scholarly journals Risk Assessment Tool based on Demographic Risk Factors to Predict Breast Cancer Risk using Neuro-Fuzzy Technique

2017 ◽  
Vol 174 (8) ◽  
pp. 23-29
Author(s):  
Donia S. ◽  
Kareem R.
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Risk Assessment ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Assessment Tool ◽  
Risk Assessment Tool ◽  
Neuro Fuzzy ◽  
Demographic Risk ◽  
Demographic Risk Factors

scholarly journals Using an Internet-Based Breast Cancer Risk Assessment Tool to Improve Social-Cognitive Precursors of Physical Activity

2017 ◽  
Vol 37 (6) ◽  
pp. 657-669 ◽  
Author(s):  
Stephanie L. Fowler ◽  
William M. P. Klein ◽  
Linda Ball ◽  
Jaclyn McGuire ◽  
Graham A. Colditz ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Physical Activity ◽  
Risk Assessment ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Social Cognitive ◽  
Assessment Tool ◽  
Risk Assessment Tool ◽  
Cancer Risk Assessment ◽  
Breast Cancer Risk Assessment

scholarly journals Model for Individualized Prediction of Breast Cancer Risk After a Benign Breast Biopsy

2015 ◽  
Vol 33 (8) ◽  
pp. 923-929 ◽  
Author(s):  
V. Shane Pankratz ◽  
Amy C. Degnim ◽  
Ryan D. Frank ◽  
Marlene H. Frost ◽  
Daniel W. Visscher ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Assessment Tool ◽  
Risk Assessment Tool ◽  
Cancer Risk Assessment ◽  
Increased Risk ◽  
Breast Cancer Risk Assessment ◽  
Benign Biopsy

Purpose Optimal early detection and prevention for breast cancer depend on accurate identification of women at increased risk. We present a risk prediction model that incorporates histologic features of biopsy tissues from women with benign breast disease (BBD) and compare its performance to the Breast Cancer Risk Assessment Tool (BCRAT). Methods We estimated the age-specific incidence of breast cancer and death from the Mayo BBD cohort and then combined these estimates with a relative risk model derived from 377 patient cases with breast cancer and 734 matched controls sampled from the Mayo BBD cohort to develop the BBD–to–breast cancer (BBD-BC) risk assessment tool. We validated the model using an independent set of 378 patient cases with breast cancer and 728 matched controls from the Mayo BBD cohort and compared the risk predictions from our model with those from the BCRAT. Results The BBD-BC model predicts the probability of breast cancer in women with BBD using tissue-based and other risk factors. The concordance statistic from the BBD-BC model was 0.665 in the model development series and 0.629 in the validation series; these values were higher than those from the BCRAT (0.567 and 0.472, respectively). The BCRAT significantly underpredicted breast cancer risk after benign biopsy (P = .004), whereas the BBD-BC predictions were appropriately calibrated to observed cancers (P = .247). Conclusion We developed a model using both demographic and histologic features to predict breast cancer risk in women with BBD. Our model more accurately classifies a woman's breast cancer risk after a benign biopsy than the BCRAT.

scholarly journals Performance of the Breast Cancer Risk Assessment Tool Among Women Age 75 Years and Older

2015 ◽  
Vol 108 (3) ◽  
pp. djv348 ◽  
Author(s):  
Mara A. Schonberg ◽  
Vicky W. Li ◽  
A. Heather Eliassen ◽  
Roger B. Davis ◽  
Andrea Z. LaCroix ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Assessment Tool ◽  
Risk Assessment Tool ◽  
Cancer Risk Assessment ◽  
Breast Cancer Risk Assessment

scholarly journals Assessing Breast Cancer Risk Estimates Based on the Gail Model and Its Predictors in Qatari Women

2017 ◽  
Vol 8 (3) ◽  
pp. 180-187 ◽  
Author(s):  
Abdulbari Bener ◽  
Funda Çatan ◽  
Hanadi R. El Ayoubi ◽  
Ahmet Acar ◽  
Wanis H. Ibrahim
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Family History ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Assessment Tool ◽  
Risk Assessment Tool ◽  
Arab Women ◽  
Gail Model ◽  
Breast Cancer Risk Assessment

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.

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