An improved clinical model to predict stimulated C-peptide in children with recent-onset type 1 diabetes

Area of Science:

• Endocrinology
• Metabolic Disorders
• Pediatric Diabetes

Background:

• The mixed meal tolerance test (MMTT) is the gold standard for assessing residual beta-cell function in type 1 diabetes (T1D).
• However, MMTT is impractical for routine clinical use outside of research settings.
• There is a need for a more accessible method to evaluate beta-cell function in T1D.

Purpose of the Study:

• To develop and validate a clinical model for estimating residual beta-cell function in children with recent-onset T1D.
• To identify commonly measured clinical variables that can predict stimulated C-peptide levels.
• To provide a practical tool for monitoring disease progression in T1D.

Main Methods:

• A predictive model was developed using multiple linear regression in a cohort of 46 children with recent-onset T1D.
• The model incorporated variables such as age, gender, BMI, HbA1c, and insulin dose.
• The model was subsequently validated in a larger clinical cohort of 262 children (Hvidoere study group).

Main Results:

• A clinical model incorporating age, gender, BMI, HbA1c, and insulin dose accurately predicted 90-minute stimulated C-peptide levels (adjusted R² = 0.63, P < 0.0001).
• The combined insulin dose and HbA1c (IDAA1c) alone had a lower predictive value (R² = 0.37, P < 0.0001).
• The model demonstrated consistent predictive accuracy at 6 and 12 months post-diagnosis in the validation cohort.

Conclusions:

• A clinical model utilizing age, gender, BMI, HbA1c, and insulin dose effectively estimates stimulated C-peptide levels in children with recent-onset T1D.
• This estimated C-peptide measurement serves as a valuable surrogate for assessing residual beta-cell function.
• The developed model offers a practical approach for monitoring T1D management and progression outside of clinical trials.