Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants

D. Gareth Evans,Elaine F. Harkness,Adam R. Brentnall,Elke M. van Veen,Susan M. Astley,Helen Byers,Sarah Sampson,Jake Southworth,Paula Stavrinos,Sacha J Howell,A. Maxwell,Anthony Howell,William G. Newman,Jack Cuzick

Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants

2019

D. Gareth Evans
Elaine F. Harkness
Adam R. Brentnall
Elke M. van Veen
Susan M. Astley
Helen Byers
Sarah Sampson
Jake Southworth
Paula Stavrinos
Sacha J Howell
A. Maxwell
Anthony Howell
William G. Newman
Jack Cuzick

Purpose To improve breast cancer risk stratification to enable more targeted early detection/prevention strategies that will better balance risks and benefits of population screening programmes.

Keywords:

Cancer research
Breast cancer
Oncology
Medicine
Internal medicine
Population
MAMMOGRAPHIC DENSITY
Single-nucleotide polymorphism
receptor expression
polygenic risk score
early detection
Pathology
genetic variants
risk stratification

Correction
Source
Cite
Save
Machine Reading By IdeaReader

References

Citations