# DDMODEL00000091: Van Cauter C-peptide model

Short description:
Standardized model for C-peptide kinetics
 Format: PharmML (0.6.1) Related Publication: .hiddenContent {display:none;} Estimation of insulin secretion rates from C-peptide levels. Comparison of individual and standard kinetic parameters for C-peptide clearance. Van Cauter E, Mestrez F, Sturis J, Polonsky KS Diabetes, 3/1992, Volume 41, Issue 3, pages: 368-377 Affiliation: Department of Medicine, University of Chicago, Illinois 60637. Abstract: Insulin secretion rates can be accurately estimated from plasma C-peptide levels with a two-compartment model for C-peptide distribution and degradation. In previous studies, the kinetic parameters of C-peptide clearance were derived in each subject from the decay curve observed after bolus intravenous injection of biosynthetic human C-peptide. To determine whether standard parameters for C-peptide clearance could be defined and used to calculate insulin secretion without obtaining a decay curve in each subject, we analyzed 200 decay curves of biosynthetic human C-peptide obtained in normal, obese, and non-insulin-dependent diabetes mellitus subjects studied in our laboratory. This analysis showed that the volume of distribution and kinetic parameters of C-peptide distribution and metabolism vary by less than 30% in a population highly heterogeneous in terms of age, sex, degree of obesity, and degree of glucose tolerance. The volume of distribution correlated with the degree of obesity as quantified by body surface area (BSA). This dependence of C-peptide distribution volume on BSA was more marked in men than in women. The long half-life was slightly longer in elderly subjects than in younger adults. When effects of BSA, sex, and age were taken into account, the parameters of C-peptide kinetics were very similar in normal, obese, and diabetic subjects. Based on these findings, a simple procedure to derive standard parameters for C-peptide clearance taking into account degree of obesity, sex, and age was defined. These standard parameters resulted in estimations of mean insulin secretion rates, which differed in each subject by only 10-12% from those obtained with individual parameters. The approach of using standard rather than individual parameters did not systematically underestimate or overestimate insulin secretion so that group values for the fasting secretion rate, the mean 24-h secretion rate, and the number and the amplitude of secretory pulses obtained with standard parameters differed by only 1-2% from the values obtained with individual parameters. Furthermore, the accuracy of measurements based on standard parameters was not different from that associated with replicate determinations of the parameters of C-peptide clearance in the same subject. We conclude that it is possible to estimate insulin secretion rates from plasma C-peptide levels with standard parameters for C-peptide clearance rather than individually derived parameters without significant loss of accuracy. Contributors: Roberto Bizzotto
 Context of model development: Clinical end-point; Mechanistic Understanding; Discrepancy between implemented model and original publication: This model instance describes the Van Cauter model as it is commonly used, i.e., for the calculation of C-peptide kinetic parameters from the subject's anthropometric characteristics. In the original study by Van Cauter et al., the C-peptide kinetic parameters were derived from the individual C-peptide decay curves using least-squares parameter estimation. This model instance does not describe parameter estimation.; Long technical model description: vanCauter.txt; Model compliance with original publication: No; Model implementation requiring submitter’s additional knowledge: Yes; Modelling context description: The main purpose of the C-peptide kinetics model is to calculate insulin secretion from C-peptide concentration using deconvolution. The model by Van Cauter et al. was developed to estimate individual parameters for C-peptide kinetics based on the anthropometric characteristics of the subjects, in order to avoid the determination of the individual C-peptide decay curves. In the Van Cauter model, simple allometric equations are used to derive the parameters based on the diabetes status, obesity, sex, weight, height and age. These standard C-peptide kinetic parameters resulted in deconvolution-estimated insulin secretion rates that differed in each subject by only 10-12% from those obtained with individual parameters. This model instance describes the Van Cauter model as it is commonly used, i.e., for the calculation of C-peptide kinetic parameters from the subject's anthropometric characteristics. This model is used not only to determine insulin secretion by deconvolution but also as a component of insulin secretion models (e.g. Mari A, Tura A, Gastaldelli A, Ferrannini E: Assessing insulin secretion by modeling in multiple-meal tests: role of potentiation. Diabetes 51 (Suppl 1):S221-S226, 2002).; Modelling task in scope: estimation; simulation; Nature of research: Clinical research & Therapeutic use; Therapeutic/disease area: Endocrinology;
 Validation Status: Annotations are correct. Certification Comment: This model is not certified.
• Model owner: Roberto Bizzotto
• Submitted: Dec 10, 2015 7:49:25 PM
##### Revisions
• Version: 13
• Submitted on: May 18, 2016 2:43:30 PM
• Submitted by: Roberto Bizzotto
• With comment: Model revised without commit message
• Version: 10
• Submitted on: Dec 10, 2015 7:49:25 PM
• Submitted by: Roberto Bizzotto
• With comment: Edited model metadata online.

Independent variable T

### Structural Model sm

Variable definitions

$BSA=((0.2024726 ×wt0.425) ×ht0.725)$
$BMI=wtht2$
$T2=(29.2+(0.14 ×age))$
$A=FV$
$B=(1-F)V$
$a=log(2)T1$
$b=log(2)T2$
$dx1dT=((-a ×x1)+ISR)$
$dx2dT=((-b ×x2)+ISR)$
$C=((A ×x1)+(B ×x2))$

Initial conditions

$x1=ISRssa$
$x2=ISRssb$

### Covariate Model

Continuous covariate ISR

Continuous covariate wt

Continuous covariate ht

Continuous covariate age

Continuous covariate sex

Continuous covariate T2D

Parameters

### Observation Model

#### Observation YContinuous / Residual Data

Parameters

$Y=C$

• simStep_1