TriNetX Neuropsychiatric Outcomes Analysis Pipeline

R pipeline for parsing TriNetX cohort exports, generating publication-ready figures, computing prospective statistical power, and exporting consolidated results tables for manuscript preparation.

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Overview

This repository contains:

• Raw TriNetX export files
• An R analysis pipeline
• Publication-ready figures
• Consolidated results tables
• Statistical power analyses

The workflow parses TriNetX MOA and Kaplan–Meier exports across three propensity-score-matched concussion cohorts and generates manuscript figures and supplementary analytic outputs automatically.

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Repository Structure

.
├── data/
│   ├── Concuss_1x_5_year_V12_424528/
│   ├── Concuss_2x_5_year_V12_(1)_(1)_677193/
│   └── Concuss_3x_5_year_V12_327389/
│
├── R/
│   └── make_figures.R
│
├── results/
│   ├── figure2_forest.*
│   ├── figure3_power.*
│   ├── power_table.csv
│   ├── results.csv
│   ├── figure_captions.txt
│   └── session_info.txt
│
└── README.md

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Requirements

R Version

• R 4.3 or newer recommended

Required Packages

The script automatically loads:

ggplot2
dplyr
readr
stringr
purrr
scales
grid
gtable
patchwork

Install missing packages with:

install.packages(c(
  "ggplot2",
  "dplyr",
  "readr",
  "stringr",
  "purrr",
  "scales",
  "gtable",
  "patchwork"
))

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Running the Pipeline

From the repository root directory, run:

Rscript R/make_figures.R

The script will automatically:

• Parse all TriNetX outcome tables
• Build consolidated results datasets
• Apply BH-FDR correction
• Compute prospective statistical power
• Generate publication-ready figures
• Export all outputs to ./results

No additional configuration is required if the repository structure is preserved.

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Input Data

The pipeline expects three comparison directories inside ./data:

Comparison	Description
Concuss_1x_5_year_V12_424528	Single concussion vs orthopedic fracture controls
Concuss_2x_5_year_V12_(1)_(1)_677193	Two concussions vs one concussion
Concuss_3x_5_year_V12_327389	Three concussions vs two concussions

Each directory must contain TriNetX exports including:

• MOA tables
• KM tables
• associated graph CSVs
• baseline characteristic files

The analysis script specifically parses:

Outcome_*_Result_a_MOA_table.csv
Outcome_*_Result_b_KM_table.csv

for outcomes 1–8.

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Outcomes Included

Internalizing / Neurodevelopmental

• Mood disorders
• Anxiety disorders
• ADHD
• Unspecified psychosis

Substance Use

• Generalized substance use disorder
• Alcohol-related disorders
• Cannabis-related disorders
• Opioid-related disorders

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Statistical Methods

Relative Risk Analysis

The script extracts:

• Relative risks (RR)
• Hazard ratios (HR)
• 95% confidence intervals
• Log-rank p-values

from TriNetX exports.

Multiple Testing Correction

Benjamini–Hochberg false discovery rate correction is applied across all 24 hypothesis tests.

Prospective Power Analysis

Prospective statistical power is computed using:

• two-sided α = 0.05
• minimum clinically important RR = 1.20
• normal approximation to the two-proportion z-test

using matched cohort sample sizes and observed reference-group event rates.

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Output Files

All outputs are written to:

./results/

Main Tables

File	Description
results.csv	Consolidated analytic dataset
power_table.csv	Prospective power calculations

Figures

Figure 2 — Forest Plot

Exports:

figure2_forest.svg
figure2_forest.pdf
figure2_forest.png
figure2_forest.tiff

Displays:

• Relative risks
• 95% confidence intervals
• BH-FDR significance indicators

Figure 3 — Prospective Power Analysis

Exports:

figure3_power.svg
figure3_power.pdf
figure3_power.png
figure3_power.tiff

Displays:

• Statistical power across outcomes and comparisons
• Conventional 80% adequacy threshold

Additional Outputs

File	Description
figure_captions.txt	Manuscript-ready figure captions
session_info.txt	Full R session metadata

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Console Output

The script prints:

• Figure captions
• Comparisons with power < 0.80
• Comparisons with power < 0.50

Example:

Cells with power < 0.80:
- CX3_vs_CX2 | Opioid-related | power=0.412

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Figure Specifications

Figures are exported at:

• Width: 260 mm
• Height: 120 mm
• Resolution: 300 DPI

Formats include:

• SVG
• PDF
• PNG
• TIFF (LZW compression)

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Reproducibility

The analysis includes:

• deterministic random seed (set.seed(20260421))
• session metadata export
• standardized plotting themes
• fully scripted data processing

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Notes

• The script assumes consistent TriNetX export formatting.
• Missing or malformed files will stop execution with informative errors.
• Helvetica is used as the default figure font family.

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License

Add your preferred license here.

Example:

MIT License

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Citation

If used in academic work, please cite the associated manuscript or repository.