next.subtrial {BOIN} | R Documentation |

Determine the starting dose and the dose-searching space for next subtrial after the current subtrial is completed when using the waterfall design

```
next.subtrial(
target,
npts,
ntox,
p.saf = 0.6 * target,
p.tox = 1.4 * target,
cutoff.eli = 0.95,
extrasafe = FALSE,
offset = 0.05
)
```

`target` |
the target DLT rate |

`npts` |
a |

`ntox` |
a |

`p.saf` |
the highest toxicity probability that is deemed subtherapeutic (i.e. below
the MTD) such that dose escalation should be undertaken. The default value
is |

`p.tox` |
the lowest toxicity probability that is deemed overly toxic such that
deescalation is required. The default value is |

`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 0 and 0.5) to control how strict the
stopping rule is when |

For the waterfall design, this function is used to obtain the starting dose and
dose-searching space for the next subtrial when the current subtrial is completed.
The input data include: the number of patients treated at each dose combination
(i.e., `npts`

), the number of patients who experienced dose-limiting
toxicities at each dose combination (i.e., `ntox`

).

`next.subtrial()`

returns a list object, containing the starting dose
(`$starting_dose`

) and the dose-searching space for the the next subtrial
(`$next_subtrial`

).

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.

Yan, F., Zhang, L., Zhou, Y., Pan, H., Liu, S. and Yuan, Y. (2020).BOIN: An R Package
for Designing Single-Agent and Drug-Combination Dose-Finding Trials Using Bayesian Optimal
Interval Designs. *Journal of Statistical Software*, 94(13),1-32.<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, 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

```
## determine the starting dose and dose searching space for next subtrial
n <- matrix(c(6, 0, 0, 0,
6, 10, 12, 0,
9, 12, 0, 0), ncol=4, byrow=TRUE)
y <- matrix(c(0, 0, 0, 0,
1, 1, 4, 0,
2, 3, 0, 0), ncol=4, byrow=TRUE)
nxt.trial <- next.subtrial(target=0.3, npts=n, ntox=y)
summary(nxt.trial)
```

[Package *BOIN* version 2.7.2 Index]