drugdevelopR (version 1.0.2)

EPsProg23: Expected probability of a successful program deciding between two or three phase III trials in a time-to-event setting

Description

The function EPsProg23() calculates the expected probability of a successful program in a time-to-event setting. This function follows a special decision rule in order to determine whether two or three phase III trials should be conducted. First, two phase III trials are performed. Depending on their success, the decision for a third phase III trial is made:

• If both trials are successful, no third phase III trial will be conducted.

• If only one of the two trials is successful and the other trial has a treatment effect that points in the same direction, a third phase III trial will be conducted with a sample size of N3 = N3(ymin), which depends on an assumed minimal clinical relevant effect (ymin). The third trial then has to be significant at level alpha

• If only one of the two trials is successful and the treatment effect of the other points in opposite direction or if none of the two trials are successful, then no third trial is performed and the drug development development program is not successful. In the utility function, this will lead to a utility of -9999.

Usage

EPsProg23(HRgo, d2, alpha, beta, w, hr1, hr2, id1, id2, case, size, ymin)

Value

The output of the function EPsProg23() is the expected probability of a successful program.

Arguments

HRgo

threshold value for the go/no-go decision rule

d2

total number of events in phase II

alpha

significance level

beta

1-beta power for calculation of sample size for phase III

w

weight for mixture prior distribution

hr1

first assumed true treatment effect on HR scale for prior distribution

hr2

second assumed true treatment effect on HR scale for prior distribution

id1

amount of information for hr1 in terms of number of events

id2

amount of information for hr2 in terms of number of events

case

choose case: "at least 1, 2 or 3 significant trials needed for approval"

size

size category "small", "medium" or "large"

ymin

assumed minimal clinical relevant effect

Examples

res <- EPsProg23(HRgo = 0.8, d2 = 50,  alpha = 0.025, beta = 0.1, 
                                  w = 0.3, hr1 =  0.69, hr2 = 0.81, 
                                  id1 = 280, id2 = 420, case = 2, size = "small",
                                  ymin = 0.5)