Skip to main content
Top
Published in: BMC Medical Research Methodology 1/2021

Open Access 01-12-2021 | Pharmacokinetics | Research article

Phase I dose-escalation oncology trials with sequential multiple schedules

Authors: Burak Kürsad Günhan, Sebastian Weber, Abdelkader Seroutou, Tim Friede

Published in: BMC Medical Research Methodology | Issue 1/2021

Login to get access

Abstract

Background

Conventional methods for phase I dose-escalation trials in oncology are based on a single treatment schedule only. More recently, however, multiple schedules are more frequently investigated in the same trial.

Methods

Here, we consider sequential phase I trials, where the trial proceeds with a new schedule (e.g. daily or weekly dosing) once the dose escalation with another schedule has been completed. The aim is to utilize the information from both the completed and the ongoing schedules to inform decisions on the dose level for the next dose cohort. For this purpose, we adapted the time-to-event pharmacokinetics (TITE-PK) model, which were originally developed for simultaneous investigation of multiple schedules. TITE-PK integrates information from multiple schedules using a pharmacokinetics (PK) model.

Results

In a simulation study, the developed approach is compared to the bridging continual reassessment method and the Bayesian logistic regression model using a meta-analytic-predictive prior. TITE-PK results in better performance than comparators in terms of recommending acceptable dose and avoiding overly toxic doses for sequential phase I trials in most of the scenarios considered. Furthermore, better performance of TITE-PK is achieved while requiring similar number of patients in the simulated trials. For the scenarios involving one schedule, TITE-PK displays similar performance with alternatives in terms of acceptable dose recommendations. The R and Stan code for the implementation of an illustrative sequential phase I trial example in oncology is publicly available (https://​github.​com/​gunhanb/​TITEPK_​sequential).

Conclusion

In phase I oncology trials with sequential multiple schedules, the use of all relevant information is of great importance. For these trials, the adapted TITE-PK which combines information using PK principles is recommended.
Literature
1.
go back to reference Le Tourneau C, Lee J, Siu L. Dose escalation methods in phase I cancer clinical trials. J Natl Cancer Inst. 2009; 101(10):708–20.CrossRef Le Tourneau C, Lee J, Siu L. Dose escalation methods in phase I cancer clinical trials. J Natl Cancer Inst. 2009; 101(10):708–20.CrossRef
3.
go back to reference Sverdlov O, Wong W, Ryeznik Y. Adaptive clinical trial designs for phase I cancer studies. Statist Surv. 2014; 8:2–44.CrossRef Sverdlov O, Wong W, Ryeznik Y. Adaptive clinical trial designs for phase I cancer studies. Statist Surv. 2014; 8:2–44.CrossRef
4.
go back to reference Neuenschwander B, Branson M, Gsponer T. Critical aspects of the Bayesian approach to phase I cancer trials. Stat Med. 2008; 27(13):2420–39.CrossRef Neuenschwander B, Branson M, Gsponer T. Critical aspects of the Bayesian approach to phase I cancer trials. Stat Med. 2008; 27(13):2420–39.CrossRef
6.
go back to reference Storer B. Design and analysis of phase I clinical trials. Biom. 1989; 45(3):925–37.CrossRef Storer B. Design and analysis of phase I clinical trials. Biom. 1989; 45(3):925–37.CrossRef
7.
go back to reference O’Quigley J, Pepe M, Fisher L. Continual reassessment method: A practical design for phase 1 clinical trials in cancer. Biom. 1990; 46(1):33–48.CrossRef O’Quigley J, Pepe M, Fisher L. Continual reassessment method: A practical design for phase 1 clinical trials in cancer. Biom. 1990; 46(1):33–48.CrossRef
8.
go back to reference Neuenschwander B, Matano A, Tang Z, Roychoudhury S, Wandel S, Bailey S. A Bayesian industry approach to phase I combination trials in oncology In: Zhao W, Yang H, editors. Statistical Methods in Drug Combination Studies. Boca Raton: CRC Press: 2015. p. 95–135. Neuenschwander B, Matano A, Tang Z, Roychoudhury S, Wandel S, Bailey S. A Bayesian industry approach to phase I combination trials in oncology In: Zhao W, Yang H, editors. Statistical Methods in Drug Combination Studies. Boca Raton: CRC Press: 2015. p. 95–135.
9.
go back to reference Babb J, Rogatko A, Zacks S. Cancer phase I clinical trials: Efficient dose escalation with overdose control. Stat Med. 1998; 17(10):1103–20.CrossRef Babb J, Rogatko A, Zacks S. Cancer phase I clinical trials: Efficient dose escalation with overdose control. Stat Med. 1998; 17(10):1103–20.CrossRef
10.
go back to reference Braun T, Thall P, H N, De Lima M. Simultaneously optimizing dose and schedule of a new cytotoxic agent. Clin Trials. 2007; 4(2):113–24.CrossRef Braun T, Thall P, H N, De Lima M. Simultaneously optimizing dose and schedule of a new cytotoxic agent. Clin Trials. 2007; 4(2):113–24.CrossRef
11.
go back to reference Wages N, O’Quigley J, Conaway M. Phase I design for completely or partially ordered treatment schedules. Stat Med. 2014; 33(4):569–79.CrossRef Wages N, O’Quigley J, Conaway M. Phase I design for completely or partially ordered treatment schedules. Stat Med. 2014; 33(4):569–79.CrossRef
12.
go back to reference Günhan BK, Weber S, Friede T. A Bayesian time-to-event pharmacokinetic model for phase I dose-escalation trials with multiple schedules. Stat Med. 2020; 39(27):3986–4000.CrossRef Günhan BK, Weber S, Friede T. A Bayesian time-to-event pharmacokinetic model for phase I dose-escalation trials with multiple schedules. Stat Med. 2020; 39(27):3986–4000.CrossRef
13.
go back to reference Liu S, Pan H, Xia J, Huang Q, Yuan Y. Bridging continual reassessment method for phase I clinical trials in different ethnic populations. Stat Med. 2015; 34(10):1681–94.CrossRef Liu S, Pan H, Xia J, Huang Q, Yuan Y. Bridging continual reassessment method for phase I clinical trials in different ethnic populations. Stat Med. 2015; 34(10):1681–94.CrossRef
14.
go back to reference Neuenschwander B, Roychoudhury S, Schmidli H. On the use of co-data in clinical trials. Stat Biopharm Res. 2016; 8(3):345–54.CrossRef Neuenschwander B, Roychoudhury S, Schmidli H. On the use of co-data in clinical trials. Stat Biopharm Res. 2016; 8(3):345–54.CrossRef
17.
go back to reference Schmidli H, Gsteiger S, Roychoudhury S, O’Hagan A, Spiegelhalter D, Neuenschwander B. Robust meta-analytic-predictive priors in clinical trials with historical control information. Biom. 2014; 70(4):1023–32.CrossRef Schmidli H, Gsteiger S, Roychoudhury S, O’Hagan A, Spiegelhalter D, Neuenschwander B. Robust meta-analytic-predictive priors in clinical trials with historical control information. Biom. 2014; 70(4):1023–32.CrossRef
20.
go back to reference O’Donnell A, Faivre S, Burris III H, Rea D, Papadimitrakopoulou V, Shand N, Lane H, Hazell K, Zoellner U, Kovarik J, Brock C, Jones S, Raymond E, Judson I. Phase I pharmacokinetic and pharmacodynamic study of the oral mammalian target of rapamycin inhibitor everolimus in patients with advanced solid tumors. J Clin Oncol. 2008; 26(10):1588–95.CrossRef O’Donnell A, Faivre S, Burris III H, Rea D, Papadimitrakopoulou V, Shand N, Lane H, Hazell K, Zoellner U, Kovarik J, Brock C, Jones S, Raymond E, Judson I. Phase I pharmacokinetic and pharmacodynamic study of the oral mammalian target of rapamycin inhibitor everolimus in patients with advanced solid tumors. J Clin Oncol. 2008; 26(10):1588–95.CrossRef
21.
go back to reference Besse B, Heist R, Papadmitrakopoulou V, Camidge D, Beck J, Schmid P, Mulatero C, Miller N, Dimitrijevic S, Urva S, Pylvaenaeinen I, Petrovic K, Johnson B. A phase Ib dose-escalation study of everolimus combined with cisplatin and etoposide as first-line therapy in patients with extensive-stage small-cell lung cancer. Ann Oncol. 2014; 25(2):505–11.CrossRef Besse B, Heist R, Papadmitrakopoulou V, Camidge D, Beck J, Schmid P, Mulatero C, Miller N, Dimitrijevic S, Urva S, Pylvaenaeinen I, Petrovic K, Johnson B. A phase Ib dose-escalation study of everolimus combined with cisplatin and etoposide as first-line therapy in patients with extensive-stage small-cell lung cancer. Ann Oncol. 2014; 25(2):505–11.CrossRef
22.
go back to reference Cheung Y, Chappell R. Sequential designs for phase I clinical trials with late-onset toxicities. Biom. 2000; 56(4):1177–82.CrossRef Cheung Y, Chappell R. Sequential designs for phase I clinical trials with late-onset toxicities. Biom. 2000; 56(4):1177–82.CrossRef
23.
go back to reference Spiegelhalter D, Abrams K, Myles J. Prior distributions. In: Bayesian Approaches to Clinical Trials and Health-Care Evaluation. West Sussex: CRC Press: 2004. p. 139–181. Spiegelhalter D, Abrams K, Myles J. Prior distributions. In: Bayesian Approaches to Clinical Trials and Health-Care Evaluation. West Sussex: CRC Press: 2004. p. 139–181.
24.
go back to reference Neuenschwander B, Capkun-Niggli G, Branson M, Spiegelhalter D. Summarizing historical information on controls in clinical trials. Clin Trials. 2010; 7(1):5–18.CrossRef Neuenschwander B, Capkun-Niggli G, Branson M, Spiegelhalter D. Summarizing historical information on controls in clinical trials. Clin Trials. 2010; 7(1):5–18.CrossRef
26.
go back to reference Lee S, Cheung Y. Model calibration in the continual reassessment method. Clin Trials. 2009; 6(3):227–38.CrossRef Lee S, Cheung Y. Model calibration in the continual reassessment method. Clin Trials. 2009; 6(3):227–38.CrossRef
27.
go back to reference Ayer M, Brunk H, Ewing G, Reid W, Silverman E. An empirical distribution function for sampling with incomplete information. Ann Math Statist. 1955; 26(4):641–7.CrossRef Ayer M, Brunk H, Ewing G, Reid W, Silverman E. An empirical distribution function for sampling with incomplete information. Ann Math Statist. 1955; 26(4):641–7.CrossRef
28.
go back to reference Barlow R, Bartholomew D, Bremner J, Brunk H. Chapter 1. In: Statistical Inference Under Order Restrictions: The Theory and Application of Isotonic Regression. New York, USA: Wiley: 1972. p. 1–64. Barlow R, Bartholomew D, Bremner J, Brunk H. Chapter 1. In: Statistical Inference Under Order Restrictions: The Theory and Application of Isotonic Regression. New York, USA: Wiley: 1972. p. 1–64.
29.
go back to reference Yin G, Yuan Y. Bayesian model averaging continual reassessment method in phase I clinical trials. J Am Stat Assoc. 2009; 104(487):954–68.CrossRef Yin G, Yuan Y. Bayesian model averaging continual reassessment method in phase I clinical trials. J Am Stat Assoc. 2009; 104(487):954–68.CrossRef
31.
go back to reference Cox E, Veyrat-Follet C, Beal S, Fuseau E, Kenkare S, Sheiner L. A population pharmacokinetic–pharmacodynamic analysis of repeated measures time-to-event pharmacodynamic responses: The antiemetic effect of ondansetron. J Pharmacokinet Biopharm. 1999; 27(6):625–44.CrossRef Cox E, Veyrat-Follet C, Beal S, Fuseau E, Kenkare S, Sheiner L. A population pharmacokinetic–pharmacodynamic analysis of repeated measures time-to-event pharmacodynamic responses: The antiemetic effect of ondansetron. J Pharmacokinet Biopharm. 1999; 27(6):625–44.CrossRef
32.
go back to reference Ursino M, Zohar S, Lentz F, Alberti C, Friede T, Stallard N, Comets E. Dose-finding methods for phase i clinical trials using pharmacokinetics in small populations. Biom J. 2017; 59(4):804–25.CrossRef Ursino M, Zohar S, Lentz F, Alberti C, Friede T, Stallard N, Comets E. Dose-finding methods for phase i clinical trials using pharmacokinetics in small populations. Biom J. 2017; 59(4):804–25.CrossRef
33.
go back to reference Ooi Q, Hasegawa C, Duffull S, Wright D. Kinetic-pharmacodynamic model for drugs with non-linear elimination: Parameterisation matters. Br J Clin Pharmacol. 2020; 86(2):196–8.CrossRef Ooi Q, Hasegawa C, Duffull S, Wright D. Kinetic-pharmacodynamic model for drugs with non-linear elimination: Parameterisation matters. Br J Clin Pharmacol. 2020; 86(2):196–8.CrossRef
34.
go back to reference Kalbfleisch J, Prentice R. Failure time models. In: The Statistical Analysis of Failure Time Data. New York, NY: John Wiley & Sons: 2002. p. 31–52.CrossRef Kalbfleisch J, Prentice R. Failure time models. In: The Statistical Analysis of Failure Time Data. New York, NY: John Wiley & Sons: 2002. p. 31–52.CrossRef
35.
go back to reference Carpenter B, Gelman A, Hoffman M, Lee D, Goodrich B, Betancourt M, Brubaker M, Guo J, Li P, Riddell A. Stan: A probabilistic programming language. J Stat Softw. 2017; 76(1):1–32.CrossRef Carpenter B, Gelman A, Hoffman M, Lee D, Goodrich B, Betancourt M, Brubaker M, Guo J, Li P, Riddell A. Stan: A probabilistic programming language. J Stat Softw. 2017; 76(1):1–32.CrossRef
37.
go back to reference Benda N, Branson M, Maurer M, Friede T. Aspects of modernizing drug development using clinical scenario planning and evaluation. Drug Inf J. 2010; 44(3):299–315.CrossRef Benda N, Branson M, Maurer M, Friede T. Aspects of modernizing drug development using clinical scenario planning and evaluation. Drug Inf J. 2010; 44(3):299–315.CrossRef
38.
go back to reference 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.CrossRef 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.CrossRef
Metadata
Title
Phase I dose-escalation oncology trials with sequential multiple schedules
Authors
Burak Kürsad Günhan
Sebastian Weber
Abdelkader Seroutou
Tim Friede
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2021
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/s12874-021-01218-9

Other articles of this Issue 1/2021

BMC Medical Research Methodology 1/2021 Go to the issue