In ielbadisy/CEACT: Cost-Effectiveness Analysis Toolkit for Clinical Trials

Overview

CEACT (Cost-Effectiveness Analysis for Clinical Trials) is an R package designed to facilitate the economic evaluation of healthcare interventions in randomized trials. It offers a suite of functions for estimating and visualizing core cost-effectiveness metrics, including:

• Incremental Cost-Effectiveness Ratios (ICER),
• Cost-effectiveness planes,
• Cost-effectiveness acceptability curves (CEAC),
• Net monetary benefit (NMB) metrics.

CEACT is built using a formula-friendly, tidyverse-inspired interface to streamline analysis workflows.

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Installation

# Install from GitHub using devtools
# install.packages("devtools")
#devtools::install_github("ielbadisy/CEACT")
library(CEACT)

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Key Features

• cea(): Estimate ICER and generate a descriptive cost-effectiveness summary.
• boot_icer(): Perform bootstrap-based uncertainty analysis for ICER.
• plot_ceplane(): Visualize the cost-effectiveness plane with optional quadrant breakdown.
• plot_ceac(): Plot the cost-effectiveness acceptability curve.
• compute_nmb_ceac(): Compute expected NMB and probability of cost-effectiveness across WTP values.

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Example Usage

Simulate Trial Data

set.seed(123)

control <- data.frame(
  cost = rnorm(200, 500, 100),
  effect = rnorm(200, 0.4, 0.05),
  group = "control"
)

treatment <- data.frame(
  cost = rnorm(200, 550, 100),
  effect = rnorm(200, 0.3, 0.06),
  group = "treatment"
)

df <- rbind(control, treatment)

Run Cost-Effectiveness Analysis

res_cea <- CEACT::cea(cost + effect ~ group, data = df, ref = "control")
summary(res_cea)

Bootstrap the ICER

res_boot <- CEACT::boot_icer(cost + effect ~ group, data = df, ref = "control", R = 300)
summary(res_boot)

Visualize the Cost-Effectiveness Plane

CEACT::plot_ceplane(res_boot, k = 1000)

Plot the CEAC

CEACT::plot_ceac(res_boot, wtp_range = seq(0, 20000, 1000))

Compute NMB and CEAC Table

nmb_table <- CEACT::compute_nmb_ceac(cost + effect ~ 1, data = df, wtp_range = seq(0, 20000, 1000))
head(nmb_table)

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Feedback & Contributions

We welcome feedback, issues, and pull requests.
Contribute via the GitHub Issues page.

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TODO

• [x] Formula-based interface across all functions
• [x] Optional quadrant labels in CE plane
• [x] Improved p-value formatting
• [x] Complete function-level documentation using roxygen2
• [x] Fix warnings and notes
• [ ] Add unit tests using testthat
• [ ] Create a PDF vignette (theory + practical examples)
• [ ] Write a comprehensive tutorial (or use-case article ?)
• [ ] Submit to CRAN

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ielbadisy/CEACT documentation built on June 11, 2025, 9:19 p.m.