utility23 {drugdevelopR} | R Documentation |
Utility function for multitrial programs deciding between two or three phase III trials in a time-to-event setting
Description
The utility function calculates the expected utility of our drug development program and is given as gains minus costs and depends on the parameters and the expected probability of a successful program.
The utility is in further step maximized by the optimal_multitrial()
function.
Usage
utility23(
d2,
HRgo,
w,
hr1,
hr2,
id1,
id2,
alpha,
beta,
xi2,
xi3,
c2,
c3,
c02,
c03,
b1,
b2,
b3
)
Arguments
d2 |
total sample size for phase II; must be even number |
HRgo |
threshold value for the go/no-go decision rule |
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 |
id2 |
amount of information for |
alpha |
significance level |
beta |
|
xi2 |
event rate for phase II |
xi3 |
event rate for phase III |
c2 |
variable per-patient cost for phase II |
c3 |
variable per-patient cost for phase III |
c02 |
fixed cost for phase II |
c03 |
fixed cost for phase III |
b1 |
expected gain for effect size category |
b2 |
expected gain for effect size category |
b3 |
expected gain for effect size category |
Value
The output of the function utility23()
is the expected utility of the program depending on whether two or three phase III trials are performed.
Examples
utility23(d2 = 50, HRgo = 0.8, w = 0.3,
hr1 = 0.69, hr2 = 0.81,
id1 = 280, id2 = 420,
alpha = 0.025, beta = 0.1, xi2 = 0.7, xi3 = 0.7,
c2 = 0.75, c3 = 1, c02 = 100, c03 = 150,
b1 = 1000, b2 = 2000, b3 = 3000)