scholarly journals Personalizing Breast Cancer Screening Based on Polygenic Risk and Family History

Author(s):  
Jeroen J van den Broek ◽  
Clyde B Schechter ◽  
Nicolien T van Ravesteyn ◽  
A Cecile J W Janssens ◽  
Michael C Wolfson ◽  
...  

Abstract Background We assessed the clinical utility of a first-degree breast cancer family history and polygenic risk score (PRS) to inform screening decisions among women aged 30-50 years. Methods Two established breast cancer models evaluated digital mammography screening strategies in the 1985 US birth cohort by risk groups defined by family history and PRS based on 313 single nucleotide polymorphisms. Strategies varied in initiation age (30, 35, 40, 45, and 50 years) and interval (annual, hybrid, biennial, triennial). The benefits (breast cancer deaths averted, life-years gained) and harms (false-positive mammograms, overdiagnoses) were compared with those seen with 3 established screening guidelines. Results Women with a breast cancer family history who initiated biennial screening at age 40 years (vs 50 years) had a 36% (model range = 29%-40%) increase in life-years gained and 20% (model range = 16%-24%) more breast cancer deaths averted, but 21% (model range = 17%-23%) more overdiagnoses and 63% (model range = 62%-64%) more false positives. Screening tailored to PRS vs biennial screening from 50 to 74 years had smaller positive effects on life-years gained (20%) and breast cancer deaths averted (11%) but also smaller increases in overdiagnoses (10%) and false positives (26%). Combined use of family history and PRS vs biennial screening from 50 to 74 years had the greatest increase in life-years gained (29%) and breast cancer deaths averted (18%). Conclusions Our results suggest that breast cancer family history and PRS could guide screening decisions before age 50 years among women at increased risk for breast cancer but expected increases in overdiagnoses and false positives should be expected.

1988 ◽  
Vol 11 (3) ◽  
pp. 263-267 ◽  
Author(s):  
Henry T. Lynch ◽  
Patrice Watson ◽  
Theresa Conway ◽  
Mary Lee Fitzsimmons ◽  
Jane Lynch

The Breast ◽  
1997 ◽  
Vol 6 (4) ◽  
pp. 253-254
Author(s):  
P. Hopwood ◽  
F. Keeling ◽  
J. Thompson ◽  
C. Pool ◽  
A. Howell ◽  
...  

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.


2013 ◽  
Vol 13 (1) ◽  
pp. 99-107 ◽  
Author(s):  
Fabienne Dominique Schwab ◽  
Nicole Bürki ◽  
Dorothy Jane Huang ◽  
Viola Heinzelmann-Schwarz ◽  
Seraina Margaretha Schmid ◽  
...  

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

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