| ewoc2 {EWOC.Comb} | R Documentation |
Escalation With Overdose Control for two drugs combination
Description
Finding the doses of next cohort for a phase I clinical trial based on Escalation with Overdose Control (EWOC) design considering the classic parametrization for binary response and two agents.
Usage
ewoc2(dose.a, dose.b, resp, theta, alpha, Min.Dose.A, Max.Dose.A, Min.Dose.B, Max.Dose.B,
a01, b01, a10, b10, a00, b00, a, b, delta1x, delta1y, burn, mm, delta1)
## Default S3 method:
ewoc2(dose.a, dose.b, resp, theta, alpha, Min.Dose.A, Max.Dose.A, Min.Dose.B, Max.Dose.B,
a01, b01, a10, b10, a00, b00, a, b, delta1x, delta1y, burn=4000, mm=2000, delta1=0.05)
Arguments
dose.a |
a numeric vector of allowable doses for drug A |
dose.b |
a numeric vector of allowable doses for drug B |
resp |
a numeric vector of allowable responses, 0 or 1 |
theta |
a numeric value defining the proportion of expectd patients to experience a medically unacceptable, dose-limiting toxicity (DLT) if administered the MTD. |
alpha |
a numerical value defining the probability that dose selected by EWOC is higher than the MTD. |
Min.Dose.A |
a numeric value defining the lower bound of the support of the MTD for drug A |
Max.Dose.A |
a numeric value defining the upper bound of the support of the MTD for drug A |
Min.Dose.B |
a numeric value defining the lower bound of the support of the MTD for drug B |
Max.Dose.B |
a numeric value defining the upper bound of the support of the MTD for drug B |
a01 |
a numeric value for beta prior distribution associated with parameter rho01 |
b01 |
a numeric value for beta prior distribution associated with parameter rho01 |
a10 |
a numeric value for beta prior distribution associated with parameter rho10 |
b10 |
a numeric value for beta prior distribution associated with parameter rho10 |
a00 |
a numeric value for beta prior distribution associated with parameter rho00 |
b00 |
a numeric value for beta prior distribution associated with parameter rho00 |
a |
a numeric value for gamma prior distribution associated with parameter eta |
b |
a numeric value for the gamma prior distribution associated with the parameter eta |
delta1x |
Maximum dose escalation at each step for drug A, the default is 0.2*(Max.Dose.A-Min.Dose.A if not assigned) |
delta1y |
Maximum dose escalation at each step for drug B, the default is 0.2*(Max.Dose.B-Min.Dose.B if not assigned) |
burn |
Number of iterations for adaption, see n.adapt in jags.model for detail |
mm |
Number of iterations to monitor, see n.iter in code.samples for detail |
delta1 |
Threshold for toxicity |
Value
data |
a data frame containing the current doses and responses set |
parameters |
list of input parameters |
priors |
list of prior parameters |
nextdose.x |
the next recommended doses for drug A |
nextdose.y |
the next recommended doses for drug B |
References
Tighiouart M, Li Q and Rogatko A. A Bayesian adaptive design for estimating the maximuym tolerated dose curve using drug combinations in cancer phase I clinical trials. Statistics in Medicine. 2017, 36: 280-290.
Examples
test = ewoc2(dose.a=c(0,0),dose.b=c(0,0),resp=c(0,0),theta=0.33,alpha=0.25,
Min.Dose.A=0, Max.Dose.A=1, Min.Dose.B=0, Max.Dose.B=1,a01=1,b01=1,a10=1,b10=1,
a00=1,b00=1,a=0.8,b=0.0384)
print(test)