Type: Package
Title: Using Historical Controls for Designing Phase II Clinical Trials
Version: 0.1.0
Description: Provides functions for designing phase II clinical trials adjusting for the heterogeneity of the population using known subgroups or historical controls.
Depends: R (≥ 3.5.0)
License: GPL-2 | GPL-3
LazyData: TRUE
RoxygenNote: 6.1.1
Imports: clinfun, GenBinomApps, stats
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-12-12 08:06:44 UTC; edelmand
Author: Dominic Edelmann [aut, cre]
Maintainer: Dominic Edelmann <dominic.edelmann@dkfz-heidelberg.de>
Repository: CRAN
Date/Publication: 2018-12-21 15:20:06 UTC

hctrial: A package for designing phase 2 clinical trials adjusting for heterogeneous populations.

Description

The hctrial package provides functions for designing phase 2 clinical trials that adjust for the heterogeneity in the population.

Details

Two different ways are considered for designing a trial: based on known subgroups or based on historical data.

For initializing a stratified trial, use strat_start.

At interim, strat_interim should be used to adjust the trial.

At the end of the study, strat_end is used to adjust the trial again.

hist_start, hist_interim and hist_end work analogously, but are based on historical controls.

Adjust a design based on historical controls at the end of the study using the covariate data of the patients accrued in stage 2.

Description

Adjust a design based on historical controls at the end of the study using the covariate data of the patients accrued in stage 2.

Usage

hist_end(interim, stagetwo_data)

Arguments

interim

An design based on historical controls and adjusted at interim as returned by hist_interim().

stagetwo_data

A dataframe containing the relevant covariate data of the patients accrued in stage 2.

Value

A list returning the arguments of the function and the final design of the trial.

Examples

X <- abs(rnorm(1000, 0, 1))
Y <- rbinom(1000, 1, 1-exp(-X))
mydata <- data.frame("X" = X, "Y" = Y)
start <- hist_start(mydata, Y~X, c1 = 2)
n1 <- start$des_start[2]
X1 <- abs(rnorm(n1, 0, 1))
dataone <- data.frame("X" = X1)
interim <- hist_interim(start, dataone)
n2 <- interim$des_interim[4]
X2 <- abs(rnorm(n2, 0, 1))
datatwo <- data.frame("X" = X2)
hist_end(interim, datatwo)

Adjust a design based on historical controls at interim using the covariate data of the patients accrued in stage 1.

Description

Adjust a design based on historical controls at interim using the covariate data of the patients accrued in stage 1.

Usage

hist_interim(start, stageone_data)

Arguments

start

An initialized design based on historical controls as returned by hist_start().

stageone_data

A dataframe containing the relevant covariate data of the patients accrued in stage 1.

Value

A list returning the arguments of the function and the preliminary design of a trial based on historical controls adjusted at interim.

Examples

X <- abs(rnorm(1000, 0, 1))
Y <- rbinom(1000, 1, 1-exp(-X))
mydata <- data.frame("X" = X, "Y" = Y)
start <- hist_start(mydata, Y~X, c1 = 2)
n1 <- start$des_start[2]
X1 <- abs(rnorm(n1, 0, 1))
dataone <- data.frame("X" = X1)
hist_interim(start, dataone)

Initializes a design based on historical controls before the start of the study.

Description

Initializes a design based on historical controls before the start of the study.

Usage

hist_start(hist_data, formula, phi = "odds_ratio", c1, modelfit = NULL,
  mean0 = NULL, mean1 = NULL, alpha = 0.05, beta = 0.2)

Arguments

hist_data

A data frame containing covariates and binary responses for historical controls.

formula

A formula which is used for fitting a logistic regression model on the historical data.

phi

The relation between the response rate under the null and the response rate under the interesting alternative. "odds_ratio" assumes that the odds ratio (OR) between these response rates is constant with OR = c1+1. "difference" assumes that the response rate under the alternative is c1 higher than under the null. Can also be specified by the user by providing a function with arguments c and x.

c1

parameter for obtaining the response rate under the alternative, see description of phi.

modelfit

Can be used instead of formula and hist_data to provide an arbitrary fitted model that is compatible with predict(modelfit, type="response"). formula and hist_data are ignored if modelfit is specified.

mean0

Optional: Can be used to overwrite the estimated average response rate under the null of the fitted model.

mean1

Optional: Can be used to overwrite the estimated average response rate under the alternative of the fitted model.

alpha

Specified type I error of the trial.

beta

Specified type II error of the trial.

Value

A list returning the arguments of the function and the preliminary design for starting the stratified trial.

Examples

X <- abs(rnorm(1000, 0, 1))
Y <- rbinom(1000, 1, 1-exp(-X))
mydata <- data.frame("X" = X, "Y" = Y)
hist_start(mydata, Y~X, c1 = 2)

Adjust a subspace stratified design at the end of the study.

Description

Adjust a subspace stratified design at the end of the study.

Usage

strat_end(interim, sub_stagetwo)

Arguments

interim

A preliminary stratified design adjusted at interim as returned by strat_interim().

sub_stagetwo

The subtypes observed for the patients accrued in stage 2.

Value

A list returning the arguments of the function and the final design of the stratified trial.

Examples

p0_sub <- c(0.1, 0.3, 0.5)
p1_sub <- c(0.3, 0.5, 0.7)
distr_sub <- c(1/3, 1/3, 1/3)
start <- strat_start(p0_sub, p1_sub, distr_sub)
n1 <- start$des_start[2]
subone <- sample(c(1,2,3), n1, TRUE)
interim <- strat_interim(start, subone)
n2 <- interim$des_interim[4]
subtwo <- sample(c(1,2,3), n2, TRUE)
strat_end(interim, subtwo)

Adjust a subspace stratified design at interim.

Description

Adjust a subspace stratified design at interim.

Usage

strat_interim(start, sub_stageone)

Arguments

start

An initialized stratified design as returned by strat_start().

sub_stageone

The subtypes observed for the patients accrued in stage 1.

Value

A list returning the arguments of the function and the preliminary design of a stratified trial adjusted at interim.

Examples

p0_sub <- c(0.1, 0.3, 0.5)
p1_sub <- c(0.3, 0.5, 0.7)
distr_sub <- c(1/3, 1/3, 1/3)
start <- strat_start(p0_sub, p1_sub, distr_sub)
n1 <- start$des_start[2]
subone <- sample(c(1,2,3), n1, TRUE)
strat_interim(start, subone)

Initializes a subspace stratified design before the start of the study.

Description

Initializes a subspace stratified design before the start of the study.

Usage

strat_start(p0_sub, p1_sub, distr_sub, alpha = 0.05, beta = 0.2)

Arguments

p0_sub

A vector, where the $i$-th entry corresponds to the response rate under the null for the $i$-th subtype.

p1_sub

A vector, where the $i$-th entry corresponds to the response rate under the alternative for the $i$-th subtype.

distr_sub

A vector, where the $i$-th entry corresponds to the prevalence of the $i$-th subtype in the population.

alpha

Specified type I error of the trial.

beta

Specified type II error of the trial.

Value

A list returning the arguments of the function and the preliminary design for starting the stratified trial.

Examples

p0_sub <- c(0.1, 0.3, 0.5)
p1_sub <- c(0.3, 0.5, 0.7)
distr_sub <- c(1/3, 1/3, 1/3)
strat_start(p0_sub, p1_sub, distr_sub)