scholarly journals Outpatient Genetic Risk Assessment in Women With Breast Cancer: One Center's Experiencetions

2005 ◽  
Vol 9 (1) ◽  
pp. 49-53 ◽  
Author(s):  
Nancy J. Washburn ◽  
Valerie K. Sommer ◽  
Sarah E. Spencer ◽  
Sandra K. Simmons ◽  
Barbara W. Adkins ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Genetic Risk ◽  
Genetic Risk Assessment

An update on genetic risk assessment and prevention: the role of genetic testing panels in breast cancer

2019 ◽  
Vol 19 (9) ◽  
pp. 787-801 ◽  
Author(s):  
Carolyn Piccinin ◽  
Seema Panchal ◽  
Nicholas Watkins ◽  
Raymond H Kim
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Genetic Testing ◽  
Genetic Risk ◽  
Genetic Risk Assessment ◽  
Risk Assessment And Prevention

Systematic genetic risk assessment for breast cancer patients in a community oncology practice

2008 ◽  
Vol 26 (15_suppl) ◽  
pp. 22172-22172
Author(s):  
T. Amatruda ◽  
S. Coombes ◽  
J. Greenberg ◽  
B. Kunz ◽  
J. Larsen Haidle ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Cancer Patients ◽  
Genetic Risk ◽  
Breast Cancer Patients ◽  
Genetic Risk Assessment ◽  
Community Oncology ◽  
Oncology Practice

Genetic risk assessment and prevention: the role of genetic testing panels in breast cancer

2015 ◽  
Vol 15 (11) ◽  
pp. 1315-1326 ◽  
Author(s):  
Jordan Lerner-Ellis ◽  
Sam Khalouei ◽  
Victoria Sopik ◽  
Steven A Narod
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Genetic Testing ◽  
Genetic Risk ◽  
Genetic Risk Assessment ◽  
Risk Assessment And Prevention

scholarly journals A feasibility study of breast cancer genetic risk assessment in a federally qualified health center

Cancer ◽  
2018 ◽  
Vol 124 (18) ◽  
pp. 3733-3741 ◽  
Author(s):  
Kent F. Hoskins ◽  
Silvia Tejeda ◽  
Ganga Vijayasiri ◽  
Ifeanyi Beverly Chukwudozie ◽  
Mylene H. Remo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Health Center ◽  
Feasibility Study ◽  
Genetic Risk ◽  
Cancer Genetic ◽  
Genetic Risk Assessment ◽  
Federally Qualified Health Center ◽  
Cancer Genetic Risk Assessment

Influence of race and socioeconomic status on genetic risk assessment for breast cancer.

2016 ◽  
Vol 34 (15_suppl) ◽  
pp. e18079-e18079
Author(s):  
Mahvish Muzaffar ◽  
Jessica R. Hildebrand ◽  
Nicole Lawing ◽  
Suzanne Hudson ◽  
Jan H. Wong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Socioeconomic Status ◽  
Genetic Risk ◽  
Genetic Risk Assessment

scholarly journals Uncertainty Handling in Genetic Risk Assessment and Counseling

2021 ◽  
Vol 27 (12) ◽  
pp. 1347-1370
Author(s):  
Ekaterina Auer ◽  
Wolfram Luther
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Genetic Counseling ◽  
Genetic Risk ◽  
Epistemic Uncertainty ◽  
Point Of View ◽  
Assessment Tools ◽  
Risk Category ◽  
Genetic Risk Assessment ◽  
Uncertainty Handling

In this paper, we consider genetic risk assessment and genetic counseling for breast cancer from the point of view of reliable uncertainty handling. In medical practice, there exist fairly accurate numerical tools predicting breast cancer (or gene mutation) probability based on such factors as the family history of a patient. However, they are too complex to be applied in normal doctors’ offices, so that several simplified, questionnaire-type support tools appeared. This process is highly affected by uncertainty. At the same time, reliability of test interpretations and counseling conclusions is especially important since they have direct influence on humans and their decisions. We show how expert opinions on mutation probabilities can be combined using the Dempster-Shafer theory. Based on multi-criteria binary decision trees and interval analysis, we combine the referral screening tool designed to determine patients at risk of breast cancer (and recommend genetic counseling or testing for them) with three further risk assessment tools available for this purpose. A patient’s confidence in the outcome of a genetic counseling session can be heightened by the proposed method since it combines different sources to provide score ranges leading to more information. Finally, based on this approach, a decision tree for assigning a risk category is proposed which enhances the existing methodology. The great impact of epistemic uncertainty is reflected through large overlapping intervals for the risk classes.

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