BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

164 related articles for article (PubMed ID: 22076477)

  • 1. Risk prediction models of breast cancer: a systematic review of model performances.
    Anothaisintawee T; Teerawattananon Y; Wiratkapun C; Kasamesup V; Thakkinstian A
    Breast Cancer Res Treat; 2012 May; 133(1):1-10. PubMed ID: 22076477
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Development and validation of a breast cancer risk prediction model for Thai women: a cross-sectional study.
    Anothaisintawee T; Teerawattananon Y; Wiratkapun C; Srinakarin J; Woodtichartpreecha P; Hirunpat S; Wongwaisayawan S; Lertsithichai P; Kasamesup V; Thakkinstian A
    Asian Pac J Cancer Prev; 2014; 15(16):6811-7. PubMed ID: 25169530
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Extensions of the Rosner-Colditz breast cancer prediction model to include older women and type-specific predicted risk.
    Glynn RJ; Colditz GA; Tamimi RM; Chen WY; Hankinson SE; Willett WW; Rosner B
    Breast Cancer Res Treat; 2017 Aug; 165(1):215-223. PubMed ID: 28589369
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance.
    Meads C; Ahmed I; Riley RD
    Breast Cancer Res Treat; 2012 Apr; 132(2):365-77. PubMed ID: 22037780
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Impact of adding breast density to breast cancer risk models: A systematic review.
    Vilmun BM; Vejborg I; Lynge E; Lillholm M; Nielsen M; Nielsen MB; Carlsen JF
    Eur J Radiol; 2020 Jun; 127():109019. PubMed ID: 32361308
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Predicting risk of breast cancer in postmenopausal women by hormone receptor status.
    Chlebowski RT; Anderson GL; Lane DS; Aragaki AK; Rohan T; Yasmeen S; Sarto G; Rosenberg CA; Hubbell FA;
    J Natl Cancer Inst; 2007 Nov; 99(22):1695-705. PubMed ID: 18000216
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Gail model for prediction of absolute risk of invasive breast cancer: independent evaluation in the Florence-European Prospective Investigation Into Cancer and Nutrition cohort.
    Decarli A; Calza S; Masala G; Specchia C; Palli D; Gail MH
    J Natl Cancer Inst; 2006 Dec; 98(23):1686-93. PubMed ID: 17148770
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Comparison of Questionnaire-Based Breast Cancer Prediction Models in the Nurses' Health Study.
    Glynn RJ; Colditz GA; Tamimi RM; Chen WY; Hankinson SE; Willett WW; Rosner B
    Cancer Epidemiol Biomarkers Prev; 2019 Jul; 28(7):1187-1194. PubMed ID: 31015199
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Breast cancer risk prediction: an update to the Rosner-Colditz breast cancer incidence model.
    Rice MS; Tworoger SS; Hankinson SE; Tamimi RM; Eliassen AH; Willett WC; Colditz G; Rosner B
    Breast Cancer Res Treat; 2017 Nov; 166(1):227-240. PubMed ID: 28702896
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Prognostic models for complete recovery in ischemic stroke: a systematic review and meta-analysis.
    Jampathong N; Laopaiboon M; Rattanakanokchai S; Pattanittum P
    BMC Neurol; 2018 Mar; 18(1):26. PubMed ID: 29523104
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A comparison between different prediction models for invasive breast cancer occurrence in the French E3N cohort.
    Dartois L; Gauthier É; Heitzmann J; Baglietto L; Michiels S; Mesrine S; Boutron-Ruault MC; Delaloge S; Ragusa S; Clavel-Chapelon F; Fagherazzi G
    Breast Cancer Res Treat; 2015 Apr; 150(2):415-26. PubMed ID: 25744293
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Review of non-clinical risk models to aid prevention of breast cancer.
    Al-Ajmi K; Lophatananon A; Yuille M; Ollier W; Muir KR
    Cancer Causes Control; 2018 Oct; 29(10):967-986. PubMed ID: 30178398
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Breast cancer risk prediction with a log-incidence model: evaluation of accuracy.
    Rockhill B; Byrne C; Rosner B; Louie MM; Colditz G
    J Clin Epidemiol; 2003 Sep; 56(9):856-61. PubMed ID: 14505770
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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; Bernstein L
    Breast Cancer Res Treat; 2013 Nov; 142(1):187-202. PubMed ID: 24158759
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A systematic review and quality assessment of individualised breast cancer risk prediction models.
    Louro J; Posso M; Hilton Boon M; Román M; Domingo L; Castells X; Sala M
    Br J Cancer; 2019 Jul; 121(1):76-85. PubMed ID: 31114019
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Development of a Breast Cancer Risk Prediction Model for Women in Nigeria.
    Wang S; Ogundiran T; Ademola A; Olayiwola OA; Adeoye A; Sofoluwe A; Morhason-Bello I; Odedina S; Agwai I; Adebamowo C; Obajimi M; Ojengbede O; Olopade OI; Huo D
    Cancer Epidemiol Biomarkers Prev; 2018 Jun; 27(6):636-643. PubMed ID: 29678902
    [No Abstract]   [Full Text] [Related]  

  • 17. Prediction models for endometrial cancer for the general population or symptomatic women: A systematic review.
    Alblas M; Velt KB; Pashayan N; Widschwendter M; Steyerberg EW; Vergouwe Y
    Crit Rev Oncol Hematol; 2018 Jun; 126():92-99. PubMed ID: 29759571
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Risk prediction models for incident primary cutaneous melanoma: a systematic review.
    Vuong K; McGeechan K; Armstrong BK; Cust AE
    JAMA Dermatol; 2014 Apr; 150(4):434-44. PubMed ID: 24522401
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Risk prediction for breast Cancer in Han Chinese women based on a cause-specific Hazard model.
    Wang L; Liu L; Lou Z; Ding L; Guan H; Wang F; Yu L; Xiang Y; Zhou F; Xue F; Yu Z
    BMC Cancer; 2019 Feb; 19(1):128. PubMed ID: 30732565
    [TBL] [Abstract][Full Text] [Related]  

  • 20.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 9.