utility_multiarm_binary: Utility function for multiarm programs with binary...

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

Utility function for multiarm programs with binary distributed 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_binary() function.

Usage

utility_multiarm_binary(
  n2,
  RRgo,
  alpha,
  beta,
  p0 = p0,
  p11 = p11,
  p12 = p12,
  strategy,
  c2,
  c02,
  c3,
  c03,
  K,
  N,
  S,
  steps1,
  stepm1,
  stepl1,
  b1,
  b2,
  b3
)

Arguments

n2	total sample size for phase II; must be even number
RRgo	threshold value for the go/no-go decision rule
alpha	significance level
beta	1-beta power for calculation of sample size for phase III
p0	assumed true rate of control group
p11	assumed true rate of treatment group
p12	assumed true rate of treatment group
strategy	choose Strategy: 1 ("only best promising"), 2 ("all promising")
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 RR scale, default: 1
stepm1	lower boundary for effect size category "medium" in RR scale = upper boundary for effect size category "small" in RR scale, default: 0.95
stepl1	lower boundary for effect size category "large" in RR 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"

Value

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

Examples

res <- utility_multiarm_binary(n2 = 50, RRgo = 0.8, alpha = 0.05, beta = 0.1,
                            p0 = 0.6, p11 =  0.3, p12 = 0.5, strategy = 1,
                            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)

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