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Documentation Index

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This project provides a fully reproducible statistical analysis pipeline for investigating the global prevalence of inappropriate acid suppressing agent (ASA) use — including proton pump inhibitors (PPIs) and H2-receptor antagonists. Using the targets framework in R, the pipeline orchestrates data cleaning, pooled meta-analysis, subgroup analyses, meta-regression, and publication bias assessment, culminating in an automated Quarto report.

Introduction

Understand the research context, study design, and key variables behind the meta-analysis.

Quickstart

Set up the environment and run the full analysis pipeline in minutes.

Pipeline Overview

Explore how the targets pipeline orchestrates every step from raw data to final report.

Analysis Methods

Learn the statistical methods: random-effects models, subgroup analyses, and meta-regression.

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What this pipeline does

The analysis investigates how frequently acid suppressing agents are prescribed without appropriate clinical indication across global studies. Seven in ten prescriptions globally were found to be inappropriate, with substantial heterogeneity across settings, geographies, and guideline definitions.

Pooled Prevalence

Random-effects meta-analysis using the Freeman-Tukey double arcsine transformation.

Subgroup Analysis

Stratified analyses by age, continent, clinical setting, study quality, and guideline use.

Meta-Regression

Univariable and multivariable models exploring sources of between-study heterogeneity.

Publication Bias

Copas selection model and Doi plots for sensitive publication bias assessment.

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Getting started

1

Install prerequisites

Install R, Quarto, and optionally RStudio. Then install tinytex for PDF rendering:
quarto tools install tinytex
2

Restore R environment

Install renv and restore all required packages from the lockfile:
install.packages("renv")
renv::restore()
3

Add your data

Export the study-level data as data.csv and place it at data/raw/data.csv.
4

Run the pipeline

Execute the full targets pipeline to reproduce all analyses and generate the report:
targets::tar_make()
After running renv::restore(), restart your R session before proceeding to ensure all packages are loaded correctly.

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