. We used data from a large case-control study and evaluated the discriminatory accuracy of the Gail model for breast cancer risk assessment among the Iranian female population.
Methods: We used data from 942 breast cancer patients and 975 healthy controls at the Cancer Institute of Iran, Tehran, Iran, in 2016. We refitted the Gail model to our case-control data (the IR-Gail model). We compared the discriminatory power of the IR-Gail with the original Gail model, using ROC curve analyses and estimation of the area under the ROC curve (AUC).
Results: Except for the history of biopsies that showed an extremely high relative risk (OR=9.1), the observed ORs were similar to the estimates observed in Gail's study. Incidence rates of breast cancer were extremely lower in Iran than in the USA, leading to a lower average absolute risk among the Iranian population (2.78, ±SD 2.45). The AUC was significantly improved after refitting the model, but it remained modest (0.636 vs. 0.627, ΔAUC = 0.009, bootstrapped P=0.008). We reported that the cut-point of 1.67 suggested in the Gail study did not discriminate between breast cancer patients and controls among the Iranian female population.
Conclusion: Although the coefficients from the local study improved the discriminatory accuracy of the model, it remained modest. Cohort studies are warranted to evaluate the validity of the model for Iranian women.
1. GLOBOCAN (2018). Estimated number of new cancer cases in 2018, worldwide, all cancers, females, all ages. https://acsjournals.onlinelibrary.wiley.com/doi/full/10.3322/caac.21492
2. Rouhollahi MR, Mohagheghi MA, Mohammadrezai N, et al (2014). Situation analysis of the National Comprehensive Cancer Control Program (2013) in the I. R. of Iran; assessment and recommendations based on the IAEA imPACT mission. Arch Iran Med, 17(4):222-31.
3. Mohebbi E, Nahvijou A, Hadji M, et al (2017). Iran Cancer Statistics in 2012 and Projection of Cancer Incidence by 2035. Basic & Clinical Cancer Research 9:3-22.
4. Rashidian H, Daroudi R, Ghiasvand R, Harirchi I, Zendehdel K (2013). Prevalence and Incidence of premenopausal and postmenopausal breast cancer in Iran in 2010. Basic & Clinical Cancer Research, 5:2-10.
5. Ghiasvand R, Adami H-O, Harirchi I, et al (2014). Higher incidence of premenopausal breast cancer in less developed countries; myth or truth? BMC cancer, 14:343.
6. El Saghir NS, Khalil MK, Eid T, El Kinge AR, et al (2007). Trends in epidemiology and management of breast cancer in developing Arab countries: a literature and registry analysis. Int J Surg, 5(4):225-33.
7. Myers ER, Moorman P, Gierisch JM, et al (2015). Benefits and harms of breast cancer screening: a systematic review. JAMA, 314:1615-1634.
8. Nyström L, Bjurstam N, Jonsson H, et al (2017). Reduced breast cancer mortality after 20+ years of follow-up in the Swedish randomized controlled mammography trials in Malmö, Stockholm, and Göteborg. J Med Screen, 24(1):34-42.
9. Tabár L, Vitak B, Chen TH-H, et al (2011). Swedish two-county trial: impact of mammographic screening on breast cancer mortality during 3 decades. Radiology, 260(3):658-63.
10. Akbari ME, Haghighatkhah H, Shafiee M, et al (2012). Mammography and ultrasonography reports compared with tissue diagnosis--an evidence based study in Iran, 2010. Asian Pac J Cancer Prev, 13(5):1907-10.
11. Barfar E, Rashidian A, Hosseini H, et al (2014). Cost-effectiveness of mammography screening for breast cancer in a low socioeconomic group of Iranian women. Arch Iran Med, 17(4):241-5.
12. Warner E (2011). Clinical practice. Breast-cancer screening. N Engl J Med, 365:1025-32.
13. Mokarian F, Mokarian S, Ramezani A (2013). Relations of disease-free survival and overall survival with age and primary metastases in patients with breast cancer. Journal of Isfahan Medical School, 31(225):112-20.
14. Amir E, Freedman OC, Seruga B, Evans DG (2010). Assessing women at high risk of breast cancer: a review of risk assessment models. J Natl Cancer Inst, 102(10):680-91.
15. Zhao J, Song X, Leng L, et al (2017). Evaluation of risk assessment tools for breast cancer screening in Chinese population. Int J Clin Exp, 10:3582-3587.
16. Gail MH, Brinton LA, Byar DP, et al (1989). Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst, 81(24):1879-86.
17. Costantino JP, Gail MH, Pee D, Anderson S, et al (1999). Validation Studies for Models Projecting the Risk of Invasive and Total Breast Cancer Incidence. J Natl Cancer Inst, 91(18):1541-8.
18. Chay WY, Ong WS, Tan PH, et al (2012). Validation of the Gail model for predicting individual breast cancer risk in a prospective nationwide study of 28,104 Singapore women. Breast Cancer Res, 14:R19.
19. Ulusoy C, Kepenekci I, Kose K, Aydintug S, Cam R (2010). Applicability of the Gail model for breast cancer risk assessment in Turkish female population and evaluation of breastfeeding as a risk factor. Breast Cancer Res Treat, 120(2):419-24.
20. Abdulbari B, Funda Ç, Hanadi REA, et al (2017). Assessing Breast Cancer Risk Estimates Based on the Gail Model and Its Predictors in Qatari Women. J Prim Care Community Health, 8(3):180-187.
21. Ewaid S (2017). Breast cancer risk assessment by Gail Model in women of Baghdad. Alexandria Journal of Medicine, 53 (2):183-186.
22. Anothaisintawee T, Teerawattananon Y, Wiratkapun C, et al (2012). Risk prediction models of breast cancer: a systematic review of model performances. Breast Cancer Res Treat, 133(1):1-10.
23. Wang X, Huang Y, Li L, et al (2018). Assessment of performance of the Gail model for predicting breast cancer risk: a systematic review and meta-analysis with trial sequential analysis. Breast Cancer Res, 20(1):18.
24. Meads C, Ahmed I, Riley RD (2012). A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance. Breast Cancer Res Treat, 132(2):365-77.
25. Gail MH, Pfeiffer RM (2005). On criteria for evaluating models of absolute risk. Biostatistics, 6(2):227-39.
26. Wu Y, Liu J, Rio AMd, et al (2015). Developing a clinical utility framework to evaluate prediction models in radiogenomics. Proc SPIE Int Soc Opt Eng ,9416:941617.
27. Darabi H, Czene K, Zhao W, et al (2012). Breast cancer risk prediction and individualised screening based on common genetic variation and breast density measurement. Breast Cancer Res, 14(1):R25.
28. Eriksson M, Czene K, Pawitan Y, et al (2017). A clinical model for identifying the short-term risk of breast cancer. Breast Cancer Res, 19(1):29.
29. Hosseinpour R, HAJI NE, Ranjpoor F, et al (2011). Evaluation of the risk of breast cancer, based on the Gail model, in women of more than 35 years old: at health centers of Yasouj during 2010-2011. Iranian Journal of Surgery, 20(3):13-20.
30. Khazaee-Pool M, Majlessi F, Nedjat S, et al (2016). Assessing Breast Cancer Risk among Iranian Women Using the Gail Model. Asian Pac J Cancer Prev, 17(8):3759-62.
31. Mirghafourvand M, Mohammad-Alizadeh-Charandabi S, Ahmadpour P, Rahi P (2016). Breast Cancer Risk Based on the Gail Model and its Predictors in Iranian Women. Asian Pac J Cancer Prev, 17(8):3741-5.
32. Omranipour R, Karbakhsh M, Behforouz A, et al (2015). Performance of the Gail Model for Breast Cancer Risk Assessment in Iranian Women. Archives of Breast Cancer, 2(1):27-31.
33. Panahi G, Shabahang H, Sahebghalam H (2008). Breast cancer risk assessment in Iranian women by Gail model. Med J Islam Repub Iran, 22:37-39.
34. Seyed Noori T, Zahmatkesh T, Molaei T, et al (2008). Evaluation of the Risk of Developing Breast Cancer by Utilizing Gail Model. Iranian Journal of Breast Diseases, 1:53-57.
35. Shirali R, Asad Elahi K, Asad Elahi P (2010). Risk perception and preventive issues for breast cancer among female employees. International Journal of Cancer Management (Iranian Journal Of Cancer Prevention), 3(4)166-173.
36. Maleki F, Fotouhi A, Ghiasvand R, et al (2020). Association of physical activity, body mass index and reproductive history with breast cancer by menopausal status in Iranian women. Cancer Epidemiol,67,101738.
37. Sadeghi F, Ardestani A, Hadji M, Mohagheghi MA, et al (2017). Travel Burden for Cancer Patients in Iran: Analysis of 1700 Patients from the Cancer Institute of Iran. Arch Iran Med, 20(3):147-152.
38. Chlebowski RT, Collyar DE, Somerfield MR, Pfister DG (1999). American Society of Clinical Oncology technology assessment on breast cancer risk reduction strategies: tamoxifen and raloxifene. J Clin Oncol, 17(6):1939-55.
39. Fisher B, Costantino JP, Wickerham DL, et al (1998). Tamoxifen for prevention of breast cancer: report of the National Surgical Adjuvant Breast and Bowel Project P-1 Study. J Natl Cancer Inst, 90(18):1371-88.
40. McCarthy AM, Keller B, Kontos D, et al (2015). The use of the Gail model, body mass index and SNPs to predict breast cancer among women with abnormal (BI-RADS 4) mammograms. Breast Cancer Res, 17(1): 1.
41. Min JW, Chang M-C, Lee HK, et al (2014). Validation of risk assessment models for predicting the incidence of breast cancer in Korean women. J Breast Cancer, 17(3):226-235.
42. Chlebowski RT, Chen Z, Anderson GL, et al (2005). Ethnicity and breast cancer: factors influencing differences in incidence and outcome. J Natl Cancer Inst, 97(6):439-48.
43. Tice JA, Miike R, Adduci K, et al (2005). Nipple aspirate fluid cytology and the Gail model for breast cancer risk assessment in a screening population. Cancer Epidemiol Biomarkers Prev, 14(2):324-8.
44. Tice JA, Cummings SR, Smith-Bindman R, et al (2008). Using clinical factors and mammographic breast density to estimate breast cancer risk: development and validation of a new predictive model. Ann Intern Med, 148(5):337-47.
45. Tice JA, Cummings SR, Ziv E, Kerlikowske K (2005). Mammographic breast density and the Gail model for breast cancer risk prediction in a screening population. Breast Cancer Res Treat, 94(2):115-22.
46. Chen SQ, Huang M, Shen YY, et al (2017). Abbreviated MRI Protocols for Detecting Breast Cancer in Women with Dense Breasts. Korean J Radiol, 18(3):470-475.
47. Mealiffe ME, Stokowski RP, Rhees BK, et al (2010). Assessment of clinical validity of a breast cancer risk model combining genetic and clinical information. J Natl Cancer Inst, 102(21):1618-27.
48. Wacholder S, Hartge P, Prentice R, et al (2010). Performance of common genetic variants in breast-cancer risk models. N Engl J Med, 362(11):986-93.
2. Rouhollahi MR, Mohagheghi MA, Mohammadrezai N, et al (2014). Situation analysis of the National Comprehensive Cancer Control Program (2013) in the I. R. of Iran; assessment and recommendations based on the IAEA imPACT mission. Arch Iran Med, 17(4):222-31.
3. Mohebbi E, Nahvijou A, Hadji M, et al (2017). Iran Cancer Statistics in 2012 and Projection of Cancer Incidence by 2035. Basic & Clinical Cancer Research 9:3-22.
4. Rashidian H, Daroudi R, Ghiasvand R, Harirchi I, Zendehdel K (2013). Prevalence and Incidence of premenopausal and postmenopausal breast cancer in Iran in 2010. Basic & Clinical Cancer Research, 5:2-10.
5. Ghiasvand R, Adami H-O, Harirchi I, et al (2014). Higher incidence of premenopausal breast cancer in less developed countries; myth or truth? BMC cancer, 14:343.
6. El Saghir NS, Khalil MK, Eid T, El Kinge AR, et al (2007). Trends in epidemiology and management of breast cancer in developing Arab countries: a literature and registry analysis. Int J Surg, 5(4):225-33.
7. Myers ER, Moorman P, Gierisch JM, et al (2015). Benefits and harms of breast cancer screening: a systematic review. JAMA, 314:1615-1634.
8. Nyström L, Bjurstam N, Jonsson H, et al (2017). Reduced breast cancer mortality after 20+ years of follow-up in the Swedish randomized controlled mammography trials in Malmö, Stockholm, and Göteborg. J Med Screen, 24(1):34-42.
9. Tabár L, Vitak B, Chen TH-H, et al (2011). Swedish two-county trial: impact of mammographic screening on breast cancer mortality during 3 decades. Radiology, 260(3):658-63.
10. Akbari ME, Haghighatkhah H, Shafiee M, et al (2012). Mammography and ultrasonography reports compared with tissue diagnosis--an evidence based study in Iran, 2010. Asian Pac J Cancer Prev, 13(5):1907-10.
11. Barfar E, Rashidian A, Hosseini H, et al (2014). Cost-effectiveness of mammography screening for breast cancer in a low socioeconomic group of Iranian women. Arch Iran Med, 17(4):241-5.
12. Warner E (2011). Clinical practice. Breast-cancer screening. N Engl J Med, 365:1025-32.
13. Mokarian F, Mokarian S, Ramezani A (2013). Relations of disease-free survival and overall survival with age and primary metastases in patients with breast cancer. Journal of Isfahan Medical School, 31(225):112-20.
14. Amir E, Freedman OC, Seruga B, Evans DG (2010). Assessing women at high risk of breast cancer: a review of risk assessment models. J Natl Cancer Inst, 102(10):680-91.
15. Zhao J, Song X, Leng L, et al (2017). Evaluation of risk assessment tools for breast cancer screening in Chinese population. Int J Clin Exp, 10:3582-3587.
16. Gail MH, Brinton LA, Byar DP, et al (1989). Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst, 81(24):1879-86.
17. Costantino JP, Gail MH, Pee D, Anderson S, et al (1999). Validation Studies for Models Projecting the Risk of Invasive and Total Breast Cancer Incidence. J Natl Cancer Inst, 91(18):1541-8.
18. Chay WY, Ong WS, Tan PH, et al (2012). Validation of the Gail model for predicting individual breast cancer risk in a prospective nationwide study of 28,104 Singapore women. Breast Cancer Res, 14:R19.
19. Ulusoy C, Kepenekci I, Kose K, Aydintug S, Cam R (2010). Applicability of the Gail model for breast cancer risk assessment in Turkish female population and evaluation of breastfeeding as a risk factor. Breast Cancer Res Treat, 120(2):419-24.
20. Abdulbari B, Funda Ç, Hanadi REA, et al (2017). Assessing Breast Cancer Risk Estimates Based on the Gail Model and Its Predictors in Qatari Women. J Prim Care Community Health, 8(3):180-187.
21. Ewaid S (2017). Breast cancer risk assessment by Gail Model in women of Baghdad. Alexandria Journal of Medicine, 53 (2):183-186.
22. Anothaisintawee T, Teerawattananon Y, Wiratkapun C, et al (2012). Risk prediction models of breast cancer: a systematic review of model performances. Breast Cancer Res Treat, 133(1):1-10.
23. Wang X, Huang Y, Li L, et al (2018). Assessment of performance of the Gail model for predicting breast cancer risk: a systematic review and meta-analysis with trial sequential analysis. Breast Cancer Res, 20(1):18.
24. Meads C, Ahmed I, Riley RD (2012). A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance. Breast Cancer Res Treat, 132(2):365-77.
25. Gail MH, Pfeiffer RM (2005). On criteria for evaluating models of absolute risk. Biostatistics, 6(2):227-39.
26. Wu Y, Liu J, Rio AMd, et al (2015). Developing a clinical utility framework to evaluate prediction models in radiogenomics. Proc SPIE Int Soc Opt Eng ,9416:941617.
27. Darabi H, Czene K, Zhao W, et al (2012). Breast cancer risk prediction and individualised screening based on common genetic variation and breast density measurement. Breast Cancer Res, 14(1):R25.
28. Eriksson M, Czene K, Pawitan Y, et al (2017). A clinical model for identifying the short-term risk of breast cancer. Breast Cancer Res, 19(1):29.
29. Hosseinpour R, HAJI NE, Ranjpoor F, et al (2011). Evaluation of the risk of breast cancer, based on the Gail model, in women of more than 35 years old: at health centers of Yasouj during 2010-2011. Iranian Journal of Surgery, 20(3):13-20.
30. Khazaee-Pool M, Majlessi F, Nedjat S, et al (2016). Assessing Breast Cancer Risk among Iranian Women Using the Gail Model. Asian Pac J Cancer Prev, 17(8):3759-62.
31. Mirghafourvand M, Mohammad-Alizadeh-Charandabi S, Ahmadpour P, Rahi P (2016). Breast Cancer Risk Based on the Gail Model and its Predictors in Iranian Women. Asian Pac J Cancer Prev, 17(8):3741-5.
32. Omranipour R, Karbakhsh M, Behforouz A, et al (2015). Performance of the Gail Model for Breast Cancer Risk Assessment in Iranian Women. Archives of Breast Cancer, 2(1):27-31.
33. Panahi G, Shabahang H, Sahebghalam H (2008). Breast cancer risk assessment in Iranian women by Gail model. Med J Islam Repub Iran, 22:37-39.
34. Seyed Noori T, Zahmatkesh T, Molaei T, et al (2008). Evaluation of the Risk of Developing Breast Cancer by Utilizing Gail Model. Iranian Journal of Breast Diseases, 1:53-57.
35. Shirali R, Asad Elahi K, Asad Elahi P (2010). Risk perception and preventive issues for breast cancer among female employees. International Journal of Cancer Management (Iranian Journal Of Cancer Prevention), 3(4)166-173.
36. Maleki F, Fotouhi A, Ghiasvand R, et al (2020). Association of physical activity, body mass index and reproductive history with breast cancer by menopausal status in Iranian women. Cancer Epidemiol,67,101738.
37. Sadeghi F, Ardestani A, Hadji M, Mohagheghi MA, et al (2017). Travel Burden for Cancer Patients in Iran: Analysis of 1700 Patients from the Cancer Institute of Iran. Arch Iran Med, 20(3):147-152.
38. Chlebowski RT, Collyar DE, Somerfield MR, Pfister DG (1999). American Society of Clinical Oncology technology assessment on breast cancer risk reduction strategies: tamoxifen and raloxifene. J Clin Oncol, 17(6):1939-55.
39. Fisher B, Costantino JP, Wickerham DL, et al (1998). Tamoxifen for prevention of breast cancer: report of the National Surgical Adjuvant Breast and Bowel Project P-1 Study. J Natl Cancer Inst, 90(18):1371-88.
40. McCarthy AM, Keller B, Kontos D, et al (2015). The use of the Gail model, body mass index and SNPs to predict breast cancer among women with abnormal (BI-RADS 4) mammograms. Breast Cancer Res, 17(1): 1.
41. Min JW, Chang M-C, Lee HK, et al (2014). Validation of risk assessment models for predicting the incidence of breast cancer in Korean women. J Breast Cancer, 17(3):226-235.
42. Chlebowski RT, Chen Z, Anderson GL, et al (2005). Ethnicity and breast cancer: factors influencing differences in incidence and outcome. J Natl Cancer Inst, 97(6):439-48.
43. Tice JA, Miike R, Adduci K, et al (2005). Nipple aspirate fluid cytology and the Gail model for breast cancer risk assessment in a screening population. Cancer Epidemiol Biomarkers Prev, 14(2):324-8.
44. Tice JA, Cummings SR, Smith-Bindman R, et al (2008). Using clinical factors and mammographic breast density to estimate breast cancer risk: development and validation of a new predictive model. Ann Intern Med, 148(5):337-47.
45. Tice JA, Cummings SR, Ziv E, Kerlikowske K (2005). Mammographic breast density and the Gail model for breast cancer risk prediction in a screening population. Breast Cancer Res Treat, 94(2):115-22.
46. Chen SQ, Huang M, Shen YY, et al (2017). Abbreviated MRI Protocols for Detecting Breast Cancer in Women with Dense Breasts. Korean J Radiol, 18(3):470-475.
47. Mealiffe ME, Stokowski RP, Rhees BK, et al (2010). Assessment of clinical validity of a breast cancer risk model combining genetic and clinical information. J Natl Cancer Inst, 102(21):1618-27.
48. Wacholder S, Hartge P, Prentice R, et al (2010). Performance of common genetic variants in breast-cancer risk models. N Engl J Med, 362(11):986-93.
| Files | ||
| Issue | Vol 49 No 11 (2020) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/ijph.v49i11.4739 | |
| PMCID | PMC7917489 | |
| PMID | 33708742 | |
| Keywords | ||
| Breast neoplasms Risk assessment Models Statistical Logistic models | ||
| Rights and permissions | |
|
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
ROSTAMI S, RAFEI A, DAMGHANIAN M, KHAKBAZAN Z, MALEKI F, ZENDEHDEL K. Discriminatory Accuracy of the Gail Model for Breast Cancer Risk Assessment among Iranian Women. Iran J Public Health. 2020;49(11):2205-2213.
