A scoring model integrating CXCL9, GDF15, FGF21, and NfL, predicts long-term mortality in type 2 diabetes: a retrospective study
Authors' conclusion
These findings suggest that inflammatory and metabolic stress-related biomarkers independently predict long-term mortality in T2D. The biomarker-based scoring model enhances risk stratification and improves the prognostic performance of existing clinical tools, such as the RECODe equation, potentially informing targeted clinical interventions.
Study context
- Population
- Individuals with T2D followed for a median of 16.1 years
- Participants
- 478 individuals
- Outcome
- All-cause mortality
- Follow-up
- Median 16.1 years
Main finding
As reported in the abstract
Independent predictors of all-cause mortality (multivariable Cox regression)
- CXCL9, HR per 1 SD increase
- 1.19 (95% CI 1.05-1.36, p = 0.006)
- GDF15, HR
- 1.16 (95% CI 1.02-1.33, p = 0.032)
- NfL, HR
- 1.25 (95% CI 1.09-1.43, p = 0.001)
- FGF21, HR
- 1.20 (95% CI 1.04-1.37, p = 0.009)
- Composite biomarker score (range 4-12), HR per 1-point increase (95% CI 1.35-1.74, p < 0.001); 55% higher mortality risk
- 1.53
Observational data: associations, not effects.
Further findings
Biomarker levels in deceased individuals
- Deceased individuals had significantly higher IL-6, IL-10, CXCL9, FGF21, NfL and GDF15
- Biomarker levels correlated with microvascular and macrovascular complications, particularly neuropathy, nephropathy, retinopathy and major adverse cardiovascular events (MACE)
Biomarker score vs RECODe model
- Score remained independently predictive after adjustment for clinical covariates and significantly improved risk classification beyond RECODe (net reclassification and discrimination improvement)
Original publication
A scoring model integrating CXCL9, GDF15, FGF21, and NfL, predicts long-term mortality in type 2 diabetes: a retrospective study. Cardiovasc Diabetol. Published 8 July 2025. doi:10.
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