optimal_tte_generic: Generic function for optimal planning of time-to-event...

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

Generic function for optimal planning of time-to-event endpoints

Description

Generic function for optimal planning of time-to-event endpoints

Usage

optimal_tte_generic(
  w,
  hr1,
  hr2,
  id1,
  id2,
  d2min,
  d2max,
  stepd2,
  hrgomin,
  hrgomax,
  stephrgo,
  alpha,
  beta,
  xi2,
  xi3,
  c2,
  c3,
  c02,
  c03,
  K = Inf,
  N = Inf,
  S = -Inf,
  steps1 = 1,
  stepm1 = 0.95,
  stepl1 = 0.85,
  b1,
  b2,
  b3,
  gamma = 0,
  fixed = FALSE,
  num_cl = 1
)

Arguments

w	weight for mixture prior distribution, see this Shiny application for the choice of weights
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
d2min	minimal number of events for phase II
d2max	maximal number of events for phase II
stepd2	step size for the optimization over d2
hrgomin	minimal threshold value for the go/no-go decision rule
hrgomax	maximal threshold value for the go/no-go decision rule
stephrgo	step size for the optimization over HRgo
alpha	one-sided significance level
beta	type II error rate; i.e. 1 - beta is the power for calculation of the number of events for phase III by Schoenfeld's formula (Schoenfeld 1981)
xi2	assumed event rate for phase II, used for calculating the sample size of phase II via n2 = d2/xi2
xi3	event rate for phase III, used for calculating the sample size of phase III in analogy to xi2
c2	variable per-patient cost for phase II in 10^5 $.
c3	variable per-patient cost for phase III in 10^5 $.
c02	fixed cost for phase II in 10^5 $.
c03	fixed cost for phase III in 10^5 $.
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 HR scale, default: 0.95
stepl1	lower boundary for effect size category "large" in HR scale = upper boundary for effect size category "medium" in HR 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"
gamma	to model different populations in phase II and III choose gamma != 0, default: 0
fixed	choose if true treatment effects are fixed or random, if TRUE hr1 is used as a fixed effect and hr2 is ignored
num_cl	number of clusters used for parallel computing, default: 1

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