calc_AUC_expected_QR: Calculate the expected AUC under the QR model

In mjdufort/CpeptideTools: Tools for handling C-peptide data from MMTT/OGTT

Calculate the expected AUC under the QR model

Description

This function calculates the expected AUC under the quantitative response (QR) model for a mixed meal tolerance test (MMTT), following the approach developed by Bundy et al. 2020 (PMID 32704564), with expansions for other timepoints by Ylescupidez et al. 2023 (PMID 37940642). As input, it takes a data frame with age and baseline C-peptide values for each subject, and a timepoint for which to calculate the expected AUC. NOTE: Values for AUC must be in the standardized units used in the QR model, specifically in units of nmol per L per minute from a 120-minute MMTT (not log-transformed). Values for age must be in years.

Usage

calc_AUC_expected_QR(
  input_data, timepoint = 12, 
  cpeptide_baseline_colname = "auc_mean", age_colname = "age_years")

Arguments

input_data	data frame containing the C-peptide AUC values from MMTTs and subject ages.
timepoint	numeric, the number of months at which to calculate the expected C-peptide value. Current implementation only supports 12.
cpeptide_baseline_colname	character or numeric, the column containing the C-peptide values. Defaults to "auc_mean".
age_colname	character or numeric, the column containing the age values. Defaults to "age_years".

Details

The equation used is: "Cpep_expected = -0.191 + 0.812 * ln(Cpep_baseline + 1) + 0.00638 * Age"

Value

a vector containing the expected C-peptide values at the specified timepoint, in ln(nmol/L/min + 1).

mjdufort/CpeptideTools documentation built on March 5, 2025, 6:58 p.m.