Type 1 diabetes

Lifetime and 10‐year cardiovascular risk prediction in individuals with type 1 diabetes: The LIFE‐T1D model

Diabetes Obes MetabPublished Prediction model development and external validation study

Authors' conclusion

The LIFE-T1D model can estimate lifetime risk of CVD and CVD-free life expectancy in individuals with type 1 diabetes without previous CVD. This model can facilitate individualized CVD prevention among individuals with type 1 diabetes. Validation in additional cohorts will improve future clinical implementation.

Study context

Population
Individuals with T1D without prior cardiovascular disease (CVD)
Participants
39,756 / 2,709 / 1,022
Comparison
National Diabetes Register (NDR) vs Funen Diabetes Database (FDDB) vs UK Biobank
  • NDRn = 39,756
  • FDDBn = 2,709
  • UK Biobankn = 1,022
Outcome
Lifetime and 10-year risk of CVD (model discrimination, c-statistic)
Methodological detailssex-specific competing risk-adjusted Cox proportional hazards model, age as the time axis
  • Sex-specific competing risk-adjusted Cox proportional hazards model
  • Age as the time axis

Performance

As reported in the abstract

C-statistic
Test or modelValueInternal validation c-statisticExternal validation c-statistic
NDR0.85 (95% CI 0.84–0.85)0.85
FDDB0.77 (95% CI 0.74–0.81)0.77
UK Biobank0.73 (95% CI 0.70–0.77)0.73

Value

NDR0.85 (95% CI 0.84–0.85)
FDDB0.77 (95% CI 0.74–0.81)
UK Biobank0.73 (95% CI 0.70–0.77)

Internal validation c-statistic

NDR0.85
FDDB— not stated in the abstract
UK Biobank— not stated in the abstract

External validation c-statistic

NDR— not stated in the abstract
FDDB0.77
UK Biobank0.73

Further findings

Events in NDR · median follow-up 11.8 years (IQR 6.1-17.1 years)

CVD events
4608
Non-CVD deaths
1316

Parts of this Brief are withheld: the automatic checks could not confirm them against the abstract.

Original publication

Lifetime and 10‐year cardiovascular risk prediction in individuals with type 1 diabetes: The LIFE‐T1D model. Diabetes Obes Metab. Published 8 March 2024. doi:10.1111/dom.15531

Composed by AI from the published abstract and checked against it. How Briefs are made →

Get them every week

New studies on this topic in My Week and in your Monday e-mail.

We e-mail you a sign-in link and a code. No password, no spam.