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Results: 1 to 20 of 77

Cited In for PubMed (Select 16954473)

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.

A permutation method to assess heterogeneity in external validation for risk prediction models.

Wang LY, Lee WC.

PLoS One. 2015 Jan 21;10(1):e0116957. doi: 10.1371/journal.pone.0116957. eCollection 2015.

3.

The use of the Gail model, body mass index and SNPs to predict breast cancer among women with abnormal (BI-RADS 4) mammograms.

McCarthy A, Keller B, Kontos D, Boghossian L, McGuire E, Bristol M, Chen J, Domchek S, Armstrong K.

Breast Cancer Res. 2015 Jan 8;17(1):1. [Epub ahead of print]

4.

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.

5.

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.

6.

Breast density measurements using ultrasound tomography for patients undergoing tamoxifen treatment.

Sak M, Duric N, Littrup P, Li C, Bey-Knight L, Sherman M, Boyd N, Gierach G.

Proc SPIE. 2013 Mar 29;8675:86751E.

7.

Comparison of sound speed measurements on two different ultrasound tomography devices.

Sak M, Duric N, Littrup P, Bey-Knight L, Sherman M, Gierach G, Malyarenko A.

Proc Soc Photo Opt Instrum Eng. 2014 Mar 20;9040:90400S.

8.

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.

9.

Predicting invasive breast cancer versus DCIS in different age groups.

Ayvaci MU, Alagoz O, Chhatwal J, Munoz del Rio A, Sickles EA, Nassif H, Kerlikowske K, Burnside ES.

BMC Cancer. 2014 Aug 11;14:584. doi: 10.1186/1471-2407-14-584.

10.

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.

11.

Mammographic texture resemblance generalizes as an independent risk factor for breast cancer.

Nielsen M, Vachon CM, Scott CG, Chernoff K, Karemore G, Karssemeijer N, Lillholm M, Karsdal MA.

Breast Cancer Res. 2014 Apr 8;16(2):R37. doi: 10.1186/bcr3641.

12.

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.

13.

Body mass index and breast cancer risk according to postmenopausal estrogen-progestin use and hormone receptor status.

Munsell MF, Sprague BL, Berry DA, Chisholm G, Trentham-Dietz A.

Epidemiol Rev. 2014;36(1):114-36. doi: 10.1093/epirev/mxt010. Review.

14.

Update on raloxifene: role in reducing the risk of invasive breast cancer in postmenopausal women.

Vogel VG.

Breast Cancer (Dove Med Press). 2011 Oct 20;3:127-37. doi: 10.2147/BCTT.S11288. Review.

15.

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.

16.

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.

17.

Hormone replacement therapy and breast cancer: heterogeneous risks by race, weight, and breast density.

Hou N, Hong S, Wang W, Olopade OI, Dignam JJ, Huo D.

J Natl Cancer Inst. 2013 Sep 18;105(18):1365-72. doi: 10.1093/jnci/djt207. Epub 2013 Sep 3.

18.

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.

19.

Establishing a program for individuals at high risk for breast cancer.

Cadiz F, Kuerer HM, Puga J, Camacho J, Cunill E, Arun B.

J Cancer. 2013 Jul 1;4(5):433-46. doi: 10.7150/jca.6481. Print 2013.

20.

Using SNP genotypes to improve the discrimination of a simple breast cancer risk prediction model.

Dite GS, Mahmoodi M, Bickerstaffe A, Hammet F, Macinnis RJ, Tsimiklis H, Dowty JG, Apicella C, Phillips KA, Giles GG, Southey MC, Hopper JL.

Breast Cancer Res Treat. 2013 Jun;139(3):887-96. doi: 10.1007/s10549-013-2610-2. Epub 2013 Jun 18.

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