These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

66 related articles for article (PubMed ID: 11578948)

  • 1. [Statistical analysis of a prognostic study].
    Laplanche A; Mahé C
    Bull Cancer; 2001 Aug; 88(8):805-10. PubMed ID: 11578948
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Prognostic variables and prognostic groups for malignant melanoma. The information from Cox and Classification And Regression Trees analysis: an Italian population-based study.
    Crocetti E; Mangone L; Lo Scocco G; Carli P
    Melanoma Res; 2006 Oct; 16(5):429-33. PubMed ID: 17013092
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Construction and validation of a prognostic model across several studies, with an application in superficial bladder cancer.
    Royston P; Parmar MK; Sylvester R
    Stat Med; 2004 Mar; 23(6):907-26. PubMed ID: 15027080
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Penalized Cox regression analysis in the high-dimensional and low-sample size settings, with applications to microarray gene expression data.
    Gui J; Li H
    Bioinformatics; 2005 Jul; 21(13):3001-8. PubMed ID: 15814556
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Partial Cox regression analysis for high-dimensional microarray gene expression data.
    Li H; Gui J
    Bioinformatics; 2004 Aug; 20 Suppl 1():i208-15. PubMed ID: 15262801
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A SAS macro for estimation of direct adjusted survival curves based on a stratified Cox regression model.
    Zhang X; Loberiza FR; Klein JP; Zhang MJ
    Comput Methods Programs Biomed; 2007 Nov; 88(2):95-101. PubMed ID: 17850917
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Aerodigestive tract invasion by well-differentiated thyroid carcinoma: diagnosis, management, prognosis, and biology.
    McCaffrey JC
    Laryngoscope; 2006 Jan; 116(1):1-11. PubMed ID: 16481800
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Predictive survival model with time-dependent prognostic factors: development of computer-aided SAS Macro program.
    Chen LS; Yen MF; Wu HM; Liao CS; Liou DM; Kuo HS; Chen TH
    J Eval Clin Pract; 2005 Apr; 11(2):181-93. PubMed ID: 15813715
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Explained variation in survival analysis.
    Schemper M; Stare J
    Stat Med; 1996 Oct; 15(19):1999-2012. PubMed ID: 8896135
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Generating survival times to simulate Cox proportional hazards models.
    Bender R; Augustin T; Blettner M
    Stat Med; 2005 Jun; 24(11):1713-23. PubMed ID: 15724232
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects.
    Royston P; Parmar MK
    Stat Med; 2002 Aug; 21(15):2175-97. PubMed ID: 12210632
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Risk stratification using stress echocardiography: incremental prognostic value over historic, clinical, and stress electrocardiographic variables across a wide spectrum of bayesian pretest probabilities for coronary artery disease.
    Bangalore S; Gopinath D; Yao SS; Chaudhry FA
    J Am Soc Echocardiogr; 2007 Mar; 20(3):244-52. PubMed ID: 17336749
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A relative survival regression model using B-spline functions to model non-proportional hazards.
    Giorgi R; Abrahamowicz M; Quantin C; Bolard P; Esteve J; Gouvernet J; Faivre J
    Stat Med; 2003 Sep; 22(17):2767-84. PubMed ID: 12939785
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Prognostic factors in patients with advanced biliary tract cancer receiving chemotherapy.
    Saisho T; Okusaka T; Ueno H; Morizane C; Okada S
    Hepatogastroenterology; 2005; 52(66):1654-8. PubMed ID: 16334750
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Adaptive risk group refinement.
    LeBlanc M; Moon J; Crowley J
    Biometrics; 2005 Jun; 61(2):370-8. PubMed ID: 16011683
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Assessing time-by-covariate interactions in relative survival models using restrictive cubic spline functions.
    Bolard P; Quantin C; Abrahamowicz M; Esteve J; Giorgi R; Chadha-Boreham H; Binquet C; Faivre J
    J Cancer Epidemiol Prev; 2002; 7(3):113-22. PubMed ID: 12665210
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Regression analysis of doubly censored failure time data using the additive hazards model.
    Sun L; Kim YJ; Sun J
    Biometrics; 2004 Sep; 60(3):637-43. PubMed ID: 15339285
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Logical analysis of survival data: prognostic survival models by detecting high-degree interactions in right-censored data.
    Kronek LP; Reddy A
    Bioinformatics; 2008 Aug; 24(16):i248-53. PubMed ID: 18689833
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Comparing proportional hazards and accelerated failure time models for survival analysis.
    Orbe J; Ferreira E; Núñez-Antón V
    Stat Med; 2002 Nov; 21(22):3493-510. PubMed ID: 12407686
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Prognostic factors and clinicopathologic characteristics of invasive adenocarcinoma of the uterine cervix.
    Chargui R; Damak T; Khomsi F; Ben Hassouna J; Chaieb W; Hechiche M; Gamoudi A; Boussen H; Benna F; Rahal K
    Am J Obstet Gynecol; 2006 Jan; 194(1):43-8. PubMed ID: 16389008
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 4.