sim_magnusson_turnbull: Simulations of trials with GSED

In GSED: Group Sequential Enrichment Design

Simulations of trials with GSED

Description

sim_magnusson_turnbull is used to simulate clincal trials with GSED for different type of outcome (survival, binary, continuous).

Usage

sim_magnusson_turnbull(K_stages, N_subsets, f, l, u, ratio_Delta_star_d1, type_outcome, 
param_outcome=NA, n_max=NA, incl_rate=NA, mean_cur_c=NA, HR=NA, nb_required=NA, 
nmax_wait=+Inf, ordering, increasing_theta=FALSE, nsim=1000, seed=42,
nsim_tot=NA, num_sc=1, updateProgress=NULL)

Arguments

K_stages	Integer indicating the number of stages in the design.
N_subsets	Integer representing the number of possible subgroups.
f	Vector containing the prevalence rates of each subgroup. Must be of length N_subsets.
l	Vector containing the lower boundaries for stagewise decisions. Must be of length K_stages.
u	Vector containing the upper boundaries for stagewise decisions. Must be of length K_stages.
ratio_Delta_star_d1	Vector containing the ratio between the (observed Fisher) information increments at each stage >1 with the (observed Fisher) information at stage 1. Must be of length K_stages-1.
type_outcome	A string containing the type of outcome, either "survival", "binary", or "continuous".
param_outcome	Must be supplied only if type_outcome is equal to "binary" or "continuous". The parameters supplied for the binary outcome must be a list of one element containing a matrix of size 2xN_subsets. The parameters supplied for the continuous outcome must be a list of two elements containing two matrices of size 2xN_subsets. The matrices should contain probabilities of response, or the means and variances respectively, for in row control or treatment, and in column the subgroup number.
n_max	Integer representing the maximum number of patients to enroll in a trial. Must be supplied only if type_outcome is equal to "binary" or "continuous", will be ignored otherwise.
incl_rate	Number representing the inclusion rate. Must be supplied only if type_outcome is equal to "survival", will be ignored otherwise.
mean_cur_c	Number representing the median survival for the control group. Must be supplied only if type_outcome is equal to "survival", will be ignored otherwise.
HR	Vector containing the expected hazard ratios for each subgroup. Must be of length N_subsets. Must be supplied only if type_outcome is equal to "survival", will be ignored otherwise.
nb_required	Integer indicating the maximum number of events required. Must be supplied only if type_outcome is equal to "survival", will be ignored otherwise.
nmax_wait	For type_outcome equal to "survival" only, will be ignored otherwise. If specified, maximum number of patients to include in the trial, the inclusions will be stopped when this number is achieved and trial will pursue until the number of events required is achieved. Must be superior to nb_required. Default value is +Inf.
ordering	Boolean indicating if the subgroups (theta) are ordered.
increasing_theta	Boolean indicating if greater values of theta parameters represent better treatment effects. The default value is set at FALSE.
nsim	Integer indicating the number of trials to simulate. The default value is set at 1000.
seed	Interger representing the seed. The default value is set at 42.
nsim_tot	(for Rshiny application)
num_sc	(for Rshiny application)
updateProgress	(for Rshiny application)

Value

A list is returned composed of:

prob_rejec	Percentage of simulated trials (estimated probability) to reject any subgroup.
prob_accep	Percentage of simulated trials (estimated probability) to accept the null hypothesis, that is there is no treatment effect in any subgroup.
list_keep	A list of the different subgroups that were selected across all simulated trials.
pct_keep	Percentage of selection of each subgroup of list_keep across all simulated trials.
rejec_stage	Vector of percentage of simulated trials (estimated probability) to reject any subgroup at each stage.
accep_stage	Vector of percentage of simulated trials (estimated probability) to accept the null hypothesis (that is there is no treatment effect in any subgroup) at each stage.
mean_pat	Mean number of patients included across all simulated trials.
mean_duration	If type_outcome is equal to "survival", the trial mean duration across all simulated trials is also returned.

Author(s)

Marie-Karelle Riviere-Jourdan [e-mail]

References

Baldur P. Magnusson and Bruce W. Turnbull. Group sequential enrichment design incorporating subgroup selection. Statistics in Medicine, 2013. <doi:10.1002/sim.5738>

Examples

#For testing purpose only, larger number of simulations required (see in comments below)
sim_magnusson_turnbull(K_stages=2, N_subsets=3, f=c(0.6,0.2,0.2), l=c(0.7962, 2.5204), 
u=c(2.7625, 2.5204), ratio_Delta_star_d1=c(1), type_outcome="binary", param_outcome=
list(matrix(c(0.4,0.4,0.4,0.6,0.6,0.6),nrow=2,ncol=3,byrow=TRUE)), n_max=1496, 
ordering=FALSE, nsim=2, seed=42)

#sim_magnusson_turnbull(K_stages=2, N_subsets=3, f=c(0.6,0.2,0.2), l=c(0.7962, 2.5204), 
#u=c(2.7625, 2.5204), ratio_Delta_star_d1=c(1), type_outcome="binary", param_outcome=
#list(matrix(c(0.4,0.4,0.4,0.6,0.6,0.6),nrow=2,ncol=3,byrow=TRUE)), n_max=1496, 
#ordering=FALSE, nsim=1000, seed=42)

#sim_magnusson_turnbull(K_stages=2, N_subsets=3, f=c(0.6,0.2,0.2), l=c(0.7962, 2.5204), 
#u=c(2.7625, 2.5204), ratio_Delta_star_d1=c(1), type_outcome="binary", param_outcome=
#list(matrix(c(0.5,0.5,0.5,0.5,0.5,0.5),nrow=2,ncol=3,byrow=TRUE)), n_max=1496, 
#ordering=FALSE, nsim=1000, seed=42)

#sim_magnusson_turnbull(K_stages=2, N_subsets=4, f=c(0.25,0.25,0.25,0.25), l=c(0.98,2.35), 
#u=c(2.59,2.35), ratio_Delta_star_d1=c(1), type_outcome="survival", incl_rate=1/28, 
#mean_cur_c=7/log(2), HR=c(0.8,0.8,0.8,0.8), nb_required=1030, ordering=TRUE, 
#increasing_theta=FALSE, nsim=1000, seed=42)

GSED documentation built on Aug. 31, 2023, 5:06 p.m.