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 *

126 related articles for article (PubMed ID: 38252040)

  • 41. Bayesian design of biosimilars clinical programs involving multiple therapeutic indications.
    Psioda MA; Hu K; Zhang Y; Pan J; Ibrahim JG
    Biometrics; 2020 Jun; 76(2):630-642. PubMed ID: 31631321
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Bayesian sample size determination in basket trials borrowing information between subsets.
    Zheng H; Grayling MJ; Mozgunov P; Jaki T; Wason JMS
    Biostatistics; 2023 Oct; 24(4):1000-1016. PubMed ID: 35993875
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Shotgun-2: A Bayesian phase I/II basket trial design to identify indication-specific optimal biological doses.
    Chen X; Zhang J; Jiang L; Yan F
    Stat Methods Med Res; 2023 Mar; 32(3):443-464. PubMed ID: 36217826
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Flexible Bayesian subgroup analysis in early and confirmatory trials.
    Bunn V; Liu R; Lin J; Lin J
    Contemp Clin Trials; 2020 Nov; 98():106149. PubMed ID: 32942055
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Bayesian Additive Regression Trees (BART) with covariate adjusted borrowing in subgroup analyses.
    Pan J; Bunn V; Hupf B; Lin J
    J Biopharm Stat; 2022 Jul; 32(4):613-626. PubMed ID: 35737650
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Safety and Efficacy of Imatinib for Hospitalized Adults with COVID-19: A structured summary of a study protocol for a randomised controlled trial.
    Emadi A; Chua JV; Talwani R; Bentzen SM; Baddley J
    Trials; 2020 Oct; 21(1):897. PubMed ID: 33115543
    [TBL] [Abstract][Full Text] [Related]  

  • 47. 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]  

  • 48. Bayesian enhancement two-stage design for single-arm phase II clinical trials with binary and time-to-event endpoints.
    Shi H; Yin G
    Biometrics; 2018 Sep; 74(3):1055-1064. PubMed ID: 29466612
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Bayesian modeling and simulation to inform rare disease drug development early decision-making: Application to Duchenne muscular dystrophy.
    Lennie JL; Mondick JT; Gastonguay MR
    PLoS One; 2022; 17(4):e0247286. PubMed ID: 35482633
    [TBL] [Abstract][Full Text] [Related]  

  • 50. The win ratio approach for composite endpoints: practical guidance based on previous experience.
    Redfors B; Gregson J; Crowley A; McAndrew T; Ben-Yehuda O; Stone GW; Pocock SJ
    Eur Heart J; 2020 Dec; 41(46):4391-4399. PubMed ID: 32901285
    [TBL] [Abstract][Full Text] [Related]  

  • 51. An extension of Bayesian predictive sample size selection designs for monitoring efficacy and safety.
    Teramukai S; Daimon T; Zohar S
    Stat Med; 2015 Sep; 34(22):3029-39. PubMed ID: 26038148
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Bayesian methods for setting sample sizes and choosing allocation ratios in phase II clinical trials with time-to-event endpoints.
    Cotterill A; Whitehead J
    Stat Med; 2015 May; 34(11):1889-903. PubMed ID: 25620687
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Accelerating clinical development of HIV vaccine strategies: methodological challenges and considerations in constructing an optimised multi-arm phase I/II trial design.
    Richert L; Doussau A; Lelièvre JD; Arnold V; Rieux V; Bouakane A; Lévy Y; Chêne G; Thiébaut R;
    Trials; 2014 Feb; 15():68. PubMed ID: 24571662
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Optimal sample size determination for single-arm trials in pediatric and rare populations with Bayesian borrowing.
    Ji Z; Lin J; Lin J
    J Biopharm Stat; 2022 Jul; 32(4):529-546. PubMed ID: 35604836
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Deep historical borrowing framework to prospectively and simultaneously synthesize control information in confirmatory clinical trials with multiple endpoints.
    Zhan T; Zhou Y; Geng Z; Gu Y; Kang J; Wang L; Huang X; Slate EH
    J Biopharm Stat; 2022 Jan; 32(1):90-106. PubMed ID: 34632951
    [TBL] [Abstract][Full Text] [Related]  

  • 56. A Bayesian phase I/II platform design for co-developing drug combination therapies for multiple indications.
    Mu R; Xu J; Tang RS; Kopetz S; Yuan Y
    Stat Med; 2022 Jan; 41(2):374-389. PubMed ID: 34730248
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Bayesian hierarchical modeling of patient subpopulations: efficient designs of Phase II oncology clinical trials.
    Berry SM; Broglio KR; Groshen S; Berry DA
    Clin Trials; 2013 Oct; 10(5):720-34. PubMed ID: 23983156
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Matching within a hybrid RCT/RWD: framework on associated causal estimands.
    Lin J; Yu G; Gamalo M
    J Biopharm Stat; 2023 Jul; 33(4):439-451. PubMed ID: 35929973
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Optimal planning of phase II/III programs for clinical trials with multiple endpoints.
    Kieser M; Kirchner M; Dölger E; Götte H
    Pharm Stat; 2018 Sep; 17(5):437-457. PubMed ID: 29700949
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Borrowing information across subgroups in phase II trials: is it useful?
    Freidlin B; Korn EL
    Clin Cancer Res; 2013 Mar; 19(6):1326-34. PubMed ID: 23303215
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.