Predicting BRCA1 and BRCA2 gene mutation carriers: Comparison of LAMBDA, BRCAPRO, Myriad II, and modified Couch models

Noralane Morey Lindor, Rachel A. Lindor, Carmel Apicella, James G. Dowty, Amanda Ashley, Katherine Hunt, Betty A. Mincey, Marcia Wilson, M. Cathie Smith, John L. Hopper

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Context: 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. Objective: 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. Design and setting: 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. Main outcomes measures: 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. Results: 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. Conclusions: 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.

Original languageEnglish (US)
Pages (from-to)473-482
Number of pages10
JournalFamilial Cancer
Volume6
Issue number4
DOIs
StatePublished - Dec 2007

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BRCA2 Gene
BRCA1 Gene
Mutation
Neoplasms
Group Practice
Germ-Line Mutation
Tertiary Healthcare
Checklist
Software
Regression Analysis
Outcome Assessment (Health Care)

Keywords

  • Ashkenazi Jewish
  • Bayesian
  • BRCA1
  • BRCA2
  • Breast cancer
  • Risk prediction

ASJC Scopus subject areas

  • Cancer Research
  • Genetics

Cite this

Predicting BRCA1 and BRCA2 gene mutation carriers : Comparison of LAMBDA, BRCAPRO, Myriad II, and modified Couch models. / Lindor, Noralane Morey; Lindor, Rachel A.; Apicella, Carmel; Dowty, James G.; Ashley, Amanda; Hunt, Katherine; Mincey, Betty A.; Wilson, Marcia; Smith, M. Cathie; Hopper, John L.

In: Familial Cancer, Vol. 6, No. 4, 12.2007, p. 473-482.

Research output: Contribution to journalArticle

Lindor, NM, Lindor, RA, Apicella, C, Dowty, JG, Ashley, A, Hunt, K, Mincey, BA, Wilson, M, Smith, MC & Hopper, JL 2007, 'Predicting BRCA1 and BRCA2 gene mutation carriers: Comparison of LAMBDA, BRCAPRO, Myriad II, and modified Couch models', Familial Cancer, vol. 6, no. 4, pp. 473-482. https://doi.org/10.1007/s10689-007-9150-z
Lindor, Noralane Morey ; Lindor, Rachel A. ; Apicella, Carmel ; Dowty, James G. ; Ashley, Amanda ; Hunt, Katherine ; Mincey, Betty A. ; Wilson, Marcia ; Smith, M. Cathie ; Hopper, John L. / Predicting BRCA1 and BRCA2 gene mutation carriers : Comparison of LAMBDA, BRCAPRO, Myriad II, and modified Couch models. In: Familial Cancer. 2007 ; Vol. 6, No. 4. pp. 473-482.
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AU - Ashley, Amanda

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AU - Mincey, Betty A.

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N2 - Context: 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. Objective: 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. Design and setting: 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. Main outcomes measures: 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. Results: 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. Conclusions: 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.

AB - Context: 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. Objective: 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. Design and setting: 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. Main outcomes measures: 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. Results: 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. Conclusions: 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.

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