Demographic table

Introduction

  • SDTM: a standard for organizing and formatting “raw” data (e.g from paper diaries, or e-diaries)

    • Defines standard domains

    • Relies on standardized variable names, metadata, and controlled terminology

    • Supports the submission of data to regulatory authorities

  • ADaM: provides a standard framework for derivations for statistical analyses.

    • Promoting: transparency, reproducibility, and regulatory compliance.

      • Traceability: Clear linkage from analysis results back to source data (often SDTM).
      • Standard structures: Like ADSL (Subject-Level Analysis Dataset), BDS (Basic Data Structure), and OCCDS (Occurrence Data Structure).
      • Derived variables: Emphasis on clarity and documentation of derived data used in analysis.
      • Integration with Define-XML:
        • Enables metadata-driven submissions to regulatory agencies
        • Explains derivation of variables
        • Enables re-creation of derivations & statistical analyses by regulatory authorities

  • TLFs: Static output generation for Clinical Study Report

    • Listings: One proc away (filtering , subsetting etc. ), lay-out
    • Tables/ Figures: pre-processing, calculate summary statistics, lay-out (e.g.bars/lines/scatter/ presentation summary statistics) + formatting (e.g titles and footnotes) + export output (e.g. pdf, rtf, xlsx & html)

    Created with help of CDISC genius

Tables, Listings and Graphs/Figures (TLGs/TLFs)

Static outputs are part of the clinical reporting process. They are a vital part to summarise the results of the clinical trial. They can summarise safety, efficacy and exploratory outcomes, e.g. biomarkers, QOL, questionnares etc.

Safety outputs (medical history, adverse events, and concomitant medications) are pretty much similar and standard outputs that you will see across all clinical trials ( regardless of sponsor/therapeutic area).

Note. These domain names come from SDTM.

Demographic Table

!DMT01

Workflow

Method 1

The {cards} package creates Analysis Results Datasets (ARDs, which are a part of the CDISC Analysis Results Standard). The {gtsummary} utilizes ARDs to create tables.

Method 2

  • NEST Package: A collection of open-sourced R packages:

    • {rtables}: designed to create and display complex tables with R. Create and apply the tabulation of simple and complex table layouts.

    • {rlistings}: create listings

    • {tern}: contains analysis functions (e.g statistical modelling, data viz functions and analyze functions) to create tables and graphs used for clinical trial reporting.

    • {formatters}

    • {teal}

  • Other Package:

    • GGPLOT2 ### Tern Package

Analyze functions

Table {tern} analyze function
Demographic table summarize_vars()
  • wraps around the rtables analyze summarize functions.
  • And these functions specifically use tan statistics functions to do the required statistical computation on your data.
  • And it also provides the options for formatting and analysis modifications to help you define your analysis.

Analyze functions

  • .stats: which statistics to be displayed in the ta
  • .formats: which vaue formats should be u
  • .labels: whcih row labels should be used
  • .indent_mods: indent modifiers for the labels
  • .show_labels: whether vaiable label(s) should be visible or hidden