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

Standard

Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants. / Evans, D Gareth; Harkness, Elaine; Brentnall, Adam; Van Veen, Elke; Astley, Susan; Byers, Helen; Sampson, Sarah; Southworth, Jake; Stavrinos, Paula; Howell, Sacha; Maxwell, Anthony; Howell, Anthony; Newman, William; Cuzick, Jack.

In: Breast Cancer Research and Treatment, 2019.

Research output: Contribution to journalArticle

Harvard

APA

Vancouver

Author

Bibtex

@article{c5f1b6e5452d49ae967d5df3e50bec42,
title = "Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants",
abstract = "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.Methods: 9362 of 57,902 women in the Predicting-Risk-Of-Cancer-At-Screening (PROCAS) study who were unaffected by breast cancer at study entry and provided DNA for a polygenic risk score (PRS). The PRS was analysed alongside mammographic density (density-residual-DR) and standard risk factors (Tyrer-Cuzick-model) to assess future risk of breast cancer based on tumour stage receptor expression and pathology.Results: 195 prospective incident breast cancers had a prediction based on TC/DR/PRS which was informative for subsequent breast cancer overall (IQ-OR=2.25 (95{\%}CI:1.89-2.68)) with excellent calibration-(0.99). The model performed particularly well in predicting higher stage (stage 2+ IQ-OR=2.69 (95{\%}CI:2.02–3.60) and ER+ BCs (IQ-OR=2.36 (95{\%}CI:1.93–2.89)). DR was most predictive for HER2+ and stage 2+ cancers but did not discriminate as well between poor and extremely good prognosis BC as either Tyrer-Cuzick or PRS. In contrast PRS gave the highest OR for incident stage 2+ cancers, (IQR-OR=1.79 (95{\%}CI:1.30-2.46)). Conclusions: A combined approach using Tyrer-Cuzick/DR/PRS provides accurate risk stratification, particularly for poor prognosis cancers. This provides support for reducing the screening interval in high-risk women and increasing the screening interval in low-risk women defined by this model.",
keywords = "SNPs, Polygenic Risk score, Breast cancer, mammographic density, pathology, Early detection",
author = "Evans, {D Gareth} and Elaine Harkness and Adam Brentnall and {Van Veen}, Elke and Susan Astley and Helen Byers and Sarah Sampson and Jake Southworth and Paula Stavrinos and Sacha Howell and Anthony Maxwell and Anthony Howell and William Newman and Jack Cuzick",
year = "2019",
doi = "10.1007/s10549-019-05210-2",
language = "English",
journal = "Breast Cancer Research and Treatment",
issn = "0167-6806",
publisher = "Springer Nature",

}

RIS

TY - JOUR

T1 - Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants

AU - Evans, D Gareth

AU - Harkness, Elaine

AU - Brentnall, Adam

AU - Van Veen, Elke

AU - Astley, Susan

AU - Byers, Helen

AU - Sampson, Sarah

AU - Southworth, Jake

AU - Stavrinos, Paula

AU - Howell, Sacha

AU - Maxwell, Anthony

AU - Howell, Anthony

AU - Newman, William

AU - Cuzick, Jack

PY - 2019

Y1 - 2019

N2 - 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.Methods: 9362 of 57,902 women in the Predicting-Risk-Of-Cancer-At-Screening (PROCAS) study who were unaffected by breast cancer at study entry and provided DNA for a polygenic risk score (PRS). The PRS was analysed alongside mammographic density (density-residual-DR) and standard risk factors (Tyrer-Cuzick-model) to assess future risk of breast cancer based on tumour stage receptor expression and pathology.Results: 195 prospective incident breast cancers had a prediction based on TC/DR/PRS which was informative for subsequent breast cancer overall (IQ-OR=2.25 (95%CI:1.89-2.68)) with excellent calibration-(0.99). The model performed particularly well in predicting higher stage (stage 2+ IQ-OR=2.69 (95%CI:2.02–3.60) and ER+ BCs (IQ-OR=2.36 (95%CI:1.93–2.89)). DR was most predictive for HER2+ and stage 2+ cancers but did not discriminate as well between poor and extremely good prognosis BC as either Tyrer-Cuzick or PRS. In contrast PRS gave the highest OR for incident stage 2+ cancers, (IQR-OR=1.79 (95%CI:1.30-2.46)). Conclusions: A combined approach using Tyrer-Cuzick/DR/PRS provides accurate risk stratification, particularly for poor prognosis cancers. This provides support for reducing the screening interval in high-risk women and increasing the screening interval in low-risk women defined by this model.

AB - 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.Methods: 9362 of 57,902 women in the Predicting-Risk-Of-Cancer-At-Screening (PROCAS) study who were unaffected by breast cancer at study entry and provided DNA for a polygenic risk score (PRS). The PRS was analysed alongside mammographic density (density-residual-DR) and standard risk factors (Tyrer-Cuzick-model) to assess future risk of breast cancer based on tumour stage receptor expression and pathology.Results: 195 prospective incident breast cancers had a prediction based on TC/DR/PRS which was informative for subsequent breast cancer overall (IQ-OR=2.25 (95%CI:1.89-2.68)) with excellent calibration-(0.99). The model performed particularly well in predicting higher stage (stage 2+ IQ-OR=2.69 (95%CI:2.02–3.60) and ER+ BCs (IQ-OR=2.36 (95%CI:1.93–2.89)). DR was most predictive for HER2+ and stage 2+ cancers but did not discriminate as well between poor and extremely good prognosis BC as either Tyrer-Cuzick or PRS. In contrast PRS gave the highest OR for incident stage 2+ cancers, (IQR-OR=1.79 (95%CI:1.30-2.46)). Conclusions: A combined approach using Tyrer-Cuzick/DR/PRS provides accurate risk stratification, particularly for poor prognosis cancers. This provides support for reducing the screening interval in high-risk women and increasing the screening interval in low-risk women defined by this model.

KW - SNPs

KW - Polygenic Risk score

KW - Breast cancer

KW - mammographic density

KW - pathology

KW - Early detection

U2 - 10.1007/s10549-019-05210-2

DO - 10.1007/s10549-019-05210-2

M3 - Article

JO - Breast Cancer Research and Treatment

JF - Breast Cancer Research and Treatment

SN - 0167-6806

ER -