InsuSensCalc

InsuSensCalc: Insulin Sensitivity Calculator (ISC)

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Overview

InsuSensCalc (Insulin Sensitivity Calculator, or ISC for short) provides reproducible calculators for a wide range of insulin sensitivity indices derived from common clinical and research measurements (fasting, OGTT, adipose tissue, tracer studies and DXA). It is designed to be:

Who should use this package?

Quick start

Install from CRAN or GitHub and run a quick example:

install.packages("InsuSensCalc") # or remotes::install_github("sufyansuleman/InsuSensCalc")
library(InsuSensCalc)
data(example_data)
res <- isi_calculator(example_data, category = c("fasting", "ogtt"))
head(res)

Introduction

InsuSensCalc is an R package for computing insulin sensitivity indices from fasting, OGTT, adipose tissue, tracer, and DXA data. It provides a single, reproducible workflow to calculate multiple established insulin sensitivity measures used in metabolic research.

About this package

This package was developed as part of the study available at https://pubmed.ncbi.nlm.nih.gov/38635292/. The package was used to support the analyses reported in that work, and it is intended for researchers who need a consistent, easy-to-use calculator for insulin sensitivity indices.

Key features

Note: This README is the package landing page. No additional pkgdown website is included at this time.

Setup

Prerequisites

Load the necessary R libraries:

library(dplyr)
library(magrittr)
library(tibble)

If missing any, install via install.packages("package_name").

Installing InsuSensCalc

Install from CRAN or GitHub:

install.packages("InsuSensCalc")

Or directly from GitHub:

remotes::install_github("sufyansuleman/InsuSensCalc")

Understanding the isi_calculator Function

Function Overview

The package has a single main function, isi_calculator, where isi stands for Insulin Sensitivity Indices. It takes a dataframe as input and returns the same data with the requested insulin sensitivity indices appended as new columns. Indices are grouped by the type of measurement they are derived from (fasting, OGTT, adipose tissue, tracer/DXA), and you choose which groups to compute with the category argument.

Input Parameters

What it calculates

The isi_calculator function computes various insulin sensitivity (IS) indices across different data categories.

Categories and Indices

Fasting Measurements

Indices calculated from fasting measurements are essential for assessing baseline insulin sensitivity and resistance.

OGTT Measurements

OGTT-based indices are derived from glucose and insulin responses to an oral glucose tolerance test, offering insights into dynamic insulin sensitivity.

Adipose Tissue Measurements

Adipose tissue-related indices focus on the interactions between insulin sensitivity and adipose tissue metrics.

Tracer and DXA Measurements

These specialized indices involve tracer and dual-energy X-ray absorptiometry (DXA) measurements, providing advanced assessments of insulin resistance.

Data Preparation

Structure your data with the following columns and units:

Column names are case sensitive and must match exactly.

Example Usage

Calculate indices with your formatted data:

# Define or load your dataframe 'your_data'

result <- isi_calculator(your_data, "fasting")
result <- isi_calculator(your_data, "ogtt")
result <- isi_calculator(your_data, category = c("fasting", "ogtt"))

result <- isi_calculator(your_data, category = c("fasting", "ogtt", "adipo", "tracer_dxa"))
print(result)

Citation

If you use InsuSensCalc in your research, please cite both the package and the underlying study.

Citing the package

Suleman, S. (2025). InsuSensCalc: An R package for computing insulin sensitivity indices. Zenodo. https://doi.org/10.5281/zenodo.20647742

Or in BibTeX:

@software{suleman_insusensecalc_2025,
  author    = {Suleman, Sufyan},
  title     = {InsuSensCalc: An R package for computing insulin sensitivity indices},
  year      = {2025},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.20647742},
  url       = {https://doi.org/10.5281/zenodo.20647742}
}

Citing the underlying study

This package was developed from and used in the published study:

Suleman S, et al. InsuSensCalc package for insulin sensitivity index calculation. Study available at PubMed PMID 38635292. Please cite the package and the underlying study when using it in your research.

You can also use the built-in citation helper from R:

citation("InsuSensCalc")

Interpreting the Output

The resulting dataframe lists calculated indices. Missing data points will not have the corresponding index value. Output columns are raw, non-standardized values of the indices that may require normalization or standardization prior to any statistical analysis or visualization.

Conclusion

The InsuSensCalc package’s isi_calculator function offers a detailed methodology for insulin sensitivity analysis, supporting a range of data types for metabolic health research. Please cite this package and the associated study when using InsuSensCalc in your publications. The package will be updated with new indices and features in the future.

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