Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/select.mtd.comb.R

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

1 2 | ```
select.mtd.comb(target, npts, ntox, cutoff.eli = 0.95, extrasafe = FALSE,
offset = 0.05, mtd.contour = FALSE)
``` |

`target` |
the target DLT rate |

`npts` |
a |

`ntox` |
a |

`cutoff.eli` |
the cutoff to eliminate an overly toxic dose for safety.
We recommend the default value of ( |

`extrasafe` |
set |

`offset` |
a small positive number (between |

`mtd.contour` |
set |

`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).

`select.mtd.comb()`

returns returns (1) target toxicity probability (`$target`

),
(2) selected MTD or MTD contour (`$MTD`

),
(3) isotonic estimate of the DLT probablity at each dose (`$p_est`

).

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.

Suyu Liu, Liangcai Zhang and Ying Yuan

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. (2017). Bayesian Optimal Interval Designs for Dose Finding in
Drug-combination Trials, *Statistical Methods in Medical Research*, 26, 2155-2167.

Zhang L. and Yuan, Y. (2016). A Simple Bayesian Design to Identify the Maximum
Tolerated Dose Contour for Drug Combination Trials, *Statistics in Medicine*, 35, 4924-4936.

Tutorial: http://odin.mdacc.tmc.edu/~yyuan/Software/BOIN/BOIN2.6_tutorial.pdf

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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ```
### drug-combination trial to find a single MTD
## 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)
sel.comb <- select.mtd.comb(target=0.3, npts=n, ntox=y)
summary.boin(sel.comb)
plot.boin(sel.comb)
### drug-combination trial to find the MTD contour
## 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)
sel.comb2 <- select.mtd.comb(target=0.3, npts=n, ntox=y, mtd.contour=TRUE)
summary.boin(sel.comb2)
plot.boin(sel.comb2)
``` |

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