Skip to main content
SpringerLink
Log in

Platform Trials

  • Chapter
  • First Online:
Bayesian Adaptive Design for Immunotherapy and Targeted Therapy

  • 350 Accesses

Abstract

Traditional phase II clinical trial designs were developed mainly for evaluating candidate treatments in a one-treatment-at-a-time manner. With tremendous advances in biomedical research, a number of candidate drugs are produced and discovered at an unprecedented speed. This makes the traditional one-treatment-at-a-time phase II trial paradigm cumbersome and grossly inefficient. Platform trials, also known as multi-arm multi-stage trials, provide an efficient way to screen a large number of candidate drugs and quickly identify promising ones for the next phase of development. In this chapter, several platform trial designs are introduced to illustrate this approach. These designs are highly flexible and adaptive, allowing dropping inefficient treatments and adding new candidate treatments during the course of the trial.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    By taking this “censoring” strategy, we implicitly assume that patients behave similarly for “old” and new SOCs. If investigators show concern about this assumption, the information from the “old” SOC may not be used.

  2. 2.

    Technically similar to historical or external control data if we only focus on concept of the nonexchangeability.

References

  • Angus, D. C., Alexander, B. M., Berry, S., Buxton, M., Lewis, R., Paoloni, M., & Woodcock, J. (2019). Adaptive platform trials: Definition, design, conduct and reporting considerations. Nature Reviews Drug Discovery, 18(10), 797–807.

    Google Scholar 

  • Antonijevic, Z., & Beckman, R. A. (Eds.). (2018). Platform trial designs in drug development: Umbrella trials and basket trials. CRC Press.

    Google Scholar 

  • Arabi, Y. M., Gordon, A. C., Derde, L. P., Nichol, A. D., Murthy, S., Beidh, F. A., & Webb, S. A. (2021). Lopinavir-ritonavir and hydroxychloroquine for critically ill patients with COVID-19: REMAP-CAP randomized controlled trial. Intensive Care Medicine, 47(8), 867–886.

    Google Scholar 

  • Bateman, R. J., Benzinger, T. L., Berry, S., Clifford, D. B., Duggan, C., Fagan, A. M., & Xiong, C. (2017). The DIAN-TU Next Generation Alzheimer’s prevention trial: Adaptive design and disease progression model. Alzheimer’s & Dementia, 13(1), 8–19.

    Google Scholar 

  • Bennett, M., & Mander, A. P. (2020). Designs for adding a treatment arm to an ongoing clinical trial. Trials, 21(1), 1–12.

    Article  Google Scholar 

  • Burnett, T., Mozgunov, P., Pallmann, P., Villar, S. S., Wheeler, G. M., & Jaki, T. (2020). Adding flexibility to clinical trial designs: An example-based guide to the practical use of adaptive designs. BMC Medicine, 18(1), 1–21.

    Article  Google Scholar 

  • Butler, C. C., Coenen, S., Saville, B. R., Cook, J., van der Velden, A., Homes, J., & Verheij, T. (2018). A trial like ALIC4E: Why design a platform, response-adaptive, open, randomised controlled trial of antivirals for influenza-like illness? ERJ Open Research, 4(2).

    Google Scholar 

  • Choodari-Oskooei, B., Bratton, D. J., Gannon, M. R., Meade, A. M., Sydes, M. R., & Parmar, M. K. (2020). Adding new experimental arms to randomised clinical trials: Impact on error rates. Clinical Trials, 17(3), 273–284.

    Article  Google Scholar 

  • Dunnett, C. W. (1955). A multiple comparison procedure for comparing several treatments with a control. Journal of the American Statistical Association, 50(272), 1096–1121.

    Article  MATH  Google Scholar 

  • Eisele, J. R. (1994). The doubly adaptive biased coin design for sequential clinical trials. Journal of Statistical Planning and Inference, 38(2), 249–261.

    Article  MathSciNet  MATH  Google Scholar 

  • Gordon Lan, K. K., & DeMets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika, 70(3), 659–663.

    Google Scholar 

  • Hague, D., Townsend, S., Masters, L., Rauchenberger, M., Van Looy, N., Diaz-Montana, C., & Sydes, M. R. (2019). Changing platforms without stopping the train: Experiences of data management and data management systems when adapting platform protocols by adding and closing comparisons. Trials, 20(1), 1–16.

    Google Scholar 

  • Hayward, G., Butler, C. C., Yu, L. M., Saville, B. R., Berry, N., Dorward, J., & Hobbs, F. R. (2021). Platform Randomised trial of INterventions against COVID-19 in older peoPLE (PRINCIPLE): Protocol for a randomised, controlled, open-label, adaptive platform, trial of community treatment of COVID-19 syndromic illness in people at higher risk. BMJ Open, 11(6), e046799.

    Google Scholar 

  • Hobbs, B. P., Carlin, B. P., Mandrekar, S. J., & Sargent, D. J. (2011). Hierarchical commensurate and power prior models for adaptive incorporation of historical information in clinical trials. Biometrics, 67(3), 1047–1056.

    Article  MathSciNet  MATH  Google Scholar 

  • Hobbs, B. P., Chen, N., & Lee, J. J. (2018). Controlled multi-arm platform design using predictive probability. Statistical Methods in Medical Research, 27(1), 65–78.

    Article  MathSciNet  Google Scholar 

  • Gattinoni, L., Klebanoff, C. A., Palmer, D. C., Wrzesinski, C., Kerstann, K., Yu, Z., & Restifo, N. P. (2005). Acquisition of full effector function in vitro paradoxically impairs the in vivo antitumor efficacy of adoptively transferred CD8+ T cells. The Journal of clinical investigation, 115(6), 1616–1626.

    Google Scholar 

  • Johnson, L. A., Morgan, R. A., Dudley, M. E., Cassard, L., Yang, J. C., Hughes, M. S., & Rosenberg, S. A. (2009). Gene therapy with human and mouse T-cell receptors mediates cancer regression and targets normal tissues expressing cognate antigen. Blood, The Journal of the American Society of Hematology, 114(3), 535–546.

    Google Scholar 

  • Lee, K. M., & Wason, J. (2020). Including non-concurrent control patients in the analysis of platform trials: Is it worth it? BMC Medical Research Methodology, 20, 1–12.

    Google Scholar 

  • Magaret, A., Angus, D. C., Adhikari, N. K., Banura, P., Kissoon, N., Lawler, J. V., & Jacob, S. T. (2016). Design of a multi-arm randomized clinical trial with no control arm. Contemporary Clinical Trials, 46, 12–17.

    Article  Google Scholar 

  • Magirr, D., Jaki, T., & Whitehead, J. (2012). A generalized Dunnett test for multi-arm multi-stage clinical studies with treatment selection. Biometrika, 99(2), 494–501.

    Article  MathSciNet  MATH  Google Scholar 

  • Meyer, E. L., Mesenbrink, P., Dunger-Baldauf, C., Glimm, E., Li, Y., & König, F. (2021). Decision rules for identifying combination therapies in open-entry, randomized controlled platform trials. arXiv:2103.09547.

  • Mosse, Y. (2018). Next generation personalized neuroblastoma therapy (NEPENTHE).

    Google Scholar 

  • Mu, R., Pan, H., & Xu, G. (2021). A Bayesian adaptive phase I/II platform trial design for pediatric immunotherapy trials. Statistics in Medicine, 40(2), 382–402.

    Article  MathSciNet  Google Scholar 

  • Neuenschwander, B., Branson, M., & Spiegelhalter, D. J. (2009). A note on the power prior. Statistics in Medicine, 28(28), 3562–3566.

    Article  MathSciNet  Google Scholar 

  • Normington, J., Zhu, J., Mattiello, F., Sarkar, S., & Carlin, B. (2020). An efficient Bayesian platform trial design for borrowing adaptively from historical control data in lymphoma. Contemporary Clinical Trials, 89, 105890.

    Article  Google Scholar 

  • Pallmann, P., Bedding, A. W., Choodari-Oskooei, B., Dimairo, M., Flight, L., Hampson, L. V., ... & Jaki, T. (2018). Adaptive designs in clinical trials: Why use them, and how to run and report them. BMC medicine, 16(1), 1–15.

    Google Scholar 

  • Pan, H., Yuan, X., & Ye, J. (2022). An optimal two-period multiarm platform design with new experimental arms added during the trial. In press.

    Google Scholar 

  • Park, J. J., Siden, E., Zoratti, M. J., Dron, L., Harari, O., Singer, J., ... & Mills, E. J. (2019). Systematic review of basket trials, umbrella trials, and platform trials: A landscape analysis of master protocols. Trials, 20, 1–10.

    Google Scholar 

  • Park, J. J., Harari, O., Dron, L., Lester, R. T., Thorlund, K., & Mills, E. J. (2020). An overview of platform trials with a checklist for clinical readers. Journal of Clinical Epidemiology, 125, 1–8.

    Article  Google Scholar 

  • Park, J. J., Detry, M. A., Murthy, S., Guyatt, G., & Mills, E. J. (2022). How to use and interpret the results of a platform trial: Users guide to the medical literature. JAMA, 327(1), 67–74.

    Article  Google Scholar 

  • Reitz, K. M., Seymour, C. W., Vates, J., Quintana, M., Viele, K., Detry, M., & Neal, M. (2020). Strategies to promote resiliency (SPRY): A randomised embedded multifactorial adaptative platform (REMAP) clinical trial protocol to study interventions to improve recovery after surgery in high-risk patients. BMJ Open, 10(9), e037690.

    Google Scholar 

  • Ren, Y., Li, X., & Chen, C. (2021). Statistical considerations of phase 3 umbrella trials allowing adding one treatment arm mid-trial. Contemporary Clinical Trials, 109, 106538.

    Article  Google Scholar 

  • Robert, C., Schachter, J., Long, G. V., Arance, A., Grob, J. J., Mortier, L., & Ribas, A. (2015). Pembrolizumab versus ipilimumab in advanced melanoma. New England Journal of Medicine, 372(26), 2521–2532.

    Google Scholar 

  • Roig, M. B., Krotka, P., Burman, C. F., Glimm, E., Hees, K., Jacko, P., & Posch, M. (2021). On model-based time trend adjustments in platform trials with non-concurrent controls. arXiv:2112.06574.

  • Roychoudhury, S., & Neuenschwander, B. (2020). Bayesian leveraging of historical control data for a clinical trial with timetoevent endpoint. Statistics in Medicine, 39(7), 984–995.

    Article  MathSciNet  Google Scholar 

  • Russo, M., Ventz, S., Wang, V., & Trippa, L. (2021). Inference in response adaptive clinical trials when the enrolled population varies over time. Biometrics.

    Google Scholar 

  • Saville, B. R., & Berry, S. M. (2016). Efficiencies of platform clinical trials: A vision of the future. Clinical Trials, 13(3), 358–366.

    Article  Google Scholar 

  • Schmidli, H., Gsteiger, S., Roychoudhury, S., O’Hagan, A., Spiegelhalter, D., & Neuenschwander, B. (2014). Robust meta analytic predictive priors in clinical trials with historical control information. Biometrics, 70(4), 1023–1032.

    Article  MathSciNet  MATH  Google Scholar 

  • Spiegelhalter, D. J., Best, N. G., Carlin, B. P., & Van Der Linde, A. (2002). Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society: Series b (Statistical Methodology), 64(4), 583–639.

    Article  MathSciNet  MATH  Google Scholar 

  • Stallard, N., Todd, S., Parashar, D., Kimani, P. K., & Renfro, L. A. (2019). On the need to adjust for multiplicity in confirmatory clinical trials with master protocols. Annals of Oncology, 30(4), 506.

    Article  Google Scholar 

  • Tang, R., Shen, J., & Yuan, Y. (2019). ComPAS: A Bayesian drug combination platform trial design with adaptive shrinkage. Statistics in Medicine, 38(7), 1120–1134.

    Google Scholar 

  • Ventz, S., Alexander, B. M., Parmigiani, G., Gelber, R. D., & Trippa, L. (2017). Designing clinical trials that accept new arms: An example in metastatic breast cancer. Journal of Clinical Oncology, 35(27), 3160–3168.

    Article  Google Scholar 

  • Ventz, S., Cellamare, M., Parmigiani, G., & Trippa, L. (2018). Adding experimental arms to platform clinical trials: Randomization procedures and interim analyses. Biostatistics, 19(2), 199–215.

    Article  MathSciNet  Google Scholar 

  • Wathen, J. K., & Thall, P. F. (2017). A simulation study of outcome adaptive randomization in multi-arm clinical trials. Clinical Trials, 14(5), 432–440.

    Article  Google Scholar 

  • Wason, J. M., & Jaki, T. (2012). Optimal design of multiarm multistage trials. Statistics in Medicine, 31(30), 4269–4279.

    Article  MathSciNet  Google Scholar 

  • Wason, J. M., Stecher, L., & Mander, A. P. (2014). Correcting for multiple-testing in multi-arm trials: Is it necessary and is it done? Trials, 15(1), 1–7.

    Article  Google Scholar 

  • Whitehead, J., Desai, Y., & Jaki, T. (2020). Estimation of treatment effects following a sequential trial of multiple treatments. Statistics in Medicine, 39(11), 1593–1609.

    Article  MathSciNet  Google Scholar 

  • Woodcock, J., & LaVange, L. M. (2017). Master protocols to study multiple therapies, multiple diseases, or both. New England Journal of Medicine, 377(1), 62–70.

    Article  Google Scholar 

  • Yuan, Y., Guo, B., Munsell, M., Lu, K., & Jazaeri, A. (2016). MIDAS: A practical Bayesian design for platform trials with molecularly targeted agents. Statistics in Medicine, 35(22), 3892–3906.

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Haitao Pan

  2. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Ying Yuan

Authors
  1. Haitao Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ying Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Haitao Pan .

Rights and permissions

Reprints and permissions

Copyright information

© 2023 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Pan, H., Yuan, Y. (2023). Platform Trials. In: Bayesian Adaptive Design for Immunotherapy and Targeted Therapy. Springer, Singapore. https://doi.org/10.1007/978-981-19-8176-0_9

Download citation

Publish with us

Policies and ethics

Search

Navigation