select.mtd.comb.kb {Keyboard}

Maximum Tolerated Dose (MTD) Selection for Drug-combination Trials

Description

This function selects the maximum tolerated dose (MTD) after the drug-combination trial is completed.

Usage

select.mtd.comb.kb(
  target,
  npts,
  ntox,
  cutoff.eli = 0.95,
  extrasafe = FALSE,
  offset = 0.05
)

Arguments

target

The target dose-limiting toxicity (DLT) 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 who experienced a dose-limiting toxicity at each dose combination.

cutoff.eli

The cutoff value to eliminate an overly toxic dose and all higher doses for safety.
The default value is 0.95.

extrasafe

Set extrasafe=TRUE to impose a stricter stopping rule.
The default is FALSE.

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 stricter stopping rule.
The default value is 0.05.

Details

The Keyboard design starts by specifying a target toxicity interval (referred to as the "target key") such that any dose with a toxicity probability within that interval can be practically viewed as the MTD. Based on this interval's width, the Keyboard design forms a series of equally wide keys that span the rest of the range from 0 to 1.

Given all the observed data once the trial is completed, this function selects the MTD based on matrix isotonic estimates of the toxicity probability of each dose combination, selecting the dose whose estimate is closest to the target. When there are ties, one is randomly chosen. These (matrix) isotonic estimates are obtained with biviso.

For patient safety, the following dose elimination rule is evaluated after each cohort: if at least 3 patients have been treated at the given dose and the observed data indicate that there is more than a 95% chance that the current dose is above the MTD, then we eliminate this dose and beyond from the trial to prevent exposing future patients to these overly toxic doses. The probability threshold for elimination can be specified with cutoff.eli. When a dose is eliminated, the design recommends the next lower dose for treating the next patient. If the lowest dose combination (1, 1) is overly toxic, then the trial terminates early and no dose is selected as the MTD.

For some applications, investigators may prefer a stricter stopping rule for extra safety when the lowest dose is overly toxic. This can be achieved by setting extrasafe=TRUE, which imposes the following stricter safety stopping rule:
Stop the trial if
(i) the number of patients treated at the lowest dose \ge 3, and
(ii)

Pr[(toxicity rate of the lowest dose > target) | data)] > cutoff.eli - offset

As a tradeoff, the strong stopping rule will decrease the MTD selection percentage when the lowest dose is the true MTD.

Value

The function returns a list with:

1. the target toxicity probability ($target),
   

2. the selected MTD ($MTD),
   

3. a matrix with the isotonic estimates of the DLT probability at each dose ($p_est).

Uses

This function uses biviso.

Note

The MTD selection and dose escalation/de-escalation rules are two independent components of the trial design. When appropriate, another dose selection procedure (e.g., one based on a fitted logistic model) can be used to select the MTD after completing the trial using the Keyboard design.

Author(s)

Xiaomeng Yuan, Chen Li, Hongying Sun, Li Tang and Haitao Pan

References

Yan F, Mandrekar SJ, Yuan Y. Keyboard: A Novel Bayesian Toxicity Probability Interval Design for Phase I Clinical Trials. Clinical Cancer Research. 2017; 23:3994-4003. http://clincancerres.aacrjournals.org/content/23/15/3994.full-text.pdf

Pan H, Lin R, Yuan Y. Keyboard design for phase I drug-combination trials. Contemporary Clinical Trials. 2020. https://doi.org/10.1016/j.cct.2020.105972

See Also

Other drug-combination functions: get.boundary.comb.kb(), get.oc.comb.kb(), next.comb.kb()

Examples

### Drug-combination trial ###

## Select the MTD based on the data from a 3 x 5 combination trial
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.kb(target=0.3, npts=n, ntox=y)

summary_kb(sel.comb)
plot_kb(sel.comb)