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A practical design for a dual-agent dose-escalation trial that incorporates pharmacokinetic data

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A practical design for a dual-agent dose-escalation trial that incorporates pharmacokinetic data. / Cotterill, Amy; Lorand, D.; Wang, J. et al.
In: Statistics in Medicine, Vol. 34, No. 13, 15.06.2015, p. 2138-2164.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Cotterill, A, Lorand, D, Wang, J & Jaki, T 2015, 'A practical design for a dual-agent dose-escalation trial that incorporates pharmacokinetic data', Statistics in Medicine, vol. 34, no. 13, pp. 2138-2164. https://doi.org/10.1002/sim.6482

APA

Cotterill, A., Lorand, D., Wang, J., & Jaki, T. (2015). A practical design for a dual-agent dose-escalation trial that incorporates pharmacokinetic data. Statistics in Medicine, 34(13), 2138-2164. https://doi.org/10.1002/sim.6482

Vancouver

Cotterill A, Lorand D, Wang J, Jaki T. A practical design for a dual-agent dose-escalation trial that incorporates pharmacokinetic data. Statistics in Medicine. 2015 Jun 15;34(13):2138-2164. Epub 2015 Mar 24. doi: 10.1002/sim.6482

Author

Cotterill, Amy ; Lorand, D. ; Wang, J. et al. / A practical design for a dual-agent dose-escalation trial that incorporates pharmacokinetic data. In: Statistics in Medicine. 2015 ; Vol. 34, No. 13. pp. 2138-2164.

Bibtex

@article{36c605d44e284503950e2610f03a7232,
title = "A practical design for a dual-agent dose-escalation trial that incorporates pharmacokinetic data",
abstract = "Traditionally, model-based dose-escalation trial designs recommend a dose for escalation based on an assumed dose-toxicity relationship. Pharmacokinetic data are often available but are currently only utilised by clinical teams in a subjective manner to aid decision making if the dose-toxicity model recommendation is felt to be too high. Formal incorporation of pharmacokinetic data in dose-escalation could therefore make the decision process more efficient and lead to an increase in the precision of the resulting recommended dose, as well as decreasing the subjectivity of its use. Such an approach is investigated in the dual-agent setting using a Bayesian design, where historical single-agent data are available to advise the use of pharmacokinetic data in the dual-agent setting. The dose-toxicity and dose-exposure relationships are modelled independently and the outputs combined in the escalation rules. Implementation of stopping rules highlight the practicality of the design. This is demonstrated through an example which is evaluated using simulation.",
keywords = "dose-escalation, pharmacokinetic data, dual-agent, escalation rules, combination treatment",
author = "Amy Cotterill and D. Lorand and J. Wang and Thomas Jaki",
year = "2015",
month = jun,
day = "15",
doi = "10.1002/sim.6482",
language = "English",
volume = "34",
pages = "2138--2164",
journal = "Statistics in Medicine",
issn = "0277-6715",
publisher = "John Wiley and Sons Ltd",
number = "13",

}

RIS

TY - JOUR

T1 - A practical design for a dual-agent dose-escalation trial that incorporates pharmacokinetic data

AU - Cotterill, Amy

AU - Lorand, D.

AU - Wang, J.

AU - Jaki, Thomas

PY - 2015/6/15

Y1 - 2015/6/15

N2 - Traditionally, model-based dose-escalation trial designs recommend a dose for escalation based on an assumed dose-toxicity relationship. Pharmacokinetic data are often available but are currently only utilised by clinical teams in a subjective manner to aid decision making if the dose-toxicity model recommendation is felt to be too high. Formal incorporation of pharmacokinetic data in dose-escalation could therefore make the decision process more efficient and lead to an increase in the precision of the resulting recommended dose, as well as decreasing the subjectivity of its use. Such an approach is investigated in the dual-agent setting using a Bayesian design, where historical single-agent data are available to advise the use of pharmacokinetic data in the dual-agent setting. The dose-toxicity and dose-exposure relationships are modelled independently and the outputs combined in the escalation rules. Implementation of stopping rules highlight the practicality of the design. This is demonstrated through an example which is evaluated using simulation.

AB - Traditionally, model-based dose-escalation trial designs recommend a dose for escalation based on an assumed dose-toxicity relationship. Pharmacokinetic data are often available but are currently only utilised by clinical teams in a subjective manner to aid decision making if the dose-toxicity model recommendation is felt to be too high. Formal incorporation of pharmacokinetic data in dose-escalation could therefore make the decision process more efficient and lead to an increase in the precision of the resulting recommended dose, as well as decreasing the subjectivity of its use. Such an approach is investigated in the dual-agent setting using a Bayesian design, where historical single-agent data are available to advise the use of pharmacokinetic data in the dual-agent setting. The dose-toxicity and dose-exposure relationships are modelled independently and the outputs combined in the escalation rules. Implementation of stopping rules highlight the practicality of the design. This is demonstrated through an example which is evaluated using simulation.

KW - dose-escalation

KW - pharmacokinetic data

KW - dual-agent

KW - escalation rules

KW - combination treatment

U2 - 10.1002/sim.6482

DO - 10.1002/sim.6482

M3 - Journal article

VL - 34

SP - 2138

EP - 2164

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 0277-6715

IS - 13

ER -