Bayesian optimal interval design for phase I oncology clinical trials

被引:3
|
作者
Fellman, Bryan M. [1 ]
Yuan, Ying [1 ]
机构
[1] Univ Texas Houston, MD Anderson Canc Ctr, Houston, TX 77030 USA
来源
STATA JOURNAL | 2015年 / 15卷 / 01期
关键词
st0372; optinterval; Bayesian optimal interval; phase I clinical trial design; maximum tolerated dose; operating characteristic;
D O I
10.1177/1536867X1501500107
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
The Bayesian optimal interval (BOIN) design is a novel phase I trial design for finding the maximum tolerated dose (MTD). With the BOIN design, phase I trials are conducted as a sequence of decision-making steps for assigning an appropriate dose for each enrolled patient. The design optimizes the assignment of doses to patients by minimizing incorrect decisions of dose escalation or deescalation; that is, it decreases the chance of erroneously escalating or de-escalating the dose when the current dose is higher or lower than the MTD. This feature of the BOIN design strongly ensures adherence to ethical standards. The most prominent advantage of the BOIN design is that it simultaneously achieves design simplicity and superior performance in comparison with similar methods. The BOIN design can be implemented in a simple way that is similar to the 3 3 design, but it yields substantially better operating characteristics. Compared with the well-known continual reassessment method, the BOIN design yields average performance when selecting the MTD, but it has a substantially lower risk of assigning patients to subtherapeutic or overly toxic doses. In this article, we present a command (optinterval) for implementing the BOIN design in a phase I clinical trial setting.
引用
收藏
页码:110 / 120
页数:11
相关论文
共 50 条
  • [1] Bayesian Optimal Interval Design: A Simple and Well-Performing Design for Phase I Oncology Trials
    Yuan, Ying
    Hess, Kenneth R.
    Hilsenbeck, Susan G.
    Gilbert, Mark R.
    CLINICAL CANCER RESEARCH, 2016, 22 (17) : 4291 - 4301
  • [2] Bayesian optimal interval designs for phase I clinical trials
    Liu, Suyu
    Yuan, Ying
    JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 2015, 64 (03) : 507 - 523
  • [3] Early completion of phase I cancer clinical trials with Bayesian optimal interval design
    Kojima, Masahiro
    STATISTICS IN MEDICINE, 2021, 40 (14) : 3215 - 3226
  • [4] Time-to-event Bayesian optimal interval design to accelerate phase I pediatric oncology trials
    Yuan, Ying
    Lin, Ruitao
    Li, Daniel
    Nie, Lei
    Warren, Katherine
    CANCER RESEARCH, 2020, 80 (14) : 52 - 52
  • [5] Time-to-Event Bayesian Optimal Interval Design to Accelerate Phase I Trials
    Yuan, Ying
    Lin, Ruitao
    Li, Daniel
    Nie, Lei
    Warren, Katherine E.
    CLINICAL CANCER RESEARCH, 2018, 24 (20) : 4921 - 4930
  • [6] Bayesian hybrid dose-finding design in phase I oncology clinical trials
    Yuan, Ying
    Yin, Guosheng
    STATISTICS IN MEDICINE, 2011, 30 (17) : 2098 - 2108
  • [7] Keyboard: A Novel Bayesian Toxicity Probability Interval Design for Phase I Clinical Trials
    Yan, Fangrong
    Mandrekar, Sumithra J.
    Yuan, Ying
    CLINICAL CANCER RESEARCH, 2017, 23 (15) : 3994 - 4003
  • [8] Bayesian optimal designs for phase I clinical trials
    Haines, LM
    Perevozskaya, I
    Rosenberger, WF
    BIOMETRICS, 2003, 59 (03) : 591 - 600
  • [9] A Comparative Study of Bayesian Optimal Interval (BOIN) Design With Interval 3+3 (i3+3) Design for Phase I Oncology Dose-Finding Trials
    Zhou, Yanhong
    Li, Ruobing
    Yan, Fangrong
    Lee, J. Jack
    Yuan, Ying
    STATISTICS IN BIOPHARMACEUTICAL RESEARCH, 2021, 13 (02): : 147 - 155
  • [10] Design of phase I clinical trials in radiation oncology
    Belderbos, JSA
    RADIOTHERAPY AND ONCOLOGY, 2004, 73 : S136 - S136