tflmetaR

Overview

tflmetaR provides a simple interface for retrieving titles, headers, and footnotes for tables, listings, and figures (TFLs) in clinical study reports (CSRs) or other formal deliverables from a metadata file.

Best practices in programming recommend separating code from metadata to improve readability, maintainability, and scalability. However, many R scripts used for clinical reporting still hardcode TFL annotations directly in the programs, making codebases difficult to manage and extend.

tflmetaR bridges this gap. Although independent and self-contained, it is compatible with the {gridify} and integrates with the Pharmaverse ecosystem for generating submission-ready statistical deliverables.

tflmetaR supports two workflows: a concise single-function interface and a more flexible helper-function workflow.

Installation

You can install the newest release version from CRAN:

install.packages("tflmetaR")

Metadata File

The metadata file can be an Excel file (.xlsx, .xls) or a CSV file (.csv), with standardized column names. Required columns are PGMNAME (program name), TTL1 (primary title), FOOT1 (first footnote), and SOURCE (data source). Additional columns for subtitles (TTL2, TTL3, …), further footnotes (FOOT2, FOOT3, …), population definitions, book mark and bylines are also supported. If your file uses different column names, use change_colname() to remap them to the expected names before passing the file to any tflmetaR function.

Workflow

The typical workflow is to retrieve annotation metadata from a metadata file and apply it to a TFL object created with packages such as {gt}, {flextable}, or {ggplot2}, or with lower-level grid tools such as grob or gtable. Metadata can be retrieved in two ways.

Option 1: Single-function interface

Use tflmetaR() to retrieve the required metadata in a single call:

path    <- system.file("extdata", "sample_titles.xlsx", package = "tflmetaR")
pgmname <- "t_dm"

title_info <- tflmetaR(
  path,
  by_value         = pgmname,
  annotation       = "TITLE",
  add_footr_tstamp = FALSE
)

footnotes  <- tflmetaR(
  path,
  by_value         = pgmname,
  annotation       = "FOOTR",
  add_footr_tstamp = FALSE
)

Option 2: Helper-function workflow (recommended)

Read the metadata file once with read_tfile(), then retrieve the required metadata with the get_*() helper functions. This avoids repeated I/O operations when annotating multiple fields:

meta       <- read_tfile(filename = path)
title_info <- get_title(meta, pname = pgmname)
footnotes  <- get_footnote(meta, pname = pgmname, add_footr_tstamp = FALSE)

Example

The following example creates a table using {gt} and annotates it with titles and footnotes retrieved from a metadata file using {tflmetaR}.

library(tflmetaR)
library(gt)

# Locate example metadata file
path <- system.file("extdata", "sample_titles.xlsx", package = "tflmetaR")
pgmname <- "t_dm"

# Retrieve annotation metadata (Option 2: helper-function workflow)
meta <- read_tfile(filename = path)
titles <- get_title(meta, pname = pgmname)
footnotes <- get_footnote(meta, pname = pgmname, add_footr_tstamp = FALSE)

# Create the annotated gt table
tbl <- mtcars |>
  head(5) |>
  gt::gt() |>
  gt::tab_header(
    title    = titles$TTL1[[1]],
    subtitle = gt::html(titles$TTL2[[1]])
  ) |>
  gt::tab_footnote(footnote = footnotes$FOOT1[[1]]) |>
  gt::tab_footnote(footnote = footnotes$FOOT2[[1]]) |>
  gt::tab_options(table.width = gt::pct(80))

tbl

Functions

• tflmetaR() — Single-call interface for retrieving annotation metadata
• read_tfile() — Read metadata from Excel or CSV
• get_title() — Retrieve titles and subtitles
• get_footnote() — Retrieve footnotes
• get_source() — Retrieve data source
• get_pop() — Retrieve population
• get_byline() — Retrieve bylines
• get_pgmname() — Retrieve program name
• get_bookm() — Retrieve bookmark
• get_ulheader() — Retrieve upper-left header content
• get_urheader() — Retrieve upper-right header content
• change_colname() — Standardize column names in the metadata file

Related Packages

tflmetaR is designed to work alongside:

• {gridify} — for layout and rendering annotated TFLs
• Pharmaverse — a curated collection of R packages for clinical reporting

Getting Help

For more information please visit the following vignettes:

• Table Example vignette("table-example", package = "tflmetaR") - Using tflmetaR with gt for Professional Tables.
• Figure Example vignette("f_km", package = "tflmetaR") - Creating Kaplan-Meier Survival Plots with tflmetaR and gridify.

Acknowledgments

Along with the authors and contributors, thanks to the following people for their support:

Alberto Montironi, Maciej Nasinski