Cardiovascular Risk Scores Perform Poorly in Type 1 Diabetes
Traditional tools used to predict 10-year cardiovascular risk do not perform well in people with type 1 diabetes (T1D), new research showed; however, the addition of a coronary artery calcium (CAC) test modestly improved prediction.
Models such as the Framingham Risk Score (FRS), the ASCVD Risk Estimator Plus (ASCVD), and the American Heart Association’s Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) are often integrated into electronic health records and used clinically to inform treatment decisions, yet most have not been externally validated in people with T1D.
This is a concern because “the distinct, accelerated course of cardiovascular disease in people with T1D may challenge the standard prediction models,” said Victoria R. Trapani, MPH, a research associate at the George Washington University Biostatistics Center in Washington, DC.
“More accurate, tailored risk estimation is needed for early risk mitigation interventions in T1D,”
she told attendees at the European Association for the Study of Diabetes (EASD) 2026 Annual Meeting.
Article Key Points
• FRS, ASCVD, PREVENT poorly predicted 10-year CVD risk in T1D.
• Observed CVD risk exceeded FRS by 1.43x; ASCVD 2.69x; PREVENT 2.40x.
• ST1RE slightly overpredicted risk; discrimination modest across models (c-statistic 0.54-0.64).
• CAC ≥100 reclassified low/moderate-risk T1D pts toward high CVD risk.
• CAC improved prediction modestly; maximal c-statistic rose to 0.68.
Data From the EDIC Study
Trapani and colleagues used data collected in the long-term EDIC study, the follow-on to the landmark DCCT, which established the importance of intensive blood glucose management in minimizing the risk for long-term diabetes complications. Most of the former DCCT participants are now being followed in EDIC over time, with clinical data collected at regular intervals.
Outcomes for EDIC participants older than 30 years
were compared with the predictions from the FRS, ASCVD, and PREVENT, along with one developed specifically for T1D: the Steno T1 Risk Engine (ST1RE).
Data were examined at 10-year intervals in 1311 EDIC participants, who at
EDIC year 1 had a mean age of 36 years, had a mean T1D duration of 13.7 years, were 47.5% female, and had a mean A1c of 8.1%.
By EDIC year 20, the mean age was 54 years, the mean T1D duration was 32.47 years, and mean A1c was 7.97%.
By year 20, 59.8% were using lipid-lowering medication and 56.6% were using antihypertensives.
• A total of 71 first cardiovascular disease (CVD) events occurred during EDIC years 1-10;
• 103 occurred during EDIC years 10-20; and 131 during years 20-30.
• At EDIC year 20, the 10-year observed CVD risk was 1.43 times higher than that predicted by the FRS and was more than twofold higher than the risks predicted by ASCVD (relative risk [RR], 2.69) and PREVENT (RR, 2.40).
In contrast, the ST1RE model slightly overpredicted the risk, with RRs being 0.61-0.87 at all timepoints.
Discrimination was modest, with c-statistics ranging from 0.54 to 0.64 across risk models, with PREVENT being the strongest.
CAC Slightly Improves Prediction
The investigators then looked at the CAC, which was collected in EDIC at year 8. It is not included in any of the risk models, although the ASCVD recommends using CAC as a risk enhancer, if available, with the potential for risk category reclassification.
But “CAC is not routinely performed, so it’s not always readily available for clinical use,” Trapani noted.
The FRS defines 10-year low, moderate, and high risk as a less than 10%, 10%-20%, and more than 20% chance of a CVD event, respectively. Individuals in the low or moderate categories according to the FRS but who had a CAC score ≥ 100 Agatston units had a risk comparable to that of those with a high FRS-predicted risk. Those with a CAC of 0 had a risk comparable to the low predicted FRS risk category.
Very similar patterns were seen with the ASCVD and PREVENT risk scores.
Trapani and colleagues then recategorized the individuals with low or moderate predicted risk by the models but with high CAC scores as high risk and those with CAC scores of 0 from the moderate- to low-risk category. This slightly improved discrimination, with an increase to 0.68 in maximal c-statistic.
Better T1D-Specific Risk Prediction Needed
Asked to comment, Ilhan Satman, MD, professor emerita of internal medicine and endocrinology at Istanbul Faculty of Medicine, Istanbul, Türkiye, told Medscape Medical News, “Most risk models are created for people with type 2 diabetes or those without diabetes…CAC can increase [the prediction] by a little bit more, but not too much. We need to search more to improve the method, and the tools.”
Satman said that there are probably several reasons why the currently used prediction models work less well in T1D, including the more rapid development of kidney and nerve damage and possibly mechanisms related to autoimmunity that aren’t present in T2D or most people without diabetes.
She also brought up a point made by another audience member: Statin use can actually increase coronary artery calcification which will also be picked up on a CAC. “This cannot be discriminated,” she said. “The gold standard, of course, is angiography.”
Clinically, Satman advised that further cardiovascular investigation is warranted for people with T1D who have complications such as nephropathy or foot ulcers, have had T1D for more than 20 years, or who are older than 40 years but added “definitely there’s a need for more practical and more efficient tools.”
During the discussion period, Jan Westerink, PhD, of UMC Utrecht in Utrecht, Netherlands, noted that his group had developed a T1D-specific CV risk predictor called the LIFE-T1D model that is currently available and asked why Trapani hadn’t performed an external validation of it in the EDIC population. Trapani responded, “I am aware of the LIFE-T1D model. Thank you for raising it.” She added that they will consider it for future directions and additional research. Westerink replied, “Happy to cooperate.”
Q: How does coronary artery calcium scoring influence preventive cardiology decisions?
A: Coronary artery calcium scoring can identify subclinical atherosclerosis and improve risk classification beyond clinical factors alone, particularly when CAC is zero or substantially elevated. It is most useful as a risk-enhancing test rather than a standalone decision tool, and interpretation should account for age, diabetes duration, and preventive therapy already in place.
Q: How should cardiovascular risk be assessed in adults with type 1 diabetes?
A: Cardiovascular risk assessment in type 1 diabetes generally relies on traditional risk factors, diabetes duration, glycemic control, kidney disease, blood pressure, lipids, and smoking history, but standard tools may be less reliable than in type 2 diabetes. Clinicians often look for diabetes-specific approaches that better capture the accelerated atherosclerotic risk seen in long-standing disease.
Q: What cardiovascular complications are most common in long-standing type 1 diabetes?
A: Long-standing type 1 diabetes is associated with coronary artery disease, stroke, peripheral arterial disease, nephropathy, and autonomic or peripheral neuropathy, with risk rising as duration and microvascular complications accumulate. Clinicians often consider kidney disease, poor glycemic control, and other end-organ damage as markers of higher cardiovascular risk.
Q: When should statins and antihypertensives be used for primary prevention in type 1 diabetes?
A: Primary prevention in type 1 diabetes typically centers on aggressive management of LDL cholesterol, blood pressure, and other modifiable risk factors, with statin and antihypertensive use guided by overall ASCVD risk and comorbidity burden. Research commonly focuses on how diabetes duration, kidney disease, and age should influence treatment thresholds.
Q: Which screening tests help refine coronary risk stratification in diabetes?
A: Risk refinement may include tests that identify subclinical atherosclerosis or target-organ damage, such as coronary artery calcium scoring, albuminuria assessment, and evaluation of blood pressure and lipid burden. These tools can help reclassify some adults into higher- or lower-risk groups, especially when standard clinical scores are uncertain.
From www.medscape.com
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