utility_multitrial {drugdevelopR} | R Documentation |
Utility function for multitrial programs 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
utility2(
d2,
HRgo,
w,
hr1,
hr2,
id1,
id2,
alpha,
beta,
xi2,
xi3,
c2,
c3,
c02,
c03,
K,
N,
S,
b1,
b2,
b3,
case,
fixed
)
utility3(
d2,
HRgo,
w,
hr1,
hr2,
id1,
id2,
alpha,
beta,
xi2,
xi3,
c2,
c3,
c02,
c03,
K,
N,
S,
b1,
b2,
b3,
case,
fixed
)
utility4(
d2,
HRgo,
w,
hr1,
hr2,
id1,
id2,
alpha,
beta,
xi2,
xi3,
c2,
c3,
c02,
c03,
K,
N,
S,
b1,
b2,
b3,
case,
fixed
)
Arguments
d2 |
total number of events in phase II |
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 |
K |
constraint on the costs of the program, default: Inf, e.g. no constraint |
N |
constraint on the total expected sample size of the program, default: Inf, e.g. no constraint |
S |
constraint on the expected probability of a successful program, default: -Inf, e.g. no constraint |
b1 |
expected gain for effect size category |
b2 |
expected gain for effect size category |
b3 |
expected gain for effect size category |
case |
choose case: "at least 1, 2 or 3 significant trials needed for approval" |
fixed |
choose if true treatment effects are fixed or random |
Value
The output of the functions utility2()
, utility3()
and utility4()
is the expected utility of the program when 2, 3 or 4 phase III trials are performed.
Examples
res <- utility2(d2 = 50, HRgo = 0.8, w = 0.3,
hr1 = 0.69, hr2 = 0.81,
id1 = 210, id2 = 420,
alpha = 0.025, beta = 0.1, xi2 = 0.7, xi3 = 0.7,
c2 = 0.75, c3 = 1, c02 = 100, c03 = 150,
K = Inf, N = Inf, S = -Inf,
b1 = 1000, b2 = 2000, b3 = 3000,
case = 2, fixed = TRUE)
res <- utility3(d2 = 50, HRgo = 0.8, w = 0.3,
hr1 = 0.69, hr2 = 0.81,
id1 = 210, id2 = 420,
alpha = 0.025, beta = 0.1, xi2 = 0.7, xi3 = 0.7,
c2 = 0.75, c3 = 1, c02 = 100, c03 = 150,
K = Inf, N = Inf, S = -Inf,
b1 = 1000, b2 = 2000, b3 = 3000,
case = 2, fixed = TRUE)
res <- utility4(d2 = 50, HRgo = 0.8, w = 0.3,
hr1 = 0.69, hr2 = 0.81,
id1 = 210, id2 = 420,
alpha = 0.025, beta = 0.1, xi2 = 0.7, xi3 = 0.7,
c2 = 0.75, c3 = 1, c02 = 100, c03 = 150,
K = Inf, N = Inf, S = -Inf,
b1 = 1000, b2 = 2000, b3 = 3000,
case = 3, fixed = TRUE)