Comb-BOIN12: A Utility-Based Bayesian Optimal Interval Design for Dose Optimization in Cancer Drug-Combination Trials

References

• Thomas M. Braun and Shufang Wang. A hierarchical bayesian design for phase i trials of novel combinations of cancer therapeutic agents. Biometrics, 66(3):805–812, 2010. DOI: 10.1111/j.1541-0420.2009.01363.x. URL https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1541-0420.2009.01363.x.
   Google Scholar
• Gordon Bril, Richard Dykstra, Carolyn Pillers, and Tim Robertson. Algorithm as 206: Isotonic regression in two independent variables. Journal of the Royal Statistical Society. Series C (Applied Statistics), 33(3):352–357, 1984. ISSN 00359254, 14679876. URL http://www.jstor.org/stable/2347723.
   Google Scholar
• Chunyan Cai, Ying Yuan, and Yuan Ji. A bayesian dose-finding design for oncology clinical trials of combinational biological agents. Journal of the Royal Statistical Society. Series C, Applied statistics, 63(1):159, 2014.
   Google Scholar
• Matthieu Clertant, Nolan A. Wages, and John O’Quigley. Semiparametric dose finding methods for partially ordered drug combinations. Statistica Sinica, 2022. DOI: 10.5705/ss.202020.0248.URL http://www.stat.sinica.edu.tw/statistica/.
   Google Scholar
• Tara C Gangadhar, Omid Hamid, David C Smith, Todd M Bauer, Jeffrey S Wasser, Jason J Luke, Ani S Balmanoukian, David R Kaufman, Yufan Zhao, Janet Maleski, Lance Leopold, and Thomas F Gajewski. Preliminary results from a phase i/ii study of epacadostat (incb024360) in combination with pembrolizumab in patients with selected advanced cancers. Journal for immunotherapy of cancer, 3(2):1–2, 2015.
   Google Scholar
• Beibei Guo and Yisheng Li. Bayesian dose-finding designs for combination of molecularly targeted agents assuming partial stochastic ordering. Statistics in medicine, 34(5):859–875, 2015.
   Google Scholar
• José L Jiménez, Sungjin Kim, and Mourad Tighiouart. A bayesian seamless phase i–ii trial design with two stages for cancer clinical trials with drug combinations. Biometrical Journal, 62(5):1300–1314, 2020.
   Google Scholar
• Akihito Kawazoe, Yasutoshi Kuboki, Eiji Shinozaki, Hiroki Hara, Tomohiro Nishina, Yoshito Komatsu, Satoshi Yuki, Masashi Wakabayashi, Shogo Nomura, Akihiro Sato, Takeshi Kuwata, Masahito Kawazu, Hiroyuki Mano, Yosuke Togashi, Hiroyoshi Nishikawa, and Takayuki Yoshino. Multicenter phase i/ii trial of napabucasin and pembrolizumab in patients with metastatic colorectal cancer (epoc1503/scoop trial). Clinical Cancer Research, 26(22):5887–5894, 2020.
   Google Scholar
• Ruitao Lin and Guosheng Yin. Bayesian optimal interval design for dose finding in drug-combination trials. Statistical Methods in Medical Research, 26(5):2155–2167, 2017. DOI: 10.1177/0962280215594494.URL . PMID: 26178591.
   Google Scholar
• Ruitao Lin and Ying Yuan. Time-to-event model-assisted designs for dose-finding trials with delayed toxicity. Biostatistics, 21(4):807–824, 2020.
   Google Scholar
• Ruitao Lin, Yanhong Zhou, Fangrong Yan, Daniel Li, and Ying Yuan. Boin12: Bayesian optimal interval phase i/ii trial design for utility-based dose finding in immunotherapy and targeted therapies. JCO precision oncology, 4:1393–1402, 2020.
   Google Scholar
• Xiaolei Lin and Yuan Ji. The joint i3 + 3 (ji3 + 3) design for phase i/ii adoptive cell therapy clinical trials. Journal of Biopharmaceutical Statistics, 30(6):993–1005, 2020.
   Google Scholar
• Rong Liu, Ying Yuan, Suman Sen, Xin Yang, Qi Jiang, Xiaoyun Li, Chengxing Lu, Mithat Gönen, Hong Tian, Heng Zhou, et al. Accuracy and safety of novel designs for phase i drug-combination oncology trials. Statistics in biopharmaceutical research, 14(3):270–282, 2022.
   Google Scholar
• Suyu Liu and Ying Yuan. Bayesian optimal interval designs for phase i clinical trials. Journal of the Royal Statistical Society: Series C (Applied Statistics), 64(3):507–523, 2015.
   Google Scholar
• Suyu Liu, Beibei Guo, and Ying Yuan. A bayesian phase i/ii trial design for immunotherapy. Journal of the American Statistical Association, 113(523):1016–1027, 2018.
   Google Scholar
• Tara C Mitchell, Omid Hamid, David C Smith, Todd M Bauer, Jeffrey S Wasser, Anthony J Olszanski, Jason J Luke, Ani S Balmanoukian, Emmett V Schmidt, Yufan Zhao, Xiaohua Gong, Janet Maleski, Lance Leopold, and Thomas Gajewski. Epacadostat plus pembrolizumab in patients with advanced solid tumors: phase i results from a multicenter, open-label phase i/ii trial (echo-202/keynote-037). Journal of Clinical Oncology, 36(32):3223, 2018.
   Google Scholar
• Reza Bayat Mokhtari, Tina S Homayouni, Narges Baluch, Evgeniya Morgatskaya, Sushil Kumar, Bikul Das, and Herman Yeger. Combination therapy in combating cancer. Oncotarget, 8(23): 38022, 2017.
   Google Scholar
• Haitao Pan, Ruitao Lin, Yanhong Zhou, and Ying Yuan. Keyboard design for phase i drug-combination trials. Contemporary Clinical Trials, 92:105972, 2020. ISSN 1551-7144. DOI: 10.1016/j.cct.2020.105972. URL https://www.sciencedirect.com/science/article/pii/S1551714420300501.
   Google Scholar
• Leslie E Papke and Jeffrey M Wooldridge. Econometric methods for fractional response variables with an application to 401 (k) plan participation rates. Journal of applied econometrics, 11(6): 619–632, 1996.
   Google Scholar
• Marie-Karelle Riviere, Ying Yuan, Frédéric Dubois, and Sarah Zohar. A bayesian dose-finding design for drug combination clinical trials based on the logistic model. Pharmaceutical Statistics, 13(4):247–257, 2014. DOI: 10.1002/pst.1621. URL https://onlinelibrary.wiley.com/doi/abs/10.1002/pst.1621.
   Google Scholar
• Caroline Robert, Jacob Schachter, Georgina V Long, Ana Arance, Jean Jacques Grob, Laurent Mortier, Adil Daud, Matteo S Carlino, Catriona McNeil, Michal Lotem, James Larkin, Paul Lorigan, Bart Neyns, Christian U Blank, Omid Hamid, Christine Mateus, Ronnie Shapira-Frommer, Michele Kosh, Honghong Zhou, Nageatte Ibrahim, Scot Ebbinghaus, and Antoni Ribas. Pembrolizumab versus ipilimumab in advanced melanoma. New England Journal of Medicine, 372(26):2521–2532, 2015.
   Google Scholar
• Fumiya Shimamura, Chikuma Hamada, Shigeyuki Matsui, and Akihiro Hirakawa. Two-stage approach based on zone and dose findings for two-agent combination phase i/ii trials. Journal of Biopharmaceutical Statistics, 28(6):1025–1037, 2018. DOI: 10.1080/10543406.2018.1434190.URL . PMID: 29420127.
   Google Scholar
• Zhichao Sun and Thomas M Braun. A two-dimensional biased coin design for dual-agent dose-finding trials. Clinical Trials, 12(6):596–607, 2015. DOI: 10.1177/1740774515592404.URL . PMID: 26163309.
   Google Scholar
• Matthew H Taylor, Chung-Han Lee, Vicky Makker, Drew Rasco, Corina E Dutcus, Jane Wu, Daniel E Stepan, Robert C Shumaker, and Robert J Motzer. Phase ib/ii trial of lenvatinib plus pembrolizumab in patients with advanced renal cell carcinoma, endometrial cancer, and other selected advanced solid tumors. Journal of Clinical Oncology, 38(11):1154, 2020.
   Google Scholar
• Peter F. Thall, Randall E. Millikan, Peter Mueller, and Sang-Joon Lee. Dose-finding with two agents in phase i oncology trials. Biometrics, 59(3):487–496, 2003. DOI: 10.1111/1541-0420.00058. URL https://onlinelibrary.wiley.com/doi/abs/10.1111/1541-0420.00058.
   Google Scholar
• Nolan A Wages and Mark R Conaway. Phase i/ii adaptive design for drug combination oncology trials. Statistics in medicine, 33(12):1990–2003, 2014.
   Google Scholar
• Nolan A. Wages, Mark R. Conaway, and John O’Quigley. Continual reassessment method for partial ordering. Biometrics, 67(4):1555–1563, 2011. DOI: 10.1111/j.1541-0420.2011.01560.x. URL https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1541-0420.2011.01560.x.
   Google Scholar
• Shinjo Yada and Chikuma Hamada. A bayesian hierarchal modeling approach to shortening phase i/ii trials of anticancer drug combinations. Pharmaceutical statistics, 17(6):750–760, 2018.
   Google Scholar
• Guosheng Yin and Ying Yuan. Bayesian dose finding in oncology for drug combinations by copula regression. Journal of the Royal Statistical Society: Series C (Applied Statistics), 58(2):211–224, 2009. DOI: 10.1111/j.1467-9876.2009.00649.x. URL https://rss.onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-9876.2009.00649.x.
   Google Scholar
• Ying Yuan and Guosheng Yin. Bayesian phase i/ii adaptively randomized oncology trials with combined drugs. The annals of applied statistics, 5(2A):924, 2011.
   Google Scholar
• Ying Yuan, Ruitao Lin, Daniel Li, Lei Nie, and Katherine E Warren. Time-to-event bayesian optimal interval design to accelerate phase i trialstite-boin to accelerate phase i trials. Clinical Cancer Research, 24(20):4921–4930, 2018.
   Google Scholar
• Z Yuan, R Chappell, and H Bailey. The continual reassessment method for multiple toxicity grades: a bayesian quasi-likelihood approach. Biometrics, 63(1):173–179, 2007.
   Google Scholar
• Yong Zang and J Jack Lee. A robust two-stage design identifying the optimal biological dose for phase i/ii clinical trials. Statistics in medicine, 36(1):27–42, 2017.
   Google Scholar
• Heng Zhou, J Jack Lee, and Ying Yuan. Bop2: Bayesian optimal design for phase ii clinical trials with simple and complex endpoints. Statistics in medicine, 36(21):3302–3314, 2017.
   Google Scholar
• Yanhong Zhou, J Jack Lee, and Ying Yuan. A utility-based bayesian optimal interval (u-boin) phase i/ii design to identify the optimal biological dose for targeted and immune therapies. Statistics in medicine, 38(28):S5299–S5316, 2019.
   Google Scholar
• Yanhong Zhou, Ruitao Lin, J Jack Lee, Daniel Li, Li Wang, Ruobing Li, and Ying Yuan. Tite-boin12: A bayesian phase i/ii trial design to find the optimal biological dose with late-onset toxicity and efficacy. Statistics in Medicine, 41(11):1918–1931, 2022.
   Google Scholar