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Genetic Susceptibility Risk Models in Clinical Decision Making

Genetic Susceptibility Risk Models in Clinical Decision Making. Susan M. Domchek, MD Abramson Cancer Center University of Pennsylvania. Oncologist. PCP. Self-referral. Cancer Risk Evaluation Program. Models. >10%. <10%. Genetic Testing. Gail and Claus. +. -. >25%. BSO

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Genetic Susceptibility Risk Models in Clinical Decision Making

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  1. Genetic Susceptibility Risk Models in Clinical Decision Making Susan M. Domchek, MD Abramson Cancer Center University of Pennsylvania

  2. Oncologist PCP Self-referral Cancer Risk Evaluation Program Models >10% <10% Genetic Testing Gail and Claus + - >25% BSO Screening studies Prevention studies PM Screening studies Chemoprevention

  3. BRCA prediction models • Logistic regression models (Couch, Shattuck-Eidens, Frank) • Bayesian formulations (BRCAPRO) • Empiric tables (Frank 2002) • Prevalence tables • Unique attributes to each model • Consideration of testing for women with a probability of 10%

  4. Limitations of family history • Adoption • Small family size, especially women • Prevalence tables can be very helpful • Early deaths • Accuracy of cancer information • Stomach cancer in women • Obtain medical records whenever possible

  5. Limitations of all models • Race/ethnicity data • How to handle DCIS • LCIS • “Other” cancers – pancreatic cancer, melanoma, early prostate

  6. Variability in models Myriad Tables: 21.2% (47% in 2 <50) Couch: 7.7% for family BRCAPro: Dependent on proband – 55% vs 1.6%

  7. What is the goal of prior probability models? • Identify candidates for testing for BRCA1/BRCA2 • Do we care more about sensitivity or specificity? • Clinically: sensitivity • Economically: specificity • Stratify risk of hereditary syndromes • In tested negative families should we do counseling based on PP models?

  8. 5/11/2004 “False” negative: what to counsel? 6 7 BR_CA 28 OV_CA d. 55 d. 48 15 62 14 59 3 2 BR_CA 52 Panc_CA 55 Skin_CA 78 d. 60 d. 55 63 64 65 60 87 1 8 9 10 11 Liver_CA Panc_CA BR_CA 48 Eye_Melan 38 d. 10 d. 7 d. 45 d. 47

  9. 4/26/2004 10 11 OV_CA 42 d. unk d. 42 7 6 5 4 Pros_CA 80 Colon_CA 61 d. 63 d. 83 d. 64 12 13 3 2 Lung_CA 76 OV_CA 69 d. 56 d. 81 d. 70 1 8 9 Which syndrome? What ovarian cancer risk?

  10. Can pathologic features help? • BRCA1 mutation related breast cancers • 90% are estrogen receptor negative • High grade, aneuploid, “pushing margins” • 3% are HER2/neu positive • BRCA2 mutation related breast cancers • More like sporadic tumors • Approximately 50% are ER positve • Only 3% HER2/neu positive

  11. Probability of BRCA1 mutation by age, ER status and grade ER positive tumors Lahkini et al, JCO 2002

  12. Probability of BRCA1 mutation by age, ER status and grade ER positive tumors

  13. Claus and Gail in Hereditary Families

  14. Issues in clinical decision making • “Hereditary” patterns that test negative • How to define them? • Is breast cancer risk assessment accurate? • What is their ovarian cancer risk? • Risk assessment in VUS?

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