Skip to main content

Advertisement

SpringerLink
Log in

Evolution of Phase II Oncology Trial Design: from Single Arm to Master Protocol

  • Review
  • Published:
Therapeutic Innovation & Regulatory Science Aims and scope Submit manuscript

Abstract

The recent development of novel anticancer treatments with diverse mechanisms of action has accelerated the detection of treatment candidates tremendously. The rapidly changing drug development landscapes and the high failure rates in Phase III trials both underscore the importance of more efficient and robust phase II designs. The goals of phase II oncology studies are to explore the preliminary efficacy and toxicity of the investigational product and to inform future drug development strategies such as go/no-go decisions for phase III development, or dose/indication selection. These complex purposes of phase II oncology designs call for efficient, flexible, and easy-to-implement clinical trial designs. Therefore, innovative adaptive study designs with the potential of improving the efficiency of the study, protecting patients, and improving the quality of information gained from trials have been commonly used in Phase II oncology studies. Although the value of adaptive clinical trial methods in early phase drug development is generally well accepted, there is no comprehensive review and guidance on adaptive design methods and their best practice for phase II oncology trials. In this paper, we review the recent development and evolution of phase II oncology design, including frequentist multistage design, Bayesian continuous monitoring, master protocol design, and innovative design methods for randomized phase II studies. The practical considerations and the implementation of these complex design methods are also discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1

Similar content being viewed by others

Data Availability

Not applicable.

References

  1. Renfro LA, An M-W, Mandrekar SJ. Precision oncology: a new era of cancer clinical trials. Cancer Lett. 2017;387:121–6.

    Article  CAS  PubMed  Google Scholar 

  2. Ivanova A, Paul B, Marchenko O, Song G, Patel N, Moschos SJ. Nine-year change in statistical design, profile, and success rates of phase II oncology trials. J Biopharm Stat. 2016;26(1):141–9.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Thezenas S, Duffour J, Culine S, Kramar A. Five-year change in statistical designs of phase II trials published in leading cancer journals. Eur J Cancer. 2004;40(8):1244–9.

    Article  CAS  PubMed  Google Scholar 

  4. FDA, Guidance Document: Adaptive designs for clinical trials of drugs and biologics, 2019.

  5. Simon R. Designs for efficient clinical trials. Oncology. 1989;3(7):43–9.

    CAS  PubMed  Google Scholar 

  6. Woodcock J, LaVange LM. Master protocols to study multiple therapies, multiple diseases, or both. N Engl J Med. 2017;377(1):62–70.

    Article  CAS  PubMed  Google Scholar 

  7. Berry SM, Carlin BP, Lee JJ, Muller P. Bayesian adaptive methods for clinical trials. Boca Raton: CRC Press; 2010.

    Book  Google Scholar 

  8. Simon R. Optimal two-stage designs for phase II clinical trials. Control Clin Trials. 1989;10(1):1–10.

    Article  CAS  PubMed  Google Scholar 

  9. Lin Y, Shih WJ. Adaptive two-stage designs for single-arm phase IIA cancer clinical trials. Biometrics. 2004;60(2):482–90.

    Article  PubMed  Google Scholar 

  10. Banerjee A, Tsiatis AA. Adaptive two-stage designs in phase II clinical trials. Stat Med. 2006;25(19):3382–95.

    Article  PubMed  Google Scholar 

  11. Englert S, Kieser M. Optimal adaptive two-stage designs for phase II cancer clinical trials. Biom J. 2013;55(6):955–68.

    Article  PubMed  Google Scholar 

  12. Shan G, Wilding GE, Hutson AD, Gerstenberger S. Optimal adaptive two-stage designs for early phase II clinical trials. Stat Med. 2016;35(8):1257–66.

    Article  PubMed  Google Scholar 

  13. Chi Y, Chen CM. Curtailed two-stage designs in phase II clinical trials. Stat Med. 2008;27(29):6175–89.

    Article  PubMed  Google Scholar 

  14. Law M, Grayling MJ, Mander AP. A stochastically curtailed single-arm phase II trial design for binary outcomes. J Biopharm Stat. 2022;32(5):671–91.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Ayanlowo A, Redden D. Stochastically curtailed phase II clinical trials. Stat Med. 2007;26(7):1462–72.

    Article  CAS  PubMed  Google Scholar 

  16. Kunz CU, Kieser M. Curtailment in single-arm two-stage phase II oncology trials. Biom J. 2012;54(4):445–56.

    Article  PubMed  Google Scholar 

  17. Bryant J, Day R. Incorporating toxicity considerations into the design of two-stage phase II clinical trials. Biometrics. 1995;51(4):1372–83.

    Article  CAS  PubMed  Google Scholar 

  18. Conaway MR, Petroni GR. Designs for phase II trials allowing for a trade-off between response and toxicity. Biometrics. 1996;52(4):1375–86.

    Article  CAS  PubMed  Google Scholar 

  19. Kocherginsky M, Cohen EE, Karrison T. Design of Phase II cancer trials for evaluation of cytostatic/cytotoxic agents. J Biopharm Stat. 2009;19(3):524–9.

    Article  PubMed  Google Scholar 

  20. Tan X, Takahara G, Tu D. Optimal Two-Stage Design for the Phase II Cancer Clinical Trials With Responses and Early Progression as Co-primary Endpoints. Stat Biopharm Res. 2010;2(3):348–54.

    Article  Google Scholar 

  21. Chang MN, Devidas M, Anderson J. One-and two-stage designs for phase II window studies. Stat Med. 2007;26(13):2604–14.

    Article  PubMed  Google Scholar 

  22. Lee JJ, Berry DA. Statistical innovations in cancer research. Holland‐Frei Cancer Medicine. 2016;1–18.

  23. Lin R, Lee JJ. Novel bayesian adaptive designs and their applications in cancer clinical trials, Computational and Methodological Statistics and Biostatistics. Cham: Springer; 2020. p. 395–426.

    Google Scholar 

  24. Thall PF, Simon R. Practical Bayesian guidelines for phase IIB clinical trials. Biometrics. 1994;50(2):337–49.

    Article  CAS  PubMed  Google Scholar 

  25. Lee JJ, Liu DD. A predictive probability design for phase II cancer clinical trials. Clin Trials. 2008;5(2):93–106.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Cai C, Liu S, Yuan Y. A Bayesian design for phase II clinical trials with delayed responses based on multiple imputation. Stat Med. 2014;33(23):4017–28.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Thall PF, Simon RM, Estey EH. Bayesian sequential monitoring designs for single-arm clinical trials with multiple outcomes. Stat Med. 1995;14(4):357–79.

    Article  CAS  PubMed  Google Scholar 

  28. Zhou H, Lee JJ, Yuan Y. BOP2: Bayesian optimal design for phase II clinical trials with simple and complex endpoints. Stat Med. 2017;36(21):3302–14.

    Article  PubMed  Google Scholar 

  29. Guo B, Liu S. An optimal Bayesian predictive probability design for phase II clinical trials with simple and complicated endpoints. Biom J. 2020;62(2):339–49.

    Article  PubMed  Google Scholar 

  30. Zhao Y, Yang B, Lee JJ, Wang L, Yuan Y. Bayesian Optimal Phase II Design for Randomized Clinical Trials. Stat Biopharm Res. 2022. https://doi.org/10.1080/19466315.2022.2050290.

    Article  Google Scholar 

  31. Saville BR, Connor JT, Ayers GD, Alvarez J. The utility of Bayesian predictive probabilities for interim monitoring of clinical trials. Clin Trials. 2014;11(4):485–93.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Emerson SS, Kittelson JM, Gillen DL. On the use of stochastic curtailment in group sequential clinical trials. 2005.

  33. Yin G, Chen N, Jack Lee J. Phase II trial design with Bayesian adaptive randomization and predictive probability. J Royal Stat Soc: Series C. 2012;61(2):219–35.

    Google Scholar 

  34. FDA, Master Protocols: Efficient Clinical Trial Design Strategies to Expedite Development of Oncology Drugs and Biologics Guidance for Industry: Guidance for Industry, 2022.

  35. Berry SM, Broglio KR, Groshen S, Berry DA. Bayesian hierarchical modeling of patient subpopulations: efficient designs of phase II oncology clinical trials. Clin Trials. 2013;10(5):720–34.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Cunanan KM, Iasonos A, Shen R, Hyman DM, Riely GJ, Gönen M, Begg CB. Specifying the true-and false-positive rates in basket trials. JCO Precision Oncol. 2017. https://doi.org/10.1200/PO.17.00181.

    Article  Google Scholar 

  37. Cunanan KM, Iasonos A, Shen R, Gönen M. Variance prior specification for a basket trial design using Bayesian hierarchical modeling. Clin Trials. 2019;16(2):142–53.

    Article  PubMed  Google Scholar 

  38. Neuenschwander B, Wandel S, Roychoudhury S, Bailey S. Robust exchangeability designs for early phase clinical trials with multiple strata. Pharm Stat. 2016;15(2):123–34.

    Article  PubMed  Google Scholar 

  39. Chu Y, Yuan Y. A Bayesian basket trial design using a calibrated Bayesian hierarchical model. Clin Trials. 2018;15(2):149–58.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Chu Y, Yuan Y. BLAST: Bayesian latent subgroup design for basket trials accounting for patient heterogeneity. J Roy Stat Soc: Ser C (Appl Stat). 2018;67(3):723–40.

    Google Scholar 

  41. Psioda MA, Xu J, Jiang Q, Ke C, Yang Z, Ibrahim JG. Bayesian adaptive basket trial design using model averaging. Biostatistics. 2021;22(1):19–34.

    Article  PubMed  Google Scholar 

  42. Kang D, Coffey CS, Smith BJ, Yuan Y, Shi Q, Yin J. Hierarchical Bayesian clustering design of multiple biomarker subgroups (HCOMBS). Stat Med. 2021;40(12):2893–921.

    Article  PubMed  Google Scholar 

  43. Lyu J, Zhou T, Yuan S, Guo W, Ji Y. MUCE: Bayesian hierarchical modeling for the design and analysis of phase 1b multiple expansion cohort trials. arXiv preprint arXiv:200607785. 2020. https://doi.org/10.48550/arXiv.2006.07785.

    Article  Google Scholar 

  44. Li M, Liu R, Lin J, Bunn V, Zhao H. Bayesian semi-parametric design (BSD) for adaptive dose-finding with multiple strata. J Biopharm Stat. 2020;30(5):806–20.

    Article  PubMed  Google Scholar 

  45. Zhang L, Rosenberger WF. Response-adaptive randomization for survival trials: the parametric approach. J Roy Stat Soc: Ser C (Appl Stat). 2007;56(2):153–65.

    Google Scholar 

  46. Huang X, Ning J, Li Y, Estey E, Issa JP, Berry DA. Using short-term response information to facilitate adaptive randomization for survival clinical trials. Stat Med. 2009;28(12):1680–9.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Nowacki AS, Zhao W, Palesch YY. A surrogate-primary replacement algorithm for response-adaptive randomization in stroke clinical trials. Stat Methods Med Res. 2017;26(3):1078–92.

    Article  PubMed  Google Scholar 

  48. Lin J, Lin LA, Bunn V, Liu R. Adaptive randomization for master protocols in precision medicine Contemporary Biostatistics with Biopharmaceutical Applications. Cham: Springer; 2019. p. 251–70.

    Book  Google Scholar 

  49. Gu X, Chen N, Wei C, Liu S, Papadimitrakopoulou VA, Herbst RS, Lee JJ. Bayesian two-stage biomarker-based adaptive design for targeted therapy development. Stat Biosci. 2016;8(1):99–128.

    Article  PubMed  Google Scholar 

  50. Liu S, Lee JJ. An overview of the design and conduct of the BATTLE trials. Chin Clin Oncol. 2015;4(3):33–33.

    PubMed  Google Scholar 

  51. Barker A, Sigman C, Kelloff G, Hylton N, Berry D, Esserman L. I-SPY 2: an adaptive breast cancer trial design in the setting of neoadjuvant chemotherapy. Clin Pharmacol Ther. 2009;86(1):97–100.

    Article  CAS  PubMed  Google Scholar 

  52. Alexander BM, Ba S, Berger MS, Berry DA, Cavenee WK, Chang SM, Cloughesy TF, Jiang T, Khasraw M, Li W. Adaptive global innovative learning environment for glioblastoma: GBM AGILE. Clin Cancer Res. 2018;24(4):737–43.

    Article  PubMed  Google Scholar 

  53. Hyman DM, Blay J-Y, Chau I, Raje NS, Fernandez MEE, Wolf J, Sirzen F, Veronese ML, Mitchell L, Puzanov I, Baselga J. VE-BASKET, a first-in-kind, phase II, histology-independent “basket” study of vemurafenib (VEM) in nonmelanoma solid tumors harboring BRAF V600 mutations (V600m). J Clin Oncol. 2014;32:2533–2533.

    Article  Google Scholar 

  54. Drilon A, Laetsch TW, Kummar S, DuBois SG, Lassen UN, Demetri GD, Nathenson M, Doebele RC, Farago AF, Pappo AS. Efficacy of larotrectinib in TRK fusion–positive cancers in adults and children. N Engl J Med. 2018;378(8):731–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Stallard N, Todd S, Parashar D, Kimani PK, Renfro LA. On the need to adjust for multiplicity in confirmatory clinical trials with master protocols. Ann Oncol. 2019;30(4):506–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Dmitrienko A, D’Agostino RB Sr, Huque MF. Key multiplicity issues in clinical drug development. Stat Med. 2013;32(7):1079–111.

    Article  PubMed  Google Scholar 

  57. Dmitrienko A, D’Agostino R Sr. Traditional multiplicity adjustment methods in clinical trials. Stat Med. 2013;32(29):5172–218.

    Article  PubMed  Google Scholar 

  58. Howard DR, Brown JM, Todd S, Gregory WM. Recommendations on multiple testing adjustment in multi-arm trials with a shared control group. Stat Methods Med Res. 2018;27(5):1513–30.

    Article  PubMed  Google Scholar 

  59. FDA, Clinical Trial Endpoints for the Approval of Cancer Drugs and Biologics: Guidance for Industry, 2018.

  60. Rubinstein L. Phase II design: history and evolution. Chin Clin Oncol. 2014;3(4):48.

    PubMed  Google Scholar 

  61. Sargent DJ, Taylor JM. Current issues in oncology drug development, with a focus on phase II trials. J Biopharm Stat. 2009;19(3):556–62.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Booth C, Calvert A, Giaccone G, Lobbezoo M, Eisenhauer E, Seymour L. On behalf of the task force on methodology for the development of innovative cancer therapies. Design and conduct of Phase II studies of targeted anticancer therapy: Recommendations from the task force on methodology for the development of innovative cancer therapies (MDICT). European J Cancer. 2008;44:25–9.

    Article  CAS  Google Scholar 

  63. Rubinstein LV, Korn EL, Freidlin B, Hunsberger S, Ivy SP, Smith MA. Design issues of randomized phase II trials and a proposal for phase II screening trials. J Clin Oncol. 2005;23(28):7199–206.

    Article  PubMed  Google Scholar 

  64. Ratain MJ, Sargent DJ. Optimising the design of phase II oncology trials: the importance of randomisation. Eur J Cancer. 2009;45(2):275–80.

    Article  PubMed  Google Scholar 

  65. Bretz F, Schmidli H, König F, Racine A, Maurer W. Confirmatory seamless phase II/III clinical trials with hypotheses selection at interim: general concepts. Biometrical J: J Math Methods Biosci. 2006;48(4):623–34.

    Article  Google Scholar 

  66. Schmidli H, Bretz F, Racine A, Maurer W. Confirmatory seamless phase II/III clinical trials with hypotheses selection at interim: applications and practical considerations. Biom J. 2006;48(4):635–43.

    Article  PubMed  Google Scholar 

  67. Jennison C, Turnbull BW. Adaptive seamless designs: selection and prospective testing of hypotheses. J Biopharm Stat. 2007;17(6):1135–61.

    Article  PubMed  Google Scholar 

  68. Li Q, Lin J, Lin Y. Adaptive design implementation in confirmatory trials: methods, practical considerations and case studies. Contemp Clin Trials. 2020;98: 106096.

    Article  PubMed  Google Scholar 

  69. Chen C, Anderson K, Mehrotra DV, Rubin EH, Tse A. A 2-in-1 adaptive phase 2/3 design for expedited oncology drug development. Contemp Clin Trials. 2018;64:238–42.

    Article  PubMed  Google Scholar 

  70. Hyman DM, Puzanov I, Subbiah V, Faris JE, Chau I, Blay J-Y, Wolf J, Raje NS, Diamond EL, Hollebecque A. Vemurafenib in multiple nonmelanoma cancers with BRAF V600 mutations. N Engl J Med. 2015;373(8):726–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. A Friends of Cancer Research Whilte Paper: Accelerating Investigation of New Therapies in Earlier Metastatic Treatment Settings, Friends of Cancer Research Annual Meeting, 2022.

  72. Thompson WR. On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika. 1933;25(3–4):285–94.

    Article  Google Scholar 

  73. Thall PF, Wathen JK. Practical Bayesian adaptive randomisation in clinical trials. Eur J Cancer. 2007;43(5):859–66.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Connor JT, Elm JJ, Broglio KR, Esett A-I. Investigators, Bayesian adaptive trials offer advantages in comparative effectiveness trials: an example in status epilepticus. J Clin Epidemiol. 2013;66(8):S130–7.

    Article  PubMed  PubMed Central  Google Scholar 

  75. Wason JM, Trippa L. A comparison of Bayesian adaptive randomization and multi-stage designs for multi-arm clinical trials. Stat Med. 2014;33(13):2206–21.

    Article  PubMed  Google Scholar 

  76. Picozzi VJ, Duliege A-M, Maitra A, Hidalgo M, Hendifar AE, Beatty GL, Doss SD, Deck R, Matrisian LM, Fleshman J, Simeone DM. Abstract PO-050: Precision Promise (PrP): An adaptive, multi-arm registration trial in metastatic pancreatic ductal adenocarcinoma (PDAC). Cancer Res. 2021;81(22_Supplement):PO-50.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. 95 Hayden Ave, Lexington, MA, 02421, USA

    Ziji Yu

  2. Takeda Pharmaceuticals, Lexington, USA

    Ziji Yu, Liwen Wu, Veronica Bunn & Jianchang Lin

  3. Morphosis AG, Boston, USA

    Qing Li

Authors
  1. Ziji Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Liwen Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Veronica Bunn
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Qing Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jianchang Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors have contributed to this review article. All authors read and approved the final manuscript for submission for publication.

Corresponding author

Correspondence to Ziji Yu.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yu, Z., Wu, L., Bunn, V. et al. Evolution of Phase II Oncology Trial Design: from Single Arm to Master Protocol. Ther Innov Regul Sci 57, 823–838 (2023). https://doi.org/10.1007/s43441-023-00500-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s43441-023-00500-w

Keywords

Search

Navigation