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