Select the maximum tolerated dose (MTD) or MTD contour for drug combination trials

Description

Select the maximum tolerated dose (MTD) or MTD contour after the drug combination trial is completed using the BOIN design or waterfall design

Usage

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select.mtd.comb(target, npts, ntox, cutoff.eli = 0.95, extrasafe = FALSE,
  offset = 0.05, print = TRUE, MTD.contour = FALSE)

Arguments

target

the target toxicity rate

npts

a J*K matrix (J<=K) containing the number of patients treated at each dose combination

ntox

a J*K matrix (J<=K) containing the number of patients experienced dose-limiting toxicity at each dose combination

cutoff.eli

the cutoff to eliminate an overly toxic dose for safety. We recommend the default value of (cutoff.eli=0.95) for general use.

extrasafe

set extrasafe=TRUE to impose a more strict stopping rule for extra safety

offset

a small positive number (between 0 and 0.5) to control how strict the stopping rule is when extrasafe=TRUE. A larger value leads to a more strict stopping rule. The default value offset=0.05 generally works well.

print

to print out the dose selection results.

MTD.contour

set MTD.contour=TRUE to select the MTD contour, otherwise select a single MTD. The value of MTD.contour should be consistent with that in get.oc.comb().

Details

select.mtd.comb() selects a MTD or the MTD contour based on matrix isotonic estimates of toxicity probabilities, depending on MTD.contour is set as TRUE or FALSE. The (matrix) isotonic estimates are obtained by the R package (Iso::biviso).

Value

the MTD(s) based on the trial data.

Note

The MTD selection and dose escalation/deescalation rule are two independent components of the trial design. When appropriate, another dose selection procedure (e.g., based on a fitted logistic model) can be used to select the MTD after the completion of the trial using the BOIN or waterfall design.

Author(s)

Suyu Liu and Ying Yuan

References

Liu S. and Yuan, Y. (2015). Bayesian Optimal Interval Designs for Phase I Clinical Trials, Journal of the Royal Statistical Society: Series C, 64, 507-523.

Lin R. and Yin, G. (2016). Bayesian Optimal Interval Designs for Dose Finding in Drug-combination Trials, Statistical Methods in Medical Research, to appear.

Zhang L. and Yuan, Y. (2016). A Simple Bayesian Design to Identify the Maximum Tolerated Dose Contour for Drug Combination Trials, under review.

See Also

Tutorial: http://odin.mdacc.tmc.edu/~yyuan/Software/BOIN/BOIN2.4_tutorial.pdf

Paper: http://odin.mdacc.tmc.edu/~yyuan/Software/BOIN/paper.pdf

Examples

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## Select the MTD based on the data from a 3x5 combination trial
## matrix n contains the number of patients treated at each dose combination
## matrix y contains the number of patients experienced toxicity at each dose combination

n<-matrix(c(3, 5, 0, 0, 0, 7, 6, 15, 0, 0, 0, 0, 4, 0, 0), ncol=5, byrow=TRUE)
y<-matrix(c(0, 1, 0, 0, 0, 1, 1, 4, 0, 0, 0, 0, 2, 0, 0), ncol=5, byrow=TRUE)
select.mtd.comb(target=0.3, npts=n, ntox=y, MTD.contour=FALSE)

## Select the MTD contour based on the data from a 3x4 combination trial
## matrix n contains the number of patients treated at each dose combination
## matrix y contains the number of patients experienced toxicity at each dose combination

n<-matrix(c(6, 9, 24, 0,  6, 24, 9, 0,  12, 18, 0, 0), ncol=4, byrow=TRUE)
y<-matrix(c(0, 1,  5, 0,  1,  5, 4, 0,  1, 5, 0, 0), ncol=4, byrow=TRUE)
select.mtd.comb(target=0.3, npts=n, ntox=y, MTD.contour=TRUE)