TY - JOUR
T1 - Improved designs for dose escalation studies using pharmacokinetic measurements
AU - Piantadosi, Steven
AU - Liu, Guanghan
PY - 1996/8/15
Y1 - 1996/8/15
N2 - We describe a method for incorporating pharmacokinetic (PK) data into dose escalation clinical trial designs. Doing so can improve the efficiency and accuracy of these studies. The method proposed uses a parametric dose response function that models the probability of response in each person with two effects: the dose of drug administered and an ancillary pharmacokinetic measurement. After treatment and observation of each subject (or group of subjects) for response, one calculates the dose to be administered to the next individual (or group) to yield the target probability of response from the current best estimate of the dose-response curve. This procedure is a variant of the continual reassesment method (CRM). Statistical simulations employing a logistic dose-response model (that is, we model the legit of the response probability as a linear combination of predictors), dose of drug, and the area under the time-concentration curve (AUC) demonstrate that the addition of pharmacokinetic information to the CRM is a practical and useful way to improve both dose-response modelling and the design of dose escalation studies.
AB - We describe a method for incorporating pharmacokinetic (PK) data into dose escalation clinical trial designs. Doing so can improve the efficiency and accuracy of these studies. The method proposed uses a parametric dose response function that models the probability of response in each person with two effects: the dose of drug administered and an ancillary pharmacokinetic measurement. After treatment and observation of each subject (or group of subjects) for response, one calculates the dose to be administered to the next individual (or group) to yield the target probability of response from the current best estimate of the dose-response curve. This procedure is a variant of the continual reassesment method (CRM). Statistical simulations employing a logistic dose-response model (that is, we model the legit of the response probability as a linear combination of predictors), dose of drug, and the area under the time-concentration curve (AUC) demonstrate that the addition of pharmacokinetic information to the CRM is a practical and useful way to improve both dose-response modelling and the design of dose escalation studies.
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U2 - 10.1002/(SICI)1097-0258(19960815)15:15<1605::AID-SIM325>3.0.CO;2-2
DO - 10.1002/(SICI)1097-0258(19960815)15:15<1605::AID-SIM325>3.0.CO;2-2
M3 - Article
C2 - 8858785
AN - SCOPUS:0029780751
SN - 0277-6715
VL - 15
SP - 1605
EP - 1618
JO - Statistics in Medicine
JF - Statistics in Medicine
IS - 15
ER -