Modified isotonic regression based phase I/II clinical trial design identifying optimal biological dose

被引:5
作者
Qiu, Yingjie [1 ]
Zhao, Yi [1 ]
Liu, Hao [2 ]
Cao, Sha [1 ,3 ]
Zhang, Chi [3 ,4 ]
Zang, Yong [1 ,3 ,5 ]
机构
[1] Indiana Univ, Dept Biostat & Hlth Data Sci, Indianapolis, IN USA
[2] Rutgers State Univ, Canc Inst New Jersey, Dept Biostat & Epidemiol, Newark, NJ USA
[3] Indiana Univ, Ctr Computat Biol & Bioinformat, Indianapolis, IN USA
[4] Indiana Univ, Dept Med & Mol Genet, Indianapolis, IN USA
[5] Indiana Univ, Dept Biostat & Hlth Data Sci, 410 W 10th St, Indianapolis, IN 46202 USA
关键词
Phase I; II clinical trials; Molecularly targeted agents; Immunotherapy; Delayed outcome; Isotonic regression; FINDING DESIGN; CANCER-IMMUNOTHERAPY; I TRIALS; TOXICITY; EFFICACY; OUTCOMES; AGENTS;
D O I
10.1016/j.cct.2023.107139
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Conventional phase I/II clinical trial designs often use complicated parametric models to characterize the dose -response relationships and conduct the trials. However, the parametric models are hard to justify in practice, and the misspecification of parametric models can lead to substantially undesirable performances in phase I/II trials. Moreover, it is difficult for the physicians conducting phase I/II trials to clinically interpret the parameters of these complicated models, and such significant learning costs impede the translation of novel statistical designs into practical trial implementation. To solve these issues, we propose a transparent and efficient phase I/II clinical trial design, referred to as the modified isotonic regression-based design (mISO), to identify the optimal biological doses for molecularly targeted agents and immunotherapy. The mISO design makes no parametric model assumptions on the dose-response relationship and yields desirable performances under any clinically meaningful dose-response curves. The concise, clinically interpretable dose-response models and dose-finding algorithm make the proposed designs highly translational from the statistical community to the clinical com-munity. We further extend the mISO design and develop the mISO-B design to handle the delayed outcomes. Our comprehensive simulation studies show that the mISO and mISO-B designs are highly efficient in optimal bio-logical dose selection and patients allocation and outperform many existing phase I/II clinical trial designs. We also provide a trial example to illustrate the practical implementation of the proposed designs. The software for simulation and trial implementation are available for free download.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] APhase I/II Trial of MEC (Mitoxantrone, Etoposide, Cytarabine) in Combination with Ixazomib for Relapsed Refractory Acute Myeloid Leukemia
    Advani, Anjali S.
    Cooper, Brenda
    Visconte, Valeria
    Elson, Paul
    Chan, Ricky
    Carew, Jennifer
    Wei, Wei
    Mukherjee, Sudipto
    Gerds, Aaron
    Carraway, Hetty
    Nazha, Aziz
    Hamilton, Betty
    Sobecks, Ronald
    Caimi, Paolo
    Tomlinson, Benjamin
    Malek, Ehsan
    Little, Jane
    Miron, Alexander
    Pink, John
    Maciejewski, Jaroslaw
    Unger, Allison
    Kalaycio, Matt
    de Lima, Marcos
    Sekeres, Mikkael A.
    [J]. CLINICAL CANCER RESEARCH, 2019, 25 (14) : 4231 - 4237
  • [2] Nivolumab dose selection: challenges, opportunities, and lessons learned for cancer immunotherapy
    Agrawal, Shruti
    Feng, Yan
    Roy, Amit
    Kollia, Georgia
    Lestini, Brian
    [J]. JOURNAL FOR IMMUNOTHERAPY OF CANCER, 2016, 4
  • [3] Barlow R., 1972, STAT INFERENCE ORDER
  • [4] Seamless phase I/II design for novel anticancer agents with competing disease progression
    Biard, Lucie
    Lee, Shing M.
    Cheng, Bin
    [J]. STATISTICS IN MEDICINE, 2021, 40 (21) : 4568 - 4581
  • [5] The bivariate continual reassessment method: extending the CRM to phase I trials of two competing outcomes
    Braun, TA
    [J]. CONTROLLED CLINICAL TRIALS, 2002, 23 (03): : 240 - 256
  • [6] Sequential designs for phase I clinical trials with late-onset toxicities
    Cheung, YK
    Chappell, R
    [J]. BIOMETRICS, 2000, 56 (04) : 1177 - 1182
  • [7] Cancer Immunotherapy
    Couzin-Frankel, Jennifer
    [J]. SCIENCE, 2013, 342 (6165) : 1432 - 1433
  • [8] A utility-based Bayesian phase I-II design for immunotherapy trials with progression-free survival end point
    Guo, Beibei
    Park, Yeonhee
    Liu, Suyu
    [J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 2019, 68 (02) : 411 - 425
  • [9] Bayesian Phase I/II Biomarker-Based Dose Finding for Precision Medicine With Molecularly Targeted Agents
    Guo, Beibei
    Yuan, Ying
    [J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2017, 112 (518) : 508 - 520
  • [10] Autophagy Inhibition to Augment mTOR Inhibition: a Phase I/II Trial of Everolimus and Hydroxychloroquine in Patients with Previously Treated Renal Cell Carcinoma
    Haas, Naomi B.
    Appleman, Leonard J.
    Stein, Mark
    Redlinger, Maryann
    Wilks, Melissa
    Xu, Xiaowei
    Onorati, Angelique
    Kalavacharla, Anusha
    Kim, Taehyong
    Zhen, Chao Jie
    Kadri, Sabah
    Segal, Jeremy P.
    Gimotty, Phyllis A.
    Davis, Lisa E.
    Amaravadi, Ravi K.
    [J]. CLINICAL CANCER RESEARCH, 2019, 25 (07) : 2080 - 2087