dfcomb (version 2.0-2)

CombPlateau_next: Combination determination for the combination of two agents where toxicity is increasing with the dose of both agent and efficacy is increasing and possibly plateaus with the dose of one agent

Description

CombPlateau_next is used to determine the next or recommended combination in a phase I/II clinical trial for combination studies where the toxicity is assumed to increase with the dose of both agents, and the efficacy is asummed to increase with one agent and increase and possibily plateaus with the second agent. This phase I/II adaptive design is performed using the design proposed by Riviere et al. entitled "A Bayesian dose finding design for clinical trials combining a cytotoxic agent with a molecularly targeted agent".

Usage

CombPlateau_next(ndose_a1, ndose_a2, tox_max, eff_min, prior_tox_a1, 
prior_tox_a2, prior_eff_a1, prior_eff_a2, stage, in_startup, cohort_start=3, 
cohort, pat_incl, dose_adm1, dose_adm2, toxicity, time_full, time_prog, 
time_follow, cycle=0, c_tox=0.85, c_eff=0.10)

Arguments

ndose_a1

Number of dose levels for agent 1.

ndose_a2

Number of dose levels for agent 2.

tox_max

Maximum acceptable toxicity probability.

eff_min

Minimum efficacy probability desired.

prior_tox_a1

A vector of initial guesses of toxicity probabilities associated with the doses of agent 1. Must be of length ndose_a1.

prior_tox_a2

A vector of initial guesses of toxicity probabilities associated with the doses of agent 2. Must be of length ndose_a2.

prior_eff_a1

A vector of initial guesses of efficacy probabilities associated with the doses of agent 1. Must be of length ndose_a1.

prior_eff_a2

A vector of initial guesses of efficacy probabilities associated with the doses of agent 2. Must be of length ndose_a2.

stage

A integer with value 0 if less than half of the total sample size have been included, 1 if more than half of the total sample size have been included but the trial is still on-going, and 2 if the trial is over and dose recommendation should be done.

in_startup

TRUE if the start-up was not ended, FALSE otherwise.

cohort_start

Cohort size for the start-up phase. Default is set at 3.

cohort

Cohort size for the model-based phase.

pat_incl

Current number of patients included.

dose_adm1

A vector indicating the dose levels of agents 1 administered to each patient included in the trial. Must be of length pat_incl.

dose_adm2

A vector indicating the dose levels of agents 2 administered to each patient included in the trial. Must be of length pat_incl.

toxicity

A vector of observed toxicities (DLTs) for each patient included in the trial. Must be of length pat_incl.

time_full

Full follow-up time window for efficacy evaluation.

time_prog

A vector of times-to-progression for each patient included in the trial. If no progression (stability or efficacy) was observed for a patient, must be filled with +Inf. Must be of length pat_incl.

time_follow

A vector of follow-up times for each patient included in the trial. Must be of length pat_incl.

cycle

Minimum waiting time between two dose cohorts (usually a toxicity cycle). Default value is set at 0.

c_tox

Toxicity threshold for decision rules. The default value is set at 0.85.

c_eff

Efficacy threshold for decision rules. The default value is set at 0.10.

Value

• An object of class "CombPlateau_next" is returned, consisting of determination of the next combination and estimations. Objects generated by CombPlateau_next contain at least the following components:
• n_pat_comb
  Number of patients per combination.
• n_tox_comb
  Number of observed toxicities per combination.
• n_eff_comb
  Number of observed toxicities per combination.
• pi
  Estimated toxicity probabilities (if the start-up ended).
• ptox_sup
  Estimated probabilities that the toxicity probability is superior to tox_max (if the start-up ended).
• resp
  Estimated efficacy probabilities (if the start-up ended).
• qeff_min
  Estimated probabilities that the efficacy probability is superior to eff_min (if the start-up ended).
• proba_tau
  Estimated posterior probabilities for plateau location at each dose of agent 2 (if the start-up ended).
• startup_in
  Start-up phase is ended or not.
• (cdose1, cdose2)
  NEXT RECOMMENDED COMBINATION.
• cohort
  Cohort size.
• pat_incl
  Number of patients included.
• tox_max
  Toxicity upper bound.
• eff_min
  Efficacy lower bound.
• prior_tox_a1
  Prior toxicity probabilities for agent 1.
• prior_tox_a2
  Prior toxicity probabilities for agent 2.
• prior_eff_a1
  Prior efficacy probabilities for agent 1.
• prior_eff_a2
  Prior efficacy probabilities for agent 2.
• c_tox
  Tocixity threshold.
• c_eff
  Efficacy threshold.
• time_full
  Full follow-up time for efficacy is also reminded.

References

Riviere, M-K., Yuan, Y., Dubois, F., and Zohar, S. (2015). A Bayesian dose finding design for clinical trials combining a cytotoxic agent with a molecularly targeted agent. Journal of the Royal Statistical Society - Series C.

See Also

CombPlateau_sim.

Examples

prior_tox_a1 = c(0.2, 0.3, 0.4)
prior_eff_a1 = c(0.3, 0.4, 0.5)
prior_tox_a2 = c(0.12, 0.2, 0.3, 0.4)
prior_eff_a2 = c(0.3, 0.4, 0.5, 0.59)
toxicity = c(0,0,0,0,0,1,0,0,0,0,0,1,0,0,1,0,0,0)
dose1 = c(1,1,1,1,1,1,2,2,2,3,3,3,3,3,3,2,2,2)
dose2 = c(1,1,1,2,2,2,1,1,1,1,1,1,1,1,1,2,2,2)
t_prog = c(1.6,4.2,3.5,5.1,2.4,4.8,2.8,4.4,+Inf,3.9,+Inf,4.6,1.8,+Inf,0.5,5.4,2.8,+Inf)
follow = c(rep(7,15), 4.9, 3.1, 1.3)

next1 = CombPlateau_next(ndose_a1=3, ndose_a2=4, tox_max=0.30, eff_min=0.20, 
prior_tox_a1, prior_tox_a2, prior_eff_a1, prior_eff_a2, stage=0, in_startup=FALSE,
cohort=3, pat_incl=18, dose_adm1=dose1, dose_adm2=dose2, toxicity=toxicity, 
time_full=7, time_prog=t_prog, time_follow=follow)

next1