// your theHunter: Call of the Wild Team. Deer hunt challenge se patch. Hello Hunters! We are thrilled to reveal our new upcoming content: Weapon Pack 2!

Technical software for research and teaching - especially biology and statistics.

The authors retrospectively aimed to determine which of the following three scenarios, related to DCIS entry into BRCAPRO, predicted BRCA mutation status more accurately: (1) DCIS as an invasive breast cancer (IBC) entered using the actual age of diagnosis, (2) DCIS as IBC entered with 10 years added to the actual age of diagnosis, and (3) DCIS entered as no cancer. Of the 85 DCIS patients included in the study, 19% ( n = 16) tested positive for a BRCA mutation, and 81% ( n = 69) tested negative. DCIS patients who tested positive for a BRCA mutation had a higher BRCAPRO risk estimation (34.61%) than patients who tested negative (11.4%) when DCIS was entered at the actual age of diagnosis.

When DCIS was entered with 10 years added to the actual age at diagnosis, the BRCAPRO estimate was still higher amongst BRCA positive patients (25.4%) than BRCA negative patients (7.1%). When DCIS was entered as no cancer, the BRCAPRO estimate remained higher among BRCA positive patients (2.56%) than BRCA negative patents (1.98%). In terms of accuracy of BRCA positivity, there was no statistically significant difference between DCIS at age at diagnosis, DCIS at 10 years later than age at diagnosis, and DCIS entered as no cancer (AUC = 0.77, 0.784, 0.75, respectively: p = 0.60).

Our results indicate that regardless of entry approach into BRCAPRO, there were no significant differences in predicting BRCA mutation in patients with DCIS. Introduction It has been shown that hereditary predisposition constitutes a major risk factor for the development of breast cancer (BC). Five to ten percent of BC is caused by inheritable gene mutations (Seeber and Driscoll, ). The BRCA1 and BRCA2 (BRCA) genes account for a high percentage of hereditary breast and ovarian cancer (Seeber and Driscoll, ). Carriers of one of the these mutations have a 43–84% risk of developing BC in their lifetime, and up to 65% risk for a contralateral BC (Ford et al.,; Chen et al., ). Understanding one's risk for testing positive for a genetic mutation has clinical and personal implications, therefore accurate risk assessment is crucial. Several genetic risk assessment models have been used to predict an individual's likelihood of possessing a BRCA gene mutation.

More specifically, the BRCAPRO model is a risk assessment tool part of the CancerGene program. It utilizes Bayes Mendel analysis and ultimately determines those that are at an increased risk of developing breast, ovarian and other cancer types. The BRCAPRO model has been shown to be an accurate model for determining the probability of carrying a genetic mutation (Berry et al., ). This model incorporates personal and family history information to determine the probability of a BRCA gene mutation. The analysis incorporates the number of first and second degree relatives along with the tumor histories of the patient and the family members. However, the incorporated tumor history only includes the invasive diagnoses and does not include the pre-invasive lesions.