Clinical Prediction Models Combining Routine Clinical Measures Have High Accuracy in Identifying Youth-Onset Type 2 Diabetes Defined by Maintained Endogenous Insulin Secretion: The SEARCH for Diabetes in Youth Study
Authors' conclusion
Prediction models combining routine clinical measures at diabetes diagnosis, with or without islet autoantibodies or T1DGRS, can accurately identify youth with diabetes who maintain endogenous insulin secretion in the range associated with T2D.
Study context
- Population
- Youth with diabetes (diagnosis age ≤19 years) in the prospective SEARCH for Diabetes in Youth study; predictors from baseline visit at mean diabetes duration of 11 months
- Participants
- 2,966 participants
- Comparison
- Models with routine clinical measures with vs without islet autoantibodies (GADA, IA-2A) and T1D genetic risk score (T1DGRS)
- Outcome
- Fasting C-peptide ≥250 pmol/L (≥0.75 ng/mL)
- Follow-up
- >3 years' (median 74 months) diabetes duration
Methodological detailsprospective, internal validation
- Prospective
- Internal validation
Performance
As reported in the abstract
Identification of participants with C-peptide ≥0.75 ng/mL
AUCROC, models with or without autoantibodies and T1DGRS
0.95-0.98
Participants with C-peptide ≥0.75 ng/mL
17%
C-peptide ≥0.75 ng/mL among those with positive autoantibodies
2.3%
C-peptide ≥0.75 ng/mL among those without positive autoantibodies
53%
Further findings
Internal validation
- Optimism very low; excellent calibration (slope)
- 0.995-0.999
Retained C-peptide, subgroups
- AUCROC in older youth with obesity
- 0.88-0.96
- AUCROC in subgroups by self-reported race and ethnicity
- 0.88-0.97
- AUCROC by autoantibody status
- 0.87-0.96
- AUCROC by clinically diagnosed diabetes type
- 0.81-0.92
Original publication
Clinical Prediction Models Combining Routine Clinical Measures Have High Accuracy in Identifying Youth-Onset Type 2 Diabetes Defined by Maintained Endogenous Insulin Secretion: The SEARCH for Diabetes in Youth Study. Diabetes Care. Published 22 January 2024. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →