Abstract 4623: External validation of the BOADICEA model for predicting ovarian cancer risk: The Breast Cancer Family Registry

Author(s):  
Jennifer S. Ferris ◽  
Jeanine M. Genkinger ◽  
Mary Beth Terry ◽  
Yuyan Liao ◽  
Robert J. MacInnis ◽  
...  
2018 ◽  
Vol 10 (2) ◽  
pp. 337-346 ◽  
Author(s):  
Mary Kathleen Ladd ◽  
Beth N Peshkin ◽  
Leigha Senter ◽  
Shari Baldinger ◽  
Claudine Isaacs ◽  
...  

Abstract Risk-reducing mastectomy (RRM) and salpingo-oophorectomy (RRSO) are increasingly used to reduce breast and ovarian cancer risk following BRCA1/BRCA2 testing. However, little is known about how genetic counseling influences decisions about these surgeries. Although previous studies have examined intentions prior to counseling, few have examined RRM and RRSO intentions in the critical window between genetic counseling and test result disclosure. Previous research has indicated that intentions at this time point predict subsequent uptake of surgery, suggesting that much decision-making has taken place prior to result disclosure. This period may be a critical time to better understand the drivers of prophylactic surgery intentions. The aim of this study was to examine predictors of RRM and RRSO intentions. We hypothesized that variables from the Health Belief Model would predict intentions, and we also examined the role of affective factors. Participants were 187 women, age 21–75, who received genetic counseling for hereditary breast and ovarian cancer. We utilized multiple logistic regression to identify independent predictors of intentions. 49.2% and 61.3% of participants reported intentions for RRM and RRSO, respectively. Variables associated with RRM intentions include: newly diagnosed with breast cancer (OR = 3.63, 95% CI = 1.20–11.04), perceived breast cancer risk (OR = 1.46, 95% CI = 1.17–1.81), perceived pros (OR = 1.79, 95% CI = 1.38–2.32) and cons of RRM (OR = 0.81, 95% CI = 0.65–0.996), and decision conflict (OR = 0.80, 95% CI = 0.66–0.98). Variables associated with RRSO intentions include: proband status (OR = 0.28, 95% CI = 0.09–0.89), perceived pros (OR = 1.35, 95% CI = 1.11–1.63) and cons of RRSO (OR = 0.72, 95% CI = 0.59–0.89), and ambiguity aversion (OR = 0.79, 95% CI = 0.65–0.95). These data provide support for the role of genetic counseling in fostering informed decisions about risk management, and suggest that the role of uncertainty should be explored further.


2011 ◽  
Vol 29 (34) ◽  
pp. 4505-4509 ◽  
Author(s):  
Allison W. Kurian ◽  
Gail D. Gong ◽  
Esther M. John ◽  
David A. Johnston ◽  
Anna Felberg ◽  
...  

Purpose Women with germline BRCA1 and BRCA2 mutations have five- to 20-fold increased risks of developing breast and ovarian cancer. A recent study claimed that women testing negative for their family-specific BRCA1 or BRCA2 mutation (noncarriers) have a five-fold increased risk of breast cancer. We estimated breast cancer risks for noncarriers by using a population-based sample of patients with breast cancer and their female first-degree relatives (FDRs). Patients and Methods Patients were women with breast cancer and their FDRs enrolled in the population-based component of the Breast Cancer Family Registry; patients with breast cancer were tested for BRCA1 and BRCA2 mutations, as were FDRs of identified mutation carriers. We used segregation analysis to fit a model that accommodates familial correlation in breast cancer risk due to unobserved shared risk factors. Results We studied 3,047 families; 160 had BRCA1 and 132 had BRCA2 mutations. There was no evidence of increased breast cancer risk for noncarriers of identified mutations compared with FDRs from families without BRCA1 or BRCA2 mutations: relative risk was 0.39 (95% CI, 0.04 to 3.81). Residual breast cancer correlation within families was strong, suggesting substantial risk heterogeneity in women without BRCA1 or BRCA2 mutations, with some 3.4% of them accounting for roughly one third of breast cancer cases. Conclusion These results support the practice of advising noncarriers that they do not have any increase in breast cancer risk attributable to the family-specific BRCA1 or BRCA2 mutation.


2020 ◽  
Vol 22 (1) ◽  
Author(s):  
Kelsey R. Monson ◽  
Mandy Goldberg ◽  
Hui-Chen Wu ◽  
Regina M. Santella ◽  
Wendy K. Chung ◽  
...  

Abstract Background Insulin-like growth factor 1 (IGF-1) and binding protein 3 (IGFBP-3) are associated with breast cancer in women at average risk of cancer. Less is known whether these biomarkers also predict risk in women with breast cancer family history. Methods We conducted a nested case-control study within the New York site of the Breast Cancer Family Registry (BCFR, n = 80 cases, 156 controls), a cohort enriched for breast cancer family history. Using conditional logistic regression, we estimated the association between IGF-1 and IGFBP-3 levels and breast cancer risk and examined whether this risk differed by predicted absolute breast cancer risk based on pedigree models. Results The overall association between IGF-1 or IGFBP-3 elevation (≥ median in controls) and breast cancer risk was elevated, but not statistically significant (IGF-1 OR = 1.37, 95% CI = 0.66–2.85; IGFBP-3 OR = 1.62, 95% CI = 0.81–3.24). Women with elevated predicted absolute 10-year risk ≥ 3.4% and elevated IGFBP-3 (≥ median) had more than a 3-fold increased risk compared to women with lower predicted absolute 10-year risk (< 3.4%) and low IGFBP-3 (OR = 3.47 95% CI = 1.04–11.6). Conclusions These data offer some support that the overall magnitude of the associations between IGF-1 and IGFBP3 seen in average risk cohorts may be similar in women enriched with a strong breast cancer family history.


2012 ◽  
Vol 187 (4S) ◽  
Author(s):  
Jean-Alfred Thomas ◽  
Leah Gerber ◽  
Daniel M. Moreira ◽  
Robert J. Hamilton ◽  
Lionel L. Bañez ◽  
...  

2012 ◽  
Vol 21 (4) ◽  
pp. 645-657 ◽  
Author(s):  
Fergus J. Couch ◽  
Mia M. Gaudet ◽  
Antonis C. Antoniou ◽  
Susan J. Ramus ◽  
Karoline B. Kuchenbaecker ◽  
...  

2007 ◽  
Vol 106 (2) ◽  
pp. 281-288 ◽  
Author(s):  
Mary Beth Terry ◽  
Julia A. Knight ◽  
Lydia Zablotska ◽  
Qiao Wang ◽  
Esther M. John ◽  
...  

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