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IJSTR >> Volume 6 - Issue 9, September 2017 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Prediction Model For Risk Of Breast Cancer Considering Interaction Between The Risk Factors

[Full Text]

 

AUTHOR(S)

Nabila Al Balushi

 

KEYWORDS

Interaction, Predictive model, AIC, GLM, Likelihood, Correlation, risk

 

ABSTRACT

This paper focuses on expansion of Barlow’s predictive model in which a large data set of 2,392,998 eligible screening mammograms taken from Breast Cancer Surveillance Consortium which was previously used by Barlow in 2006 to predict a diagnosis of breast cancer in women through including interaction of exploratory variables. 12 explanatory variables that are assumed to influence the risk of developing breast cancer in women and they are :age, breast density, menopause status, race, Hispanic, BMI ,number of first degree relatives with breast cancer, previous breast procedure, age at first birth, surgical menopause, results of last mammogram, and current hormone therapy. Forward selection method was used to select the best predictive model including significant interaction terms. The results showed 33 interactions were included in the new model through forward selection procedure improved the predictive model. However, only 10 interaction terms were found to be significant across all levels of the risk factors. Also, the updated predictive model was found to better than the main effect model, as the AIC value decreased.

 

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