Skip to main content

Advertisement

Log in

Validation of the Pedigree Assessment Tool (PAT) in Families with BRCA1 and BRCA2 Mutations

  • Breast Oncology
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

The lifetime risk of breast cancer (BC) in patients with hereditary breast cancer syndromes is as high as 80%. The Pedigree Assessment Tool (PAT) is a scoring system to aid in identifying these patients. This validation study compares the PAT to BRCA gene mutation probability models in predicting suitability for genetic referral.

Methods

Retrospective review identified subjects undergoing genetic counseling and BRCA testing from 2001 to 2008 at two institutions. PAT score and BRCA mutation probabilities were calculated using Myriad II and Penn II models. Comparisons were made between models in ability to discriminate patients appropriate for genetic evaluation based on accuracy in predicting a positive test result.

Results

Records evaluated represent 520 families. BRCA testing revealed 146 mutation-positive and 374 mutation-negative families. c-Statistic analysis was used to compare the discriminating ability of the models to correctly assign families as mutation (+) and (−). Both the PAT and Penn II model outperformed the Myriad II model. Using a threshold PAT score ≥8 and mutation probability ≥10% to assign families as mutation (+) versus (−), sensitivity, specificity, and positive and negative predictive values were calculated for each model. The PAT was more sensitive than the Myriad II model and more specific than the Penn II model.

Conclusions

In overall performance, the PAT is at least comparable to the Myriad II and Penn II models in screening women appropriate for genetic referral. Simplicity and identification of families with non-BRCA hereditary BC syndromes suggest that the PAT is better suited for BC risk screening.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Claus EB, Schildkraut JM, Thompson WD, Risch NJ. The genetic attributable risk of breast and ovarian cancer. Cancer. 1996;77:2318.

    Article  CAS  PubMed  Google Scholar 

  2. Wooster R, Weber BL. Breast and ovarian cancer. N Engl J Med. 2005;348(23):2339–47.

    Article  Google Scholar 

  3. Ford D, Easton DF, Peto J. Estimates of the gene frequency of BRCA1 and its contribution to breast and ovarian cancer incidence. Am J Hum Genet. 1995;57:1457.

    CAS  PubMed  Google Scholar 

  4. Newman B, Austin MA, Lee M, King MC. Inheritance of human breast cancer: evidence for autosomal dominant transmission in high-risk families. Proc Natl Acad Sci USA. 1988;85:3044.

    Article  CAS  PubMed  Google Scholar 

  5. Bish A, Sutton S, Jacobs C, Levene S, Ramirez A, Hodgson S. Changes in psychological distress after cancer genetic counseling: a comparison of affected and unaffected women. Br J Cancer. 2002;86:43–50.

    Article  CAS  PubMed  Google Scholar 

  6. Hoskins KF, Zwaagstra A, Ranz M. Validation of a tool for identifying women at high risk for hereditary breast cancer in population-based screening. Cancer. 2006;107(8):1769–76.

    Article  PubMed  Google Scholar 

  7. Breast cancer risk screening tool. www.mybreastrisk.com. Accessed 5 Feb 2009.

  8. O’Neill S. Quantitative breast cancer risk assessment. In: Vogel VG, editor. Management of patients at high risk for breast cancer. Blackwell, Malden; 2000. p. 63–94.

    Google Scholar 

  9. The Penn II BRCA1 and BRCA2 mutation risk evaluation model official web site. https://www.afcri.upenn.edu:8022/itacc/penn2/index.asp. Accessed 5 Feb 2009.

  10. Domchek SM, Eisen A, Calzone K, et al. Application of breast cancer risk prediction models in clinical practice. J Clin Oncol. 2003;21(4):593–601.

    Article  PubMed  Google Scholar 

  11. Frank TS, Deffenbaugh AM, Reid JE, et al. Clinical characteristics of individuals with germline mutations in BRCA1 and BRCA2: analysis of 10,000 individuals. J Clin Oncol. 2002;20:1480–90.

    Article  CAS  PubMed  Google Scholar 

  12. Myriad BRCA risk calculator and mutation prevalence tables. http://www.myriadtests.com/provider/brca-mutation-prevalence.htm. Accessed 5 Feb 2009.

  13. Myriad BRCA risk calculator. http://www.myriadtests.com/provider/brca-risk-calculator.htm. Accessed 5 Feb 2009.

  14. Harrell FE, Califf RM, Pryor DB, et al. Evaluating the yield of medical tests. JAMA. 1982;247:2543–6.

    Article  PubMed  Google Scholar 

  15. The American Society of Clinical Oncology. Statement of the American Society of Clinical Oncology: genetic testing for cancer susceptibility. J Clin Oncol. 1996;14:1730–6.

    Google Scholar 

  16. Statement of the American Society of Human Genetics on genetic testing for breast and ovarian cancer predisposition. Am J Hum Gen. 1994;55:i–iv.

    Google Scholar 

  17. Gail MH, Brinton LA, Byar DP, et al. Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst. 1989;81:1879–86.

    Article  CAS  PubMed  Google Scholar 

  18. Bondy ML, Lustbader ED, Halabi S, et al. Validation of a breast cancer risk assessment modeling women with a positive family history. J Natl Cancer Inst. 1994;86:620–5.

    Article  CAS  PubMed  Google Scholar 

  19. Constantino JP, Gail MH, Pee D, Anderson S, Redmond CK, Benichou J, et al. Validation studies for model projecting the risk of invasive breast and total breast cancer incidence. J Natl Cancer Inst. 1999;91:1541–8.

    Article  Google Scholar 

  20. Rockhill B, Spiegelman D, Byrne C, Hunter DJ, Colditz GA. Validation of the Gail model of breast cancer risk prediction and implications for chemoprevention. J Natl Cancer Inst. 2001;93:358–66.

    Article  CAS  PubMed  Google Scholar 

  21. Euhus DM, Leitch AM, Huth JF, Peters GN. Limitations of the Gail model in the specialized breast cancer risk assessment clinic. Breast J. 2002;8:23–7.

    Article  PubMed  Google Scholar 

  22. Rubinstein WS, O’Neill SM, Peters JA, et al. Mathematical modeling for breast cancer risk assessment. State of the art and role in medicine. Oncology (Huntington). 2002;16(8):1082–94.

    Google Scholar 

  23. Rhodes DJ. Identifying and counseling women at increased risk for breast cancer. Mayo Clin Proc. 2002; 77(4):355–60.

    Article  PubMed  Google Scholar 

  24. Lindor ML, Lindor RA, Apicella C, et al. Predicting BRCA1 and BRCA2 gene mutation carriers: comparison of LAMBDA, BRCAPRO, Myriad II, and modified Couch models. Familial Cancer. 2007;6:473–82.

    Article  CAS  PubMed  Google Scholar 

  25. Parmigiani P, Chen S, Iversen E, et al. Validity of models for predicting BRCA1 and BRCA2 mutations. Ann Intern Med. 2007;147:441–50.

    PubMed  Google Scholar 

  26. Parmigiani G, Berry D, Aguilar O. Determining carrier probabilities for breast cancer susceptibility genes BRCA1 and BRCA2. Am J Hum Genet. 1998;62:145–58.

    Article  CAS  PubMed  Google Scholar 

  27. Tyrer J, Duffy SW, Cuzick J. A breast cancer prediction model incorporating familial and personal risk factors. Stat Med. 2004;23:1111–30.

    Article  PubMed  Google Scholar 

  28. Martin AM, Blackwood MA, Antin-Ozerkis D, et al. Germline mutations in BRCA1 and BRCA2 in breast-ovarian families from a breast cancer risk evaluation clinic. J Clin Oncol. 2001;19:2247–53.

    CAS  PubMed  Google Scholar 

  29. Panchal S, Ennis M, Canon S, Bordeleau LJ. Selecting a BRCA risk assessment model for use in a familial cancer clinic. BMC Med Genet. 2008;9:116.

    Article  PubMed  Google Scholar 

  30. Shannon K, Lubravotich ML, Finkelstein DM, Smith B, Powell SN, Seiden MV. Model-based predictions of the BRCA1/2 mutation status in breast carcinoma patients treated at an academic medical center. Cancer. 2002;94:305–13.

    Article  CAS  PubMed  Google Scholar 

  31. James PA, Doherty R, Harris M, Mukesh BN, Milner A, Young M, et al. Optimal selection of individuals for BRCA mutation testing: a comparison of available models. J Clin Oncol. 2006;24:707–15.

    Article  CAS  PubMed  Google Scholar 

  32. Capalbo C, Ricevuto E, Vestri A, et al. Improving the accuracy of BRCA1/2 mutation prediction: validation of the novel country-customized IC software. Eur J Hum Genet. 2006;14:49–54.

    CAS  PubMed  Google Scholar 

  33. Metcalfe KA, Finch A, Poll A, et al. Breast cancer risk in women with a family history of breast or ovarian cancer who have tested negative for a BRCA1 or BRCA2 mutation. Br J Cancer. 2008;100:421–5.

    Article  PubMed  Google Scholar 

  34. American Society of Clinical Oncology policy statement update: genetic testing for cancer susceptibility. J Clin Oncol. 2003;21(12):2397–406.

    Google Scholar 

  35. US Preventive Services Task Force. Genetic risk assessment and BRCA mutation testing for breast and ovarian cancer susceptibility: recommendation statement. Ann Intern Med. 2005;143:355–61.

    Google Scholar 

Download references

Acknowledgment

Study supported by the AVON Foundation.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to P. Teller MD.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Teller, P., Hoskins, K.F., Zwaagstra, A. et al. Validation of the Pedigree Assessment Tool (PAT) in Families with BRCA1 and BRCA2 Mutations. Ann Surg Oncol 17, 240–246 (2010). https://doi.org/10.1245/s10434-009-0697-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1245/s10434-009-0697-9

Keywords

Navigation