Brcapro Software Download

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Total downloads: 335 (1 last week) Operating system: Windows XP/Vista/7/8. CancerGene provides a user friendly graphical interface for generating the input files required by the BayesMendel BRCAPRO and MMRpro and PancPro programs run seamlessly in the background. UTSW CancerGene Software download. Southwestern Medical Center at Dallas and The BayesMendel Group CancerGene with BRCAPRO, MMRpro, PancPRO, and MelaPRO. Duke, JHU and UT Southwestern may terminate this Agreement immediately upon Licensee’s breach of this Agreement.

The recent release of version 2.0-8 of the BayesMendel package contains an updated BRCAPRO risk prediction model, which includes revised modeling of Contralateral Breast Cancer (CBC) penetrance, provisions for pedigrees of mixed ethnicity and an adjustment for mastectomies among family members. We estimated penetrance functions for contralateral breast cancer by a combination of parametric survival modeling of literature data and deconvolution of SEER9 data. We then validated the resulting updated model of CBC in BRCAPRO by comparing it with the previous release (BayesMendel 2.0-7), using pedigrees from the Cancer Genetics Network (CGN) Model Validation Study. Version 2.0-8 of BRCAPRO discriminates BRCA1/BRCA2 carriers from non-carriers with similar accuracy compared to the previous version (increase in AUC: 0.0043), is slightly more precise in terms of RMSE (decrease in RMSE: 0.0108), and it significantly improves calibration (ratio of observed to expected events of 0.9765 in version 2.0-8, compared to 0.8910 in version 2.0-7). We recommend that the new version be used in clinical counseling, particularly in settings where families with CBC are common. Introduction The BRCA1 and BRCA2 genes help explain about 5–10% of breast cancer cases [,].

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About 12% of women in the general population will develop breast cancer sometime during their lives []. By contrast, according to recent estimates, 55 to 65% of women who inherit a harmful BRCA1 mutation and around 45% of women who inherit a harmful BRCA2 mutation will develop breast cancer by age 70 years [,]. Models to predict carrier status are commonly used clinically.

Among these, BRCAPRO is the most commonly used, and consistently ranks among the best performing in validation studies []. BRCAPRO is continually improved based upon current literature [–] and has been incorporated into software used by clinicians, researchers, and software developers [–]. The most recent version of BRCAPRO, included in the BayesMendel 2.0-8 package [], provides updated estimates for Contralateral Breast Cancer (CBC) penetrance, can handle pedigrees including multiple ethnicities, and adjusts for mastectomies among any of the relatives. CBC occurrence was previously estimated via the simplifying assumption that the first and second diagnoses were independent. Families with CBC had been previously identified as being one of the subgroups where predictions provided by BRCAPRO are less accurate []. Recent literature provides further evidence of a strong dependence between fist and second diagnoses [–] as well as explicit estimates of the cumulative incidence of CBC among carriers []. Before distributing the upgraded model, we validated it using data from the Cancer Genetics Network (CGN) Model Validation Study [].

Validation data The CGN Model Validation Study comprises pedigrees collected in 8 high-risk counseling clinics that well represent the populations within which the BRCAPRO model is more commonly applied. The study is described in detail elsewhere []. For reproducibility, we created an R package that reads in the raw data provided by the 8 centers, performs any necessary preprocessing, and reproduces the BRCAPRO risks evaluated independently at the sites using independent software. Across the eight sites, 2089 pedigrees were provided, of which 2038 run without error through both versions of BRCAPRO, and were thus eligible for a head-to-head model comparison. Since we do not have separate information on ethnicity of individual family members, nor information on mastectomies for these individuals, we focus on improvements resulting from the updated CBC penetrances. We compare the ability of the models to a) discriminate carriers from non-carriers using the area under the ROC curve (AUC [, ]), b) increase precision of estimated carrier probabilities using the root mean square error of prediction (for MSE see [, ]), and c) estimate the overall number of observed carriers using the observed to expected ratio (OE [, ]). For each metric, we evaluate the estimates, their 95% bias-corrected accelerated (BCa) bootstrap confidence intervals, the estimates of the differences between the two versions of BRCAPRO, and their corresponding 95% BCa bootstrap confidence intervals.

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