Sort by

Send to

Choose Destination

Links from PubMed

Items: 1 to 20 of 111


Relationship of Predicted Risk of Developing Invasive Breast Cancer, as Assessed with Three Models, and Breast Cancer Mortality among Breast Cancer Patients.

Sherman ME, Ichikawa L, Pfeiffer RM, Miglioretti DL, Kerlikowske K, Tice J, Vacek PM, Gierach GL.

PLoS One. 2016 Aug 25;11(8):e0160966. doi: 10.1371/journal.pone.0160966.


Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case-control study.

Winkel RR, von Euler-Chelpin M, Nielsen M, Petersen K, Lillholm M, Nielsen MB, Lynge E, Uldall WY, Vejborg I.

BMC Cancer. 2016 Jul 7;16:414. doi: 10.1186/s12885-016-2450-7.


Breast cancer risk feedback to women in the UK NHS breast screening population.

Evans DG, Donnelly LS, Harkness EF, Astley SM, Stavrinos P, Dawe S, Watterson D, Fox L, Sergeant JC, Ingham S, Harvie MN, Wilson M, Beetles U, Buchan I, Brentnall AR, French DP, Cuzick J, Howell A.

Br J Cancer. 2016 Apr 26;114(9):1045-52. doi: 10.1038/bjc.2016.56.


Mammographic Breast Density Evaluation in Korean Women Using Fully Automated Volumetric Assessment.

Youn I, Choi S, Kook SH, Choi YJ.

J Korean Med Sci. 2016 Mar;31(3):457-62. doi: 10.3346/jkms.2016.31.3.457.


Risk of breast cancer after false-positive results in mammographic screening.

Román M, Castells X, Hofvind S, von Euler-Chelpin M.

Cancer Med. 2016 Jun;5(6):1298-306. doi: 10.1002/cam4.646.


Quantra™ should be considered a tool for two-grade scale mammographic breast density classification.

Ekpo EU, McEntee MF, Rickard M, Brennan PC, Kunduri J, Demchig D, Mello-Thoms C.

Br J Radiol. 2016;89(1060):20151057. doi: 10.1259/bjr.20151057.


Integrative modeling of multi-omics data to identify cancer drivers and infer patient-specific gene activity.

Pavel AB, Sonkin D, Reddy A.

BMC Syst Biol. 2016 Feb 11;10:16. doi: 10.1186/s12918-016-0260-9.


Between-race differences in the effects of breast density information and information about new imaging technology on breast-health decision-making.

Manning M, Purrington K, Penner L, Duric N, Albrecht TL.

Patient Educ Couns. 2016 Jun;99(6):1002-10. doi: 10.1016/j.pec.2016.01.010.


Stromal characteristics may hold the key to mammographic density: the evidence to date.

Ironside AJ, Jones JL.

Oncotarget. 2016 May 24;7(21):31550-62. doi: 10.18632/oncotarget.6912. Review.


Breast Cancer Risk Prediction Using Clinical Models and 77 Independent Risk-Associated SNPs for Women Aged Under 50 Years: Australian Breast Cancer Family Registry.

Dite GS, MacInnis RJ, Bickerstaffe A, Dowty JG, Allman R, Apicella C, Milne RL, Tsimiklis H, Phillips KA, Giles GG, Terry MB, Southey MC, Hopper JL.

Cancer Epidemiol Biomarkers Prev. 2016 Feb;25(2):359-65. doi: 10.1158/1055-9965.EPI-15-0838.


Increased Risk of Developing Breast Cancer after a False-Positive Screening Mammogram.

Henderson LM, Hubbard RA, Sprague BL, Zhu W, Kerlikowske K.

Cancer Epidemiol Biomarkers Prev. 2015 Dec;24(12):1882-9. doi: 10.1158/1055-9965.EPI-15-0623.


Mammographic density adds accuracy to both the Tyrer-Cuzick and Gail breast cancer risk models in a prospective UK screening cohort.

Brentnall AR, Harkness EF, Astley SM, Donnelly LS, Stavrinos P, Sampson S, Fox L, Sergeant JC, Harvie MN, Wilson M, Beetles U, Gadde S, Lim Y, Jain A, Bundred S, Barr N, Reece V, Howell A, Cuzick J, Evans DG.

Breast Cancer Res. 2015 Dec 1;17(1):147. doi: 10.1186/s13058-015-0653-5.


Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy.

Burnside ES, Liu J, Wu Y, Onitilo AA, McCarty CA, Page CD, Peissig PL, Trentham-Dietz A, Kitchner T, Fan J, Yuan M.

Acad Radiol. 2016 Jan;23(1):62-9. doi: 10.1016/j.acra.2015.09.007.


An age-period-cohort analysis of female breast cancer mortality from 1990-2009 in China.

Li C, Yu C, Wang P.

Int J Equity Health. 2015 Sep 14;14:76. doi: 10.1186/s12939-015-0211-x.


The relationship of breast density in mammography and magnetic resonance imaging in high-risk women and women with breast cancer.

Albert M, Schnabel F, Chun J, Schwartz S, Lee J, Klautau Leite AP, Moy L.

Clin Imaging. 2015 Nov-Dec;39(6):987-92. doi: 10.1016/j.clinimag.2015.08.001.


Quantification of Regional Breast Density in Four Quadrants Using 3D MRI-A Pilot Study.

Fwu PT, Chen JH, Li Y, Chan S, Su MY.

Transl Oncol. 2015 Aug;8(4):250-7. doi: 10.1016/j.tranon.2015.04.005.


Lifetime and 5 years risk of breast cancer and attributable risk factor according to Gail model in Iranian women.

Mohammadbeigi A, Mohammadsalehi N, Valizadeh R, Momtaheni Z, Mokhtari M, Ansari H.

J Pharm Bioallied Sci. 2015 Jul-Sep;7(3):207-11. doi: 10.4103/0975-7406.160020.


Can the breast screening appointment be used to provide risk assessment and prevention advice?

Evans DG, Howell A.

Breast Cancer Res. 2015 Jul 9;17:84. doi: 10.1186/s13058-015-0595-y.


Are Qualitative Assessments of Background Parenchymal Enhancement, Amount of Fibroglandular Tissue on MR Images, and Mammographic Density Associated with Breast Cancer Risk?

Dontchos BN, Rahbar H, Partridge SC, Korde LA, Lam DL, Scheel JR, Peacock S, Lehman CD.

Radiology. 2015 Aug;276(2):371-80. doi: 10.1148/radiol.2015142304.


Inter-observer agreement according to three methods of evaluating mammographic density and parenchymal pattern in a case control study: impact on relative risk of breast cancer.

Winkel RR, von Euler-Chelpin M, Nielsen M, Diao P, Nielsen MB, Uldall WY, Vejborg I.

BMC Cancer. 2015 Apr 12;15:274. doi: 10.1186/s12885-015-1256-3.

Items per page

Supplemental Content

Support Center