dec.sim: run dose-finding simulations
In tsdf: Two-/Three-Stage Designs for Phase 1&2 Clinical Trials

Description Usage Arguments Details Value Author(s) Examples

Run dose-finding simulations based on a customized decision table.

1	dec.sim(truep, decTable, start.level = 1, nsim = 1000)

`truep`	a vector of length k (the number of doses being considered in the trial), with values equal to the true probabilities of toxicity at the dose levels.
`decTable`	a customized decision table. (same format as output of `dec.table`)
`start.level`	starting dose level. Defaults to 1, i.e. the lowest dose level.
`nsim`	the number of simulation trials. Defaults to 1000.

Assume there are $d$ dose levels to be studied. Denote the cumulative number of patients treated and cumulative number of DLTs at the current dose level are $n_i$ and $m_i$, respectively. $n_max$ is the maximum number of patients permitted to be treated at each dose level. The procedure is as follows

Step 1 : Update cumulative number of DLTs $m_i$ and total number of patients $n_i$ treated at the current dose and use the decision table to make a decision: if decision is “S" –> step 2; if decision is “D" or “DU” –> step 3; if decision is “E” –> step 4
Step 2 : If $n_i = n_max$, declare dose i as the MTD; otherwise, update $m_i$ and $n_i$ with additional cohort of patients and go to Step 1.
Step 3 : If the current dose level is the highest dose level, then: if n_i < n_max, update $m_i$ and $n_i$ with additional cohort of patients and go to Step 1; otherwise, stop the trial and declare that the MTD is higher than the highest dose level (inconclusive); If the current dose is not the lowest dose, then: if $n_i-1 < n_max$, update $m_i-1$ and $n_i-1$ with additional cohort of patients and set the current dose level to be the next lower dose level, and go to Step 1; otherwise, stop the trial and declare the next lower dose level is the MTD; Additionally, if the decision is “DU”, record this dose level as DU and never treat additional patients at the current dose level again.
Step 4 : If the current dose level is the highest dose level, then: if $n_i < n_max$, update $m_i$ and $n_i$ with additional cohort of patients and go to Step 1; otherwise, stop the trial and declare that the MTD is higher than the highest dose level (inconclusive); If the next higher dose level is of status DU, then: if $n_i < n_max$, update $m_i$ and $n_i$ with additional cohort of patients and go to step 1; otherwise stop, the current dose level is MTD; Otherwise: if $n_i+1 < n_max$, update $m_i+1$ and $n_i+1$ with additional cohort of patients, set the current dose level to be next higher dose level, and go to step 1; else, the current dose level is the MTD.

the functions summary.dec.sim is used to obtain and print a summary table of the results (recommended). An object of class "dec.sim" is a list containing:

`mtd`	a vector of dose levels giving the recommended maximum tolerated dose (MTD) at the end of the trial.
`mtd.prob`	a vector of length `k` giving the average proportions of selected as MTD at each dose level.
`over.prob`	a vector of length `k` giving the average proportions of selected as over the MTD at each dose level.
`n.patients`	the average number of patients dosed at each level.
`dlt`	the average number of DLTs experienced at each dose level.
`truep`	input; true probabilities of toxicity.
`start.level`	input; starting dose level.
`nsim`	input; number of simulated trails.

Wenchuan Guo <wguo1017@gmail.com>

truep <- c(0.3, 0.45, 0.5, 0.6)
res <- dec.table(0.6,0.4,0.2,0.3,c(3,3,3))
out <- dec.sim(truep, res$table, start.level = 2, nsim = 1000)
summary(out, pt = 0.3)