drugdevelopR (version 1.0.2)

utility_multiarm: Utility function for multiarm programs with time-to-event outcomes

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 as on the sample size and expected probability of a successful program. The utility is in further step maximized by the optimal_multiarm() function.

Usage

utility_multiarm(
  n2,
  HRgo,
  alpha,
  beta,
  hr1,
  hr2,
  strategy,
  ec,
  c2,
  c02,
  c3,
  c03,
  K,
  N,
  S,
  steps1,
  stepm1,
  stepl1,
  b1,
  b2,
  b3
)

Value

The output of the function utility_multiarm() is the expected utility of the program

Arguments

n2

total sample size for phase II; must be divisible by three

HRgo

threshold value for the go/no-go decision rule

alpha

significance level

beta

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

hr1

assumed true treatment effect on HR scale for treatment 1

hr2

assumed true treatment effect on HR scale for treatment 2

strategy

choose Strategy: 1 ("only best promising"), 2 ("all promising")

ec

control arm event rate for phase II and III

c2

variable per-patient cost for phase II

c02

fixed cost for phase II

c3

variable per-patient cost for phase III

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

steps1

lower boundary for effect size category "small" in HR scale, default: 1

stepm1

lower boundary for effect size category "medium" in HR scale = upper boundary for effect size category "small" in RR scale, default: 0.95

stepl1

lower boundary for effect size category "large" in HR scale = upper boundary for effect size category "medium" in RR scale, default: 0.85

b1

expected gain for effect size category "small"

b2

expected gain for effect size category "medium"

b3

expected gain for effect size category "large"

Examples

utility_multiarm(n2 = 50, HRgo = 0.8, alpha = 0.05, beta = 0.1,
                            hr1 = 0.7, hr2 = 0.8, strategy = 2, ec = 0.6,
                            c2 = 0.75, c3 = 1, c02 = 100, c03 = 150,
                            K = Inf, N = Inf, S = -Inf,  
                            steps1 = 1, stepm1 = 0.95,  stepl1 = 0.85,
                            b1 = 1000, b2 = 2000, b3 = 3000)