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WCRBayesDesign

Bayesian Two-Stage Adaptive Design for Single-Arm Survival Trials

Overview

WCRBayesDesign provides simulation and optimization tools for Bayesian two-stage adaptive single-arm trials with time-to-event endpoints. All statistical calculations are carried out in a transformed-time space induced by a reference survival function \(S_0\), while key results are reported on the original time scale for clinical interpretability.

Installation

# Install from source
install.packages("WCRBayesDesign_1.0.0.tar.gz", repos = NULL, type = "source")

Quick Start

library(WCRBayesDesign)

# Step 1 - Search feasible interim-analysis parameters
res_pIA <- find_Nw_pIA(
  tau = 24, theta_L = 0.62, theta_alt = 0.80,
  alpha_target = 0.05, beta_target = 0.20,
  rate = 5/12, X_grid = c(1, 2, 3),
  S0_dist = "weibull",
  S0_par = list(k = 1.2, lambda = 0.08)
)

# Step 2 - Optimise the two-stage design
opt <- two_stage_optimize_design(
  NwX_pIA_results = res_pIA,
  rate = 5/12, tau = 24,
  theta_L = 0.62, theta_alt = 0.80,
  alpha_target = 0.05, beta_target = 0.20,
  nsim = 2000,
  S0_dist = "weibull",
  S0_par = list(k = 1.2, lambda = 0.08),
  optimize = "ESS", ncores = 4
)

# Step 3 - Evaluate operating characteristics
oc <- oc_two_stage(
  N = 50, Nw = 30, X = 2,
  pIA = 0.5, pF = 0.05,
  rate = 5/12, tau = 24,
  theta_L = 0.62, theta_alt = 0.80,
  a0 = 0.01, b0 = 0.01, nsim = 5000,
  S0_dist = "weibull",
  S0_par = list(k = 1.2, lambda = 0.08)
)

Exported Functions

Function	Purpose
`find_Nw_pIA()`	Search for feasible interim-analysis parameters
`two_stage_optimize_design()`	Optimise sample size and decision thresholds
`oc_two_stage()`	Evaluate operating characteristics via simulation
`run_two_stage_trial()`	Simulate a single two-stage trial
`conduct()`	Perform Bayesian interim or final analysis
`S0_weibull()`	Weibull reference survival function
`S0_inverse()`	Inverse baseline survival function
`delta_from_theta_goal()`	Convert survival-probability target to delta
`stats_transformed()`	Compute transformed sufficient statistics

Supported Baseline Distributions

Exponential (S0_dist = "exp")
Weibull (S0_dist = "weibull")
Log-normal (S0_dist = "lognormal")
Log-logistic (S0_dist = "loglogistic")
User-supplied (S0_dist = "custom")

License

GPL-3

Authors

Zhongheng Cai (maintainer) — zhonghengcai123@gmail.com
Haitao Pan — Haitao.Pan@STJUDE.ORG

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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