BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

265 related articles for article (PubMed ID: 30548627)

  • 1. Predictive probability of success using surrogate endpoints.
    Saint-Hilary G; Barboux V; Pannaux M; Gasparini M; Robert V; Mastrantonio G
    Stat Med; 2019 May; 38(10):1753-1774. PubMed ID: 30548627
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Simulation optimization for Bayesian multi-arm multi-stage clinical trial with binary endpoints.
    Yu Z; Ramakrishnan V; Meinzer C
    J Biopharm Stat; 2019; 29(2):306-317. PubMed ID: 30763151
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Decision-making in drug development using a composite definition of success.
    Saint-Hilary G; Robert V; Gasparini M
    Pharm Stat; 2018 Sep; 17(5):555-569. PubMed ID: 29956453
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A Bayesian prediction model between a biomarker and the clinical endpoint for dichotomous variables.
    Jiang Z; Song Y; Shou Q; Xia J; Wang W
    Trials; 2014 Dec; 15():500. PubMed ID: 25528466
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Bayesian adaptive trial design for a newly validated surrogate endpoint.
    Renfro LA; Carlin BP; Sargent DJ
    Biometrics; 2012 Mar; 68(1):258-67. PubMed ID: 21838811
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Assurance in vaccine efficacy clinical trial design based on immunological responses.
    Callegaro A; Zahaf T; Tibaldi F
    Biom J; 2021 Oct; 63(7):1434-1443. PubMed ID: 34254347
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Using short-term endpoints to improve interim decision making and trial duration in two-stage phase II trials with nested binary endpoints.
    Zocholl D; Kunz CU; Rauch G
    Stat Methods Med Res; 2023 Sep; 32(9):1749-1765. PubMed ID: 37489267
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Uncertainty in the Bayesian meta-analysis of normally distributed surrogate endpoints.
    Bujkiewicz S; Thompson JR; Spata E; Abrams KR
    Stat Methods Med Res; 2017 Oct; 26(5):2287-2318. PubMed ID: 26271918
    [TBL] [Abstract][Full Text] [Related]  

  • 9. An optimal Bayesian predictive probability design for phase II clinical trials with simple and complicated endpoints.
    Guo B; Liu S
    Biom J; 2020 Mar; 62(2):339-349. PubMed ID: 31402481
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Bayesian model selection techniques as decision support for shaping a statistical analysis plan of a clinical trial: an example from a vertigo phase III study with longitudinal count data as primary endpoint.
    Adrion C; Mansmann U
    BMC Med Res Methodol; 2012 Sep; 12():137. PubMed ID: 22962944
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Sample size reestimation and Bayesian predictive probability for single-arm clinical trials with a time-to-event endpoint using Weibull distribution with unknown shape parameter.
    Waleed M; He J; Phadnis MA
    J Biopharm Stat; 2024 Jul; 34(4):469-487. PubMed ID: 37545144
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Optimal decision-making in oncology development programs based on probability of success for phase III utilizing phase II/III data on response and overall survival.
    Götte H; Xiong J; Kirchner M; Demirtas H; Kieser M
    Pharm Stat; 2020 Nov; 19(6):861-881. PubMed ID: 32662598
    [TBL] [Abstract][Full Text] [Related]  

  • 13. An analytical approach to assess the predictive value of biomarkers in Phase II decision making.
    Nikolakopoulos S; van der Wal WM; Roes KC
    J Biopharm Stat; 2013; 23(5):1106-23. PubMed ID: 23957519
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Novel procedures for validating surrogate endpoints in clinical trials.
    Cleophas TJ; Zwinderman AH; Chaib AH
    Curr Clin Pharmacol; 2007 May; 2(2):123-8. PubMed ID: 18690859
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Nested combination tests with a time-to-event endpoint using a short-term endpoint for design adaptations.
    Jörgens S; Wassmer G; König F; Posch M
    Pharm Stat; 2019 May; 18(3):329-350. PubMed ID: 30652401
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Surrogate endpoints for overall survival in digestive oncology trials: which candidates? A questionnaires survey among clinicians and methodologists.
    Methy N; Bedenne L; Bonnetain F
    BMC Cancer; 2010 Jun; 10():277. PubMed ID: 20537166
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Bayesian predictive sample size selection design for single-arm exploratory clinical trials.
    Teramukai S; Daimon T; Zohar S
    Stat Med; 2012 Dec; 31(30):4243-54. PubMed ID: 22807115
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A maximum entropy approach for the evaluation of surrogate endpoints based on causal inference.
    Alonso A; Van der Elst W; Molenberghs G
    Stat Med; 2018 Dec; 37(29):4525-4538. PubMed ID: 30141219
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Introduction to Bayesian methods III: use and interpretation of Bayesian tools in design and analysis.
    Berry DA
    Clin Trials; 2005; 2(4):295-300; discussion 301-4, 364-78. PubMed ID: 16281428
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Evaluating futility of a binary clinical endpoint using early read-outs.
    Van Lancker K; Vandebosch A; Vansteelandt S; De Ridder F
    Stat Med; 2019 Dec; 38(28):5361-5375. PubMed ID: 31631357
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.