ArticleDiabetologia2025
Type 1 diabetes prediction in autoantibody-positive individuals: performance, time and money matter.
Article in Diabetologia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- International consensus guidance for general population screening for islet autoantibodies to diagnose early-stage type 1 diabetes: a nominal group technique process.Diabetologia · 2026Article
- BMI Normalization Is Associated With Lower Risk of Progression to Type 1 Diabetes, Primarily in Youth.Diabetes care · 2026Article
- Development of a Patient-Level Multi-objective Optimisation Model for Screening Strategies for Childhood Type 1 Diabetes.PharmacoEconomics · 2026Article
- The evolution of C-peptide's role in diabetes care.Current opinion in endocrinology, diabetes, and obesity · 2026Review
- Article
- Historically Based Perspective on the Immunotherapy of Type 1 Diabetes: Where We Have Been, Where We Are, and Where We May Go.Journal of clinical medicine · 2025Article
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Authors and funding
14 authors.
Funding
Abstract
aims/hypothesisEfficient prediction of clinical type 1 diabetes is important for risk stratification and monitoring of autoantibody-positive individuals. In this study, we compared type 1 diabetes predictive models for predictive performance, cost and participant time needed for testing.
methodsWe developed 1943 predictive models using a Cox model based on a type 1 diabetes genetic risk score (GRS2), autoantibody count and types, BMI, age, self-reported gender and OGTT-derived glucose and C-peptide measures. We trained and validated the models using halves of a dataset comprising autoantibody-positive first-degree relatives of individuals with type 1 diabetes (n=3967, 49% female, 14.9 ± 12.1 years of age) from the TrialNet Pathway to Prevention study. The median duration of follow-up was 4.7 years (IQR 2.0-8.1), and 1311 participants developed clinical type 1 diabetes. Models were compared for predictive performances, estimated cost and participant time.
resultsModels that included metabolic measures had best performance, with most exhibiting small performance differences (less than 3% and p>0.05). However, the cost and participant time associated with measuring metabolic variables ranged between US$56 and US$293 and 10-165 min, respectively. The predictive model performance had temporal variability, with the highest GRS2 influence and discriminative power being exhibited in the earliest preclinical stages. OGTT-derived metabolic measures had a similar performance to HbA CONCLUSIONS/
interpretationCost-performance model analyses identified trade-offs between cost and performance models, and identified cost-minimising options to tailor risk-screening strategies.
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