Predicting BRCA1 and BRCA2 gene mutation carriers: comparison of LAMBDA, BRCAPRO, Myriad II, and modified Couch models
| Autor: | John L. Hopper, Betty A. Mincey, Noralane M. Lindor, Amanda K. Ashley, Katherine S. Hunt, Marcia Wilson, M. Cathie Smith, Rachel A. Lindor, James G. Dowty, Carmel Apicella |
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| Rok vydání: | 2007 |
| Předmět: |
Adult
Heterozygote Cancer Research endocrine system diseases Bayesian probability Context (language use) Biology Lambda Article Germline mutation Genetics Humans Computer Simulation skin and connective tissue diseases Genetics (clinical) BRCA2 Protein Models Genetic BRCA1 Protein Middle Aged Human genetics Oncology Jews Mutation Mutation (genetic algorithm) Female BRCA2 Gene Mutation Software |
| Zdroj: | Familial Cancer. 6:473-482 |
| ISSN: | 1573-7292 1389-9600 |
| DOI: | 10.1007/s10689-007-9150-z |
| Popis: | Models have been developed to predict the probability that a person carries a detectable germline mutation in the BRCA1 or BRCA2 genes. Their relative performance in a clinical setting is unclear.To compare the performance characteristics of four BRCA1/BRCA2 gene mutation prediction models: LAMBDA, based on a checklist and scores developed from data on Ashkenazi Jewish (AJ) women; BRCAPRO, a Bayesian computer program; modified Couch tables based on regression analyses; and Myriad II tables collated by Myriad Genetics Laboratories.Family cancer history data were analyzed from 200 probands from the Mayo Clinic Familial Cancer Program, in a multispecialty tertiary care group practice. All probands had clinical testing for BRCA1 and BRCA2 mutations conducted in a single laboratory.For each model, performance was assessed by the area under the receiver operator characteristic curve (ROC) and by tests of accuracy and dispersion. Cases "missed" by one or more models (model predicted less than 10% probability of mutation when a mutation was actually found) were compared across models.All models gave similar areas under the ROC curve of 0.71 to 0.76. All models except LAMBDA substantially under-predicted the numbers of carriers. All models were too dispersed.In terms of ranking, all prediction models performed reasonably well with similar performance characteristics. Model predictions were widely discrepant for some families. Review of cancer family histories by an experienced clinician continues to be vital to ensure that critical elements are not missed and that the most appropriate risk prediction figures are provided. |
| Databáze: | OpenAIRE |
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