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Results: 1 to 20 of 64

Cited In for PubMed (Select 18316752)

1.

Associations between breast density and a panel of single nucleotide polymorphisms linked to breast cancer risk: a cohort study with digital mammography.

Keller BM, McCarthy AM, Chen J, Armstrong K, Conant EF, Domchek SM, Kontos D.

BMC Cancer. 2015;15(1):1159. doi: 10.1186/s12885-015-1159-3. Epub 2015 Mar 18.

2.

Breast cancer in women younger than 30 years: prevalence rate and imaging findings in a symptomatic population.

Makanjuola D, Alkushi A, Alzaid M, Abukhair O, Al Tahan F, Alhadab A.

Pan Afr Med J. 2014 Sep 16;19:35. doi: 10.11604/pamj.2014.19.35.2849. eCollection 2014.

3.

Emerging Concepts in Breast Cancer Risk Prediction.

Gierach GL, Yang XR, Figueroa JD, Sherman ME.

Curr Obstet Gynecol Rep. 2013 Mar;2(1):43-52.

4.

Risk determination and prevention of breast cancer.

Howell A, Anderson AS, Clarke RB, Duffy SW, Evans DG, Garcia-Closas M, Gescher AJ, Key TJ, Saxton JM, Harvie MN.

Breast Cancer Res. 2014 Sep 28;16(5):446. doi: 10.1186/s13058-014-0446-2.

5.

Mammographic breast density refines Tyrer-Cuzick estimates of breast cancer risk in high-risk women: findings from the placebo arm of the International Breast Cancer Intervention Study I.

Warwick J, Birke H, Stone J, Warren RM, Pinney E, Brentnall AR, Duffy SW, Howell A, Cuzick J.

Breast Cancer Res. 2014 Oct 8;16(5):451. doi: 10.1186/s13058-014-0451-5.

6.

Breast Cancer Risk - Genes, Environment and Clinics.

Fasching PA, Ekici AB, Adamietz BR, Wachter DL, Hein A, Bayer CM, Häberle L, Loehberg CR, Jud SM, Heusinger K, Rübner M, Rauh C, Bani MR, Lux MP, Schulz-Wendtland R, Hartmann A, Beckmann MW.

Geburtshilfe Frauenheilkd. 2011 Dec;71(12):1056-1066.

7.

Current strategies for the prevention of breast cancer.

Advani P, Moreno-Aspitia A.

Breast Cancer (Dove Med Press). 2014 May 2;6:59-71. doi: 10.2147/BCTT.S39114. eCollection 2014. Review.

8.

Breast Cancer Risk - From Genetics to Molecular Understanding of Pathogenesis.

Fasching PA, Ekici AB, Wachter DL, Hein A, Bayer CM, Häberle L, Loehberg CR, Schneider M, Jud SM, Heusinger K, Rübner M, Rauh C, Bani MR, Lux MP, Schulz-Wendtland R, Hartmann A, Beckmann MW.

Geburtshilfe Frauenheilkd. 2013 Dec;73(12):1228-1235.

9.

A randomized, controlled trial to increase discussion of breast cancer in primary care.

Kaplan CP, Livaudais-Toman J, Tice JA, Kerlikowske K, Gregorich SE, Pérez-Stable EJ, Pasick RJ, Chen A, Quinn J, Karliner LS.

Cancer Epidemiol Biomarkers Prev. 2014 Jul;23(7):1245-53. doi: 10.1158/1055-9965.EPI-13-1380. Epub 2014 Apr 24.

10.

Cost-effectiveness and harm-benefit analyses of risk-based screening strategies for breast cancer.

Vilaprinyo E, Forné C, Carles M, Sala M, Pla R, Castells X, Domingo L, Rue M; Interval Cancer (INCA) Study Group.

PLoS One. 2014 Feb 3;9(2):e86858. doi: 10.1371/journal.pone.0086858. eCollection 2014.

11.

Development of a personalized decision aid for breast cancer risk reduction and management.

Ozanne EM, Howe R, Omer Z, Esserman LJ.

BMC Med Inform Decis Mak. 2014 Jan 14;14:4. doi: 10.1186/1472-6947-14-4.

12.

Agreement of mammographic measures of volumetric breast density to MRI.

Wang J, Azziz A, Fan B, Malkov S, Klifa C, Newitt D, Yitta S, Hylton N, Kerlikowske K, Shepherd JA.

PLoS One. 2013 Dec 4;8(12):e81653. doi: 10.1371/journal.pone.0081653. eCollection 2013.

13.

An assessment of existing models for individualized breast cancer risk estimation in a screening program in Spain.

Arrospide A, Forné C, Rué M, Torà N, Mar J, Baré M.

BMC Cancer. 2013 Dec 10;13:587. doi: 10.1186/1471-2407-13-587.

14.

Prediction of near-term breast cancer risk based on bilateral mammographic feature asymmetry.

Tan M, Zheng B, Ramalingam P, Gur D.

Acad Radiol. 2013 Dec;20(12):1542-50. doi: 10.1016/j.acra.2013.08.020.

15.

Mammographic density and risk of breast cancer by age and tumor characteristics.

Bertrand KA, Tamimi RM, Scott CG, Jensen MR, Pankratz V, Visscher D, Norman A, Couch F, Shepherd J, Fan B, Chen YY, Ma L, Beck AH, Cummings SR, Kerlikowske K, Vachon CM.

Breast Cancer Res. 2013 Nov 4;15(6):R104. doi: 10.1186/bcr3570.

16.

Validation of Rosner-Colditz breast cancer incidence model using an independent data set, the California Teachers Study.

Rosner BA, Colditz GA, Hankinson SE, Sullivan-Halley J, Lacey JV Jr, Bernstein L.

Breast Cancer Res Treat. 2013 Nov;142(1):187-202. doi: 10.1007/s10549-013-2719-3. Epub 2013 Oct 26.

17.

Risk prediction for breast, endometrial, and ovarian cancer in white women aged 50 y or older: derivation and validation from population-based cohort studies.

Pfeiffer RM, Park Y, Kreimer AR, Lacey JV Jr, Pee D, Greenlee RT, Buys SS, Hollenbeck A, Rosner B, Gail MH, Hartge P.

PLoS Med. 2013;10(7):e1001492. doi: 10.1371/journal.pmed.1001492. Epub 2013 Jul 30.

18.

Benign breast disease, mammographic breast density, and the risk of breast cancer.

Tice JA, O'Meara ES, Weaver DL, Vachon C, Ballard-Barbash R, Kerlikowske K.

J Natl Cancer Inst. 2013 Jul 17;105(14):1043-9. doi: 10.1093/jnci/djt124. Epub 2013 Jun 6.

19.

Short-term outcomes of screening mammography using computer-aided detection: a population-based study of medicare enrollees.

Fenton JJ, Xing G, Elmore JG, Bang H, Chen SL, Lindfors KK, Baldwin LM.

Ann Intern Med. 2013 Apr 16;158(8):580-7. doi: 10.7326/0003-4819-158-8-201304160-00002.

20.

Mammographic parenchymal patterns as an imaging marker of endogenous hormonal exposure: a preliminary study in a high-risk population.

Daye D, Keller B, Conant EF, Chen J, Schnall MD, Maidment AD, Kontos D.

Acad Radiol. 2013 May;20(5):635-46. doi: 10.1016/j.acra.2012.12.016.

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