Sentence examples for mutation prediction models from inspiring English sources

This study assessed the performance of mutation prediction models in this population-based data set.

4 ASCO criteria and/or prior probability of a BRCA mutation ≥ 30% using Myriad mutation prevalence tables and the Penn II mutation prediction model.

In addition, prior probabilities of carrying a BRCA1 or BRCA2 mutation were determined for each patient using mutation prevalence tables and the Penn II mutation prediction model [ 35- 37].

Mutation risk prediction models can be incorporated into clinical practice, facilitating the decision-making process and identifying individuals for molecular investigation.

In the present study we used data from French-Canadian families included in the INHERIT program to evaluate the mutation risk prediction models BOADICEA and BRCAPRO [ 14, 16] and to estimate the breast and ovarian cancer risks conferred by BRCA1 and BRCA2 mutations.

Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance.

According to prediction models, this mutation is not expected to be deleterious (IARC TP 53 mutation data base, R11, 2006) [ 21- 23].

These variants could be employed in risk prediction models for mutation carriers.

In this study we used the family histories of a large tested cohort, some with known BRCA germline mutations, to evaluate the clinical effectiveness of four risk prediction models for BRCA mutations.

Table 5 presents results from AUC for risk prediction models for MLH1 mutation and Table 6 the Pairwise comparison for MLH1 mutation.

We used two independent datasets to train and test the performance of the models for somatic mutation prediction.