Cardiovascular Risk Prediction Scores in Type 1 Diabetes: A Systematic Review and Meta-Analysis

Area of Science:

• Endocrinology
• Cardiology
• Epidemiology

Background:

• The predictive performance of cardiovascular disease (CVD) risk scores in individuals with type 1 diabetes (T1DM) is not well-established.
• Accurate CVD risk assessment is crucial for managing T1DM patients.

Purpose of the Study:

• To systematically review and meta-analyze the performance of existing CVD risk scores in individuals with T1DM.
• To compare the discriminative and calibration abilities of T1DM-specific, type 2 diabetes-specific, and general population CVD risk scores.

Main Methods:

• Systematic review and meta-analysis of studies published up to December 31, 2023, from PubMed and EMBASE.
• Included studies assessed CVD outcomes and risk scores in T1DM populations.
• Meta-analysis of discrimination measures (C-statistic) using random-effects models, stratified by risk score type.

Main Results:

• Analyzed 11 studies with 73,664 participants (mean age 34 years, predominantly White males).
• Evaluated 12 CVD risk prediction models (7 T1DM-specific, 1 T2DM-specific, 4 general population).
• Most scores demonstrated moderate to excellent discrimination (C-statistic: 0.73-0.85) and good calibration. T1DM-specific scores (pooled C-statistic 0.81) outperformed general/T2DM scores (0.75).

Conclusions:

• Cardiovascular disease risk models exhibit moderate to excellent discrimination in individuals with T1DM.
• Type 1 diabetes-specific risk scores offer superior discriminative performance and accuracy compared to general or type 2 diabetes models.