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Staging intermediate hyperglycaemia for type 2 diabetes prevention: the ELSA-Brasil study
Paula A Bracco1,2, Maria I Schmidt3, Danilo de Paula1
1Postgraduate Program in Epidemiology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
Diabetologia
|May 12, 2026
Summary
Fasting plasma glucose and 1-hour plasma glucose staging effectively identifies type 2 diabetes development risk. Combining this with a clinical score improves accuracy and reduces unnecessary lab tests for prediabetes.
Area of Science:
- Endocrinology
- Metabolic Diseases
- Public Health
Background:
- Type 2 diabetes (T2D) development involves intermediate hyperglycaemia stages.
- Accurate staging is crucial for timely intervention and complication prevention.
Purpose of the Study:
- To evaluate T2D development stages using combined fasting plasma glucose (FPG) and 1-hour plasma glucose (1h PG) or HbA1c levels.
- To assess the utility of a clinical score in conjunction with these staging schemas.
Main Methods:
- Utilized data from 1174 Brazilian adults in the ELSA-Brasil cohort.
- Developed staging schemas based on FPG/1h PG and FPG/HbA1c thresholds for mild and moderate hyperglycaemia.
- Incorporated a clinical score (≥10% 10-year diabetes risk) and evaluated insulin secretion-sensitivity index-2 (ISSI-2) and complication risk.
Main Results:
- The FPG/1h PG schema stratified individuals by decreasing ISSI-2 and increasing complication risk, with progressively higher relative risks of incident T2D.
- This schema demonstrated 89.1% sensitivity and 53.7% specificity, improving to 60.3% specificity when combined with a clinical score, reducing lab testing by 27.1%.
- FPG/HbA1c schemas showed poorer prognostic properties compared to FPG/1h PG, though performance improved with the clinical score.
Conclusions:
- FPG/1h PG staging provides nuanced stratification of intermediate hyperglycaemia with superior prognostic value over FPG/HbA1c schemas.
- Integrating a predictive clinical score enhances staging accuracy, reduces laboratory burden, and minimizes false positives in diabetes risk assessment.
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