BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

177 related articles for article (PubMed ID: 35561046)

  • 1. gBOIN-ET: The generalized Bayesian optimal interval design for optimal dose-finding accounting for ordinal graded efficacy and toxicity in early clinical trials.
    Takeda K; Morita S; Taguri M
    Biom J; 2022 Oct; 64(7):1178-1191. PubMed ID: 35561046
    [TBL] [Abstract][Full Text] [Related]  

  • 2. TITE-gBOIN-ET: Time-to-event generalized Bayesian optimal interval design to accelerate dose-finding accounting for ordinal graded efficacy and toxicity outcomes.
    Takeda K; Yamaguchi Y; Taguri M; Morita S
    Biom J; 2023 Oct; 65(7):e2200265. PubMed ID: 37309248
    [TBL] [Abstract][Full Text] [Related]  

  • 3. TITE-gBOIN: Time-to-event Bayesian optimal interval design to accelerate dose-finding accounting for toxicity grades.
    Takeda K; Xia Q; Liu S; Rong A
    Pharm Stat; 2022 Mar; 21(2):496-506. PubMed ID: 34862715
    [TBL] [Abstract][Full Text] [Related]  

  • 4. BOIN-ETC: A Bayesian optimal interval design considering efficacy and toxicity to identify the optimal dose combinations.
    Kakizume T; Takeda K; Taguri M; Morita S
    Stat Methods Med Res; 2024 Apr; 33(4):716-727. PubMed ID: 38444354
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A generalized Bayesian optimal interval design for dose optimization in immunotherapy.
    Xia Q; Takeda K; Yamaguchi Y; Zhang J
    Pharm Stat; 2024 Jan; ():. PubMed ID: 38295856
    [TBL] [Abstract][Full Text] [Related]  

  • 6. BOIN-ET: Bayesian optimal interval design for dose finding based on both efficacy and toxicity outcomes.
    Takeda K; Taguri M; Morita S
    Pharm Stat; 2018 Jul; 17(4):383-395. PubMed ID: 29700965
    [TBL] [Abstract][Full Text] [Related]  

  • 7. TITE-BOIN-ET: Time-to-event Bayesian optimal interval design to accelerate dose-finding based on both efficacy and toxicity outcomes.
    Takeda K; Morita S; Taguri M
    Pharm Stat; 2020 May; 19(3):335-349. PubMed ID: 31829517
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A Bayesian optimal interval design for dose optimization with a randomization scheme based on pharmacokinetics outcomes in oncology.
    Takeda K; Zhu J; Li R; Yamaguchi Y
    Pharm Stat; 2023; 22(6):1104-1115. PubMed ID: 37545018
    [TBL] [Abstract][Full Text] [Related]  

  • 9. An adaptive gBOIN design with shrinkage boundaries for phase I dose-finding trials.
    Mu R; Hu Z; Xu G; Pan H
    BMC Med Res Methodol; 2021 Dec; 21(1):278. PubMed ID: 34895153
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Comparison Between Simultaneous and Sequential Utilization of Safety and Efficacy for Optimal Dose Determination in Bayesian Model-Assisted Designs.
    Li R; Takeda K; Rong A
    Ther Innov Regul Sci; 2023 Jul; 57(4):728-736. PubMed ID: 37087525
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Incorporating historical information to improve dose optimization design with toxicity and efficacy endpoints: iBOIN-ET.
    Zhao Y; Liu R; Takeda K
    Pharm Stat; 2023; 22(3):440-460. PubMed ID: 36514849
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Optimal biological dose selection in dose-finding trials with model-assisted designs based on efficacy and toxicity: a simulation study.
    Yamaguchi Y; Takeda K; Yoshida S; Maruo K
    J Biopharm Stat; 2024 May; 34(3):379-393. PubMed ID: 37114985
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Improving early phase oncology clinical trial design: The case for finding the optimal biological dose.
    Phillips A; Mondal S
    Pharm Stat; 2023; 22(4):739-747. PubMed ID: 36669771
    [TBL] [Abstract][Full Text] [Related]  

  • 14. TEPI-2 and UBI: designs for optimal immuno-oncology and cell therapy dose finding with toxicity and efficacy.
    Li P; Liu R; Lin J; Ji Y
    J Biopharm Stat; 2020 Nov; 30(6):979-992. PubMed ID: 32951518
    [TBL] [Abstract][Full Text] [Related]  

  • 15. [Introduction of Oncology Dose-Finding Trial Designs].
    Takeda K
    Gan To Kagaku Ryoho; 2022 Apr; 49(4):365-370. PubMed ID: 35444116
    [TBL] [Abstract][Full Text] [Related]  

  • 16. STEIN: A simple toxicity and efficacy interval design for seamless phase I/II clinical trials.
    Lin R; Yin G
    Stat Med; 2017 Nov; 36(26):4106-4120. PubMed ID: 28786138
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A comparison of phase I dose-finding designs in clinical trials with monotonicity assumption violation.
    Abbas R; Rossoni C; Jaki T; Paoletti X; Mozgunov P
    Clin Trials; 2020 Oct; 17(5):522-534. PubMed ID: 32631095
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Adaptive design for identifying maximum tolerated dose early to accelerate dose-finding trial.
    Kojima M
    BMC Med Res Methodol; 2022 Apr; 22(1):97. PubMed ID: 35382745
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Implementing and assessing Bayesian response-adaptive randomisation for backfilling in dose-finding trials.
    Pin L; Villar SS; Dehbi HM
    Contemp Clin Trials; 2024 Jul; 142():107567. PubMed ID: 38729298
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An extended Bayesian semi-mechanistic dose-finding design for phase I oncology trials using pharmacokinetic and pharmacodynamic information.
    Yang C; Li Y
    Stat Med; 2024 Feb; 43(4):689-705. PubMed ID: 38110304
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.