utility_multitrial: Utility function for multitrial programs in a time-to-event...

In Sterniii3/drugdevelopR: Utility-Based Optimal Phase II/III Drug Development Planning

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 hr1 in terms of number of events
id2	amount of information for hr2 in terms of number of events
alpha	significance level
beta	1-beta power for calculation of sample size for phase III
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 "small"
b2	expected gain for effect size category "medium"
b3	expected gain for effect size category "large"
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)

Sterniii3/drugdevelopR documentation built on Jan. 26, 2024, 6:17 a.m.