Multidimensional Pancreatic Islet β-cell Function Assessment Improves Predictive Effect of Diabetes Risk Scores
Authors' conclusion
This novel system offers an effective method for PIF assessment, enhancing diabetes prediction and management by deepening the understanding of diabetes complexity and aiding in precise therapy.
Study context
- Population
- 814 JuRong City cohort volunteers (195 metabolically healthy, 619 abnormal), 12 Botnia clamp participants, 3394 T2D patients and 6345 METSIM cohort participantsmultiple cohorts
- Comparison
- PIF clusters in metabolically abnormal individuals; cluster 2 and 3 vs cluster 1
- Outcome
- Diabetes risk by PIF cluster (METSIM cohort)
Methodological detailsmulticohort, cluster analysis, restricted cubic spline modeling
- Multicohort
- Cluster analysis
- Restricted cubic spline modeling
Main finding
As reported in the abstract
Each group vs cluster 1Hazard ratio (95% CI)P value
Cluster 2
2.499(1.932–3.233)
P = 3.11E-12Cluster 3
3.185(2.353–4.311)
P = 6.35E-12Further findings
Metabolic profiles and disease risks (JuRong metabolically abnormal)
- Cluster 1 (highest PIF-A): best metabolic profiles and lowest cardiovascular and renal disease risks
- Cluster 3: poorest metabolic profiles and highest disease risks
Complications in T2D
- T2D patients with high PIF-S and PIF-L more prone to complications
Diabetes prediction
- 3-dimensional PIF indices surpass previous indicators in predicting diabetes and significantly improved predictive efficiency of existing risk scores
Botnia clamp validation
- Clamp experiment confirmed the distinct meaning of 3 PIF indices
Original publication
Multidimensional Pancreatic Islet β-cell Function Assessment Improves Predictive Effect of Diabetes Risk Scores. J Clin Endocrinol Metab. Published 23 June 2025. doi:10.
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