BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

186 related articles for article (PubMed ID: 31990083)

  • 1. Bayesian hierarchical meta-analytic methods for modeling surrogate relationships that vary across treatment classes using aggregate data.
    Papanikos T; Thompson JR; Abrams KR; Städler N; Ciani O; Taylor R; Bujkiewicz S
    Stat Med; 2020 Apr; 39(8):1103-1124. PubMed ID: 31990083
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Comparing Bayesian hierarchical meta-regression methods and evaluating the influence of priors for evaluations of surrogate endpoints on heterogeneous collections of clinical trials.
    Collier W; Haaland B; Inker LA; Heerspink HJL; Greene T
    BMC Med Res Methodol; 2024 Feb; 24(1):39. PubMed ID: 38365599
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Bivariate network meta-analysis for surrogate endpoint evaluation.
    Bujkiewicz S; Jackson D; Thompson JR; Turner RM; Städler N; Abrams KR; White IR
    Stat Med; 2019 Aug; 38(18):3322-3341. PubMed ID: 31131475
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Use of copula to model within-study association in bivariate meta-analysis of binomial data at the aggregate level: A Bayesian approach and application to surrogate endpoint evaluation.
    Papanikos T; Thompson JR; Abrams KR; Bujkiewicz S
    Stat Med; 2022 Nov; 41(25):4961-4981. PubMed ID: 35932152
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process.
    Bujkiewicz S; Thompson JR; Riley RD; Abrams KR
    Stat Med; 2016 Mar; 35(7):1063-89. PubMed ID: 26530518
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Bayesian adjusted R2 for the meta-analytic evaluation of surrogate time-to-event endpoints in clinical trials.
    Renfro LA; Shi Q; Sargent DJ; Carlin BP
    Stat Med; 2012 Apr; 31(8):743-61. PubMed ID: 22161275
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Comparative Study of Bayesian Information Borrowing Methods in Oncology Clinical Trials.
    Su L; Chen X; Zhang J; Yan F
    JCO Precis Oncol; 2022 Mar; 6():e2100394. PubMed ID: 35263169
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Bayesian meta-analytic approach for safety signal detection in randomized clinical trials.
    Odani M; Fukimbara S; Sato T
    Clin Trials; 2017 Apr; 14(2):192-200. PubMed ID: 28059578
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Bayesian cluster hierarchical model for subgroup borrowing in the design and analysis of basket trials with binary endpoints.
    Chen N; Lee JJ
    Stat Methods Med Res; 2020 Sep; 29(9):2717-2732. PubMed ID: 32178585
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Causal assessment of surrogacy in a meta-analysis of colorectal cancer trials.
    Li Y; Taylor JM; Elliott MR; Sargent DJ
    Biostatistics; 2011 Jul; 12(3):478-92. PubMed ID: 21252079
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Exploring the relationship between the causal-inference and meta-analytic paradigms for the evaluation of surrogate endpoints.
    Van der Elst W; Molenberghs G; Alonso A
    Stat Med; 2016 Apr; 35(8):1281-98. PubMed ID: 26612787
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Improving the Estimation of Subgroup Effects for Clinical Trial Participants with Multimorbidity by Incorporating Drug Class-Level Information in Bayesian Hierarchical Models: A Simulation Study.
    Hannigan LJ; Phillippo DM; Hanlon P; Moss L; Butterly EW; Hawkins N; Dias S; Welton NJ; McAllister DA
    Med Decis Making; 2022 Feb; 42(2):228-240. PubMed ID: 34407672
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. A reflection on the causal interpretation of individual-level surrogacy.
    Alonso A; Van Der Elst W; Molenberghs G; Florez AJ
    J Biopharm Stat; 2019; 29(3):529-540. PubMed ID: 30773114
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Flexible evaluation of surrogacy in platform studies.
    Sachs MC; Gabriel EE; Crippa A; Daniels MJ
    Biostatistics; 2023 Dec; 25(1):220-236. PubMed ID: 36610075
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Bayesian basket trial design using a calibrated Bayesian hierarchical model.
    Chu Y; Yuan Y
    Clin Trials; 2018 Apr; 15(2):149-158. PubMed ID: 29499621
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Time-to-event surrogate endpoint validation using mediation analysis and meta-analytic data.
    Le Coënt Q; Legrand C; Rondeau V
    Biostatistics; 2023 Dec; 25(1):98-116. PubMed ID: 36398615
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Bayesian hierarchical models for adaptive basket trial designs.
    Chen C; Hsiao CF
    Pharm Stat; 2023; 22(3):531-546. PubMed ID: 36625301
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Assessment of the information theory approach to evaluating time-to-event surrogate and true endpoints in a meta-analytic setting.
    Dimier N; Todd S
    Pharm Stat; 2021 Mar; 20(2):335-347. PubMed ID: 33145928
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.