select.mtd.comb {BOIN}  R Documentation 
Select the maximum tolerated dose (MTD) or MTD contour after the drug combination trial is completed using the BOIN design or waterfall design
select.mtd.comb(
target,
npts,
ntox,
cutoff.eli = 0.95,
extrasafe = FALSE,
offset = 0.05,
boundMTD = FALSE,
p.tox = 1.4 * target,
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 
boundMTD 
set 
p.tox 
the lowest toxicity probability that is deemed overly toxic such
that deescalation is required. The default value is

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, Yanhong Zhou, 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, 507523.
Lin R. and Yin, G. (2017). Bayesian Optimal Interval Designs for Dose Finding in Drugcombination Trials, Statistical Methods in Medical Research, 26, 21552167.
Yan, F., Zhang, L., Zhou, Y., Pan, H., Liu, S. and Yuan, Y. (2020).BOIN: An R Package for Designing SingleAgent and DrugCombination DoseFinding Trials Using Bayesian Optimal Interval Designs. Journal of Statistical Software, 94(13),132.<doi:10.18637/jss.v094.i13>.
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, 49244936.
Tutorial: http://odin.mdacc.tmc.edu/~yyuan/Software/BOIN/BOIN2.6_tutorial.pdf
Paper: http://odin.mdacc.tmc.edu/~yyuan/Software/BOIN/paper.pdf
### drugcombination 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(sel.comb)
plot(sel.comb)
### drugcombination 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(sel.comb2)
plot(sel.comb2)