Skip to main content
SpringerLink
Log in

PoD-TPI: Probability-of-Decision Toxicity Probability Interval Design to Accelerate Phase I Trials

  • Published:
Statistics in Biosciences Aims and scope Submit manuscript

Abstract

Cohort-based enrollment can slow down dose-finding trials since the outcomes of the previous cohort must be fully evaluated before the next cohort can be enrolled. This results in frequent suspension of patient enrollment. The issue is exacerbated in recent immune oncology trials where toxicity outcomes can take a long time to observe. We propose a novel phase I design, the probability-of-decision toxicity probability interval (PoD-TPI) design, to accelerate phase I trials. PoD-TPI enables dose assignment in real time in the presence of pending toxicity outcomes. With uncertain outcomes, the dose assignment decisions are treated as a random variable, and we calculate the posterior distribution of the decisions. The posterior distribution reflects the variability in the pending outcomes and allows a direct and intuitive evaluation of the confidence of all possible decisions. Optimal decisions are calculated based on 0-1 loss, and extra safety rules are constructed to enforce sufficient protection from exposing patients to risky doses. A new and useful feature of PoD-TPI is that it allows investigators and regulators to balance the trade-off between enrollment speed and making risky decisions by tuning a pair of intuitive design parameters. Through numerical studies, we evaluate the operating characteristics of PoD-TPI and demonstrate that PoD-TPI shortens trial duration and maintains trial safety and efficiency compared to existing time-to-event designs.

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

Fig. 1

Similar content being viewed by others

References

  1. Boag JW (1949) Maximum likelihood estimates of the proportion of patients cured by cancer therapy. J Roy Stat Soc Ser B (Methodol) 11(1):15–53

    MATH  Google Scholar 

  2. Chen SX, Liu JS (1997) Statistical applications of the Poisson-binomial and conditional Bernoulli distributions. Stat Sin 7(4):875–892

    MathSciNet  MATH  Google Scholar 

  3. Cheung YK, Chappell R (2000) Sequential designs for phase I clinical trials with late-onset toxicities. Biometrics 56(4):1177–1182

    MathSciNet  MATH  Google Scholar 

  4. Cheung YK, Chappell R (2002) A simple technique to evaluate model sensitivity in the continual reassessment method. Biometrics 58(3):671–674

    MathSciNet  MATH  Google Scholar 

  5. Guo W, Wang SJ, Yang S, Lynn H, Ji Y (2017) A Bayesian interval dose-finding design addressing Ockham’s razor: mTPI-2. Contemp Clin Trials 58:23–33

    Google Scholar 

  6. Guo W, Ji Y, Li D (2019) R-TPI: Rolling toxicity probability interval design to shorten the duration and maintain safety of phase I trials. J Biopharm Stat 29(3):1–4

    Google Scholar 

  7. Ivanova A, Flournoy N, Chung Y (2007) Cumulative cohort design for dose-finding. J Stat Plan Inference 137(7):2316–2327

    MathSciNet  MATH  Google Scholar 

  8. Jefferys WH, Berger JO (1992) Ockham’s razor and Bayesian analysis. Am Sci 80(1):64–72

    Google Scholar 

  9. Ji Y, Wang SJ (2013) Modified toxicity probability interval design: a safer and more reliable method than the 3+3 design for practical phase I trials. J Clin Oncol 31(14):1785–1791

    Google Scholar 

  10. Ji Y, Li Y, Nebiyou Bekele B (2007) Dose-finding in phase I clinical trials based on toxicity probability intervals. Clin Trials 4(3):235–244

    Google Scholar 

  11. Ji Y, Liu P, Li Y, Nebiyou Bekele B (2010) A modified toxicity probability interval method for dose-finding trials. Clin Trials 7(6):653–663

    Google Scholar 

  12. Kanjanapan Y, Day D, Butler M, Wang L, Joshua A, Hogg D, Leighl N, Razak AA, Hansen A, Boujos S, Chappell M, Chow K, Sherwin B, Stayner LA, Soultani L, Zambrana A, Siu L, Bedard P, Spreafico A (2019) Delayed immune-related adverse events in assessment for dose-limiting toxicity in early phase immunotherapy trials. Eur J Cancer 107:1–7

    Google Scholar 

  13. Klein JP, Moeschberger ML (2006) Survival analysis: techniques for censored and truncated data. Springer, New York

    MATH  Google Scholar 

  14. Lee SM, Cheung YK (2009) Model calibration in the continual reassessment method. Clin Trials 6(3):227–238

    Google Scholar 

  15. Lin R, Yuan Y (2018) Time-to-event model-assisted designs to accelerate phase I clinical trials. arXiv preprint arXiv:180708393

  16. Liu M, Wang SJ, Ji Y (2019) The i3+3 design for phase I clinical trials. arXiv preprint arXiv:190101303

  17. Liu S, Yuan Y (2015) Bayesian optimal interval designs for phase I clinical trials. J R Stat Soc Ser C (Appl Stat) 64(3):507–523

    MathSciNet  Google Scholar 

  18. Mossé YP, Lim MS, Voss SD, Wilner K, Ruffner K, Laliberte J, Rolland D, Balis FM, Maris JM, Weigel BJ, Ingle AM, Ahern C, Adamson PC, Blaney SM (2013) Safety and activity of crizotinib for paediatric patients with refractory solid tumours or anaplastic large-cell lymphoma: a children’s oncology group phase 1 consortium study. Lancet Oncol 14(6):472–480

    Google Scholar 

  19. Normolle D, Lawrence T (2006) Designing dose-escalation trials with late-onset toxicities using the time-to-event continual reassessment method. J Clin Oncol 24(27):4426–4433

    Google Scholar 

  20. O’Quigley J, Pepe M, Fisher L (1990) Continual reassessment method: a practical design for phase 1 clinical trials in cancer. Biometrics 46(1):33–48

    MathSciNet  MATH  Google Scholar 

  21. Skolnik JM, Barrett JS, Jayaraman B, Patel D, Adamson PC (2008) Shortening the timeline of pediatric phase I trials: the rolling six design. J Clin Oncol 26(2):190–195

    Google Scholar 

  22. von Stackelberg A, Locatelli F, Zugmaier G, Handgretinger R, Trippett TM, Rizzari C, Bader P, O’brien MM, Brethon B, Bhojwani D, Schlegel PG, Borkhardt A, Rheingold SR, Cooper TM, Zwaan CM, Barnette P, Messina C, Michel G, DuBois SG, Hu K, Zhu M, Whitlock JA, Gore L (2016) Phase I/phase II study of blinatumomab in pediatric patients with relapsed/refractory acute lymphoblastic leukemia. J Clin Oncol 34(36):4381–4389

    Google Scholar 

  23. Storer BE (1989) Design and analysis of phase I clinical trials. Biometrics 45(3):925–937

    MathSciNet  MATH  Google Scholar 

  24. Yan F, Mandrekar SJ, Yuan Y (2017) Keyboard: a novel Bayesian toxicity probability interval design for phase I clinical trials. Clin Cancer Res 23(15):3994–4003

    Google Scholar 

  25. Yuan Y, Lin R, Li D, Nie L, Warren KE (2018) Time-to-event Bayesian optimal interval design to accelerate phase I trials. Clinical Cancer Research Article No. 0246

Download references

Author information

Authors and Affiliations

  1. Department of Public Health Sciences, The University of Chicago, Chicago, USA

    Tianjian Zhou & Yuan Ji

  2. Laiya Consulting, Inc., Chicago, USA

    Wentian Guo

Authors
  1. Tianjian Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wentian Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yuan Ji
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuan Ji.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (pdf 191 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhou, T., Guo, W. & Ji, Y. PoD-TPI: Probability-of-Decision Toxicity Probability Interval Design to Accelerate Phase I Trials. Stat Biosci 12, 124–145 (2020). https://doi.org/10.1007/s12561-019-09264-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12561-019-09264-0

Keywords

Search

Navigation