The Objective of this research work is to prove significant role of each attribute to decide breast cancer type using Computer Aided Diagnosis. One of major challenges in medical domain is the extraction of intelligible knowledge from medical diagnostic data in minimum time and cost This research shows that out of these attributes stated, some attributes can be ignored to decide the type Breast Cancer as if the number of inputs are less then it reduces the time and cost in analyzing the breast cancer. In this paper, significant role of each attribute is proved by experiment in matlab.
Background: Family history directs referral of unaffected individuals to GS and is the main strategy to identify hereditary breast ovarian cancer syndrome. In unaffected individuals with known familial mutations, potentially life saving information can be provided to a large number of these individuals at a very modest cost.
Objectives: 1) To determine the rate of deleterious mutations in high risk individuals, based on pedigree, and 2) to identify the origin of their referral. Methods:
Over a 5-year period (2004 -2009) we analyzed the source of referral for genetic testing and the mutations detected in 1132 consecutively tested individuals. Of 1132 patients tested for BRCA1 or BRCA2 mutations, 420 were unaffected by cancer and 712 had breast or ovarian cancer at the time consultation. We excluded those from families who were previously tested at our institution to limit the bias for mutation positivity.
Results:
Seven hundred and sixty five patients were tested via comprehensive BRCA analysis (63 patients also had BART analysis) and of those only 7% (55) had deleterious mutations. Only 3% (24) had mutations in BRCA1 gene, and 29 patients had deleterious mutations in BRCA2. Of the 63 patients who underwent BART only 3% (2) had large deletions in BRCA1 gene. Two hundred and seventy three patients were tested for the three known Ashkenazi mutations and 20% (57) had deleterious mutations 10% (28) in BRCA1 gene and 10% (29) in BRCA 2. Ninety four patients were tested for known family mutations with single site analysis and there were (57%) 54 had deleterious mutations 27% (26) in BRCA 1 gene and 29% (28) in BRCA 2. Referring source was: self 283 (25%), GYN 430 (38%), surgeon 283 (25%), PCP 136 (12%) cases. Conclusions:
Single site testing of a known mutation costs ∼ 400$ and in 94 patients (8%) gave rapid information about cancer risk. Of these 27% (26) unaffected individuals were identified as carrying deleterious mutations and 73% (68) individuals found out their cancer risk was average. The yield of testing by comprehensive BRCA analysis was 7%, M3 panel detected 20% deleterious mutation and single site analysis for known familial mutations had the lower cost and higher yield of 57%. Primary care physicians identified only 12% of patients with high risk for hereditary cancer syndromes.
Discussion:
Although family history is the cornerstone of high-risk patient referral to GS, primary care physicians referred only 12% of all patients at risk for HBOC. Attention to family history and increased public awareness of hereditary risk are effective means of identifying at risk populations for referral for GS. The yield of mutation detection is highest and cost effective in families with known mutations. Our yield of 57% detection in families with known mutations is likely an indication that not all family members at risk seek genetic counseling or are referred at the same center.
Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P2-10-05.
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