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

AIMS: To develop and externally validate the LIFE-T1D model for the estimation of lifetime and 10-year risk of cardiovascular disease (CVD) in individuals with type 1 diabetes. MATERIALS AND METHODS: A sex-specific competing risk-adjusted Cox proportional hazards model was derived in individuals with type 1 diabetes without prior CVD from the Swedish National Diabetes Register (NDR), using age as the time axis. Predictors included age at diabetes onset, smoking status, body mass index, systolic blood pressure, glycated haemoglobin level, estimated glomerular filtration rate, non-high-density lipoprotein cholesterol, albuminuria and retinopathy. The model was externally validated in the Danish Funen Diabetes Database (FDDB) and the UK Biobank. RESULTS: During a median follow-up of 11.8 years (interquartile interval 6.1-17.1 years), 4608 CVD events and 1316 non-CVD deaths were observed in the NDR (n = 39 756). The internal validation c-statistic was 0.85 (95% confidence interval [CI] 0.84-0.85) and the external validation c-statistics were 0.77 (95% CI 0.74-0.81) for the FDDB (n = 2709) and 0.73 (95% CI 0.70-0.77) for the UK Biobank (n = 1022). Predicted risks were consistent with the observed incidence in the derivation and both validation cohorts. CONCLUSIONS: 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.

Variability in benefit from intensive insulin therapy on cardiovascular events in individuals with type 1 diabetes: A post hoc analysis of the DCCT/EDIC study.

AIM: To evaluate presence of treatment effect heterogeneity of intensive insulin therapy (INT) on occurrence of major adverse cardiovascular events (MACE) in individuals with type 1 diabetes. METHODS: In participants from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study, individual treatment effect of INT (≥3 daily insulin injections/insulin pump therapy) versus conventional therapy (once/twice daily insulin) on the risk of MACE was estimated using a penalized Cox regression model including treatment-by-covariate interaction terms. RESULTS: In 1441 participants, 120 first MACE events were observed and 1279 individuals (89%) were predicted to benefit from INT with regard to MACE risk reduction. The study population was divided into four groups based on predicted treatment effect: one group with no predicted benefit and three tertiles with predicted treatment benefit. The median absolute reduction in 30-year risk of MACE across groups of predicted treatment effect ranged from -0.2% (i.e. risk increase; interquartile range [IQR] -0.1% to -0.3%) in the group with no predicted benefit to 6.6% (i.e. risk reduction; IQR 3.8%-10.9%; number needed to treat 15) in the highest tertile of predicted benefit. The observed benefit of preventing microvascular complications was stable across all subgroups of predicted MACE benefit. CONCLUSIONS: Although INT reduces the risk of MACE in the majority of individuals with type 1 diabetes, benefit varies substantially. These individual differences in the effect of INT underline the necessity for a better understanding of the individual response to intensive treatment.

HbA1c and fasting plasma glucose levels are equally related to incident cardiovascular risk in a high CVD risk population without known diabetes.

OBJECTIVES: Type 2 diabetes (T2DM) is associated with increased risk for cardiovascular disease (CVD). Whether screen-detected T2DM, based on fasting plasma glucose (FPG) or on HbA1c, are associated with different risks of incident CVD in high-risk populations and which one is preferable for diabetes screening in these populations, remains unclear. METHODS: 8,274 high-risk CVD participants were included from the UCC-SMART cohort. Participants were divided into groups based on prior T2DM diagnosis, and combinations of elevated/non-elevated FPG and HbA1c (cut-offs at 7 mmol/L and 48 mmol/mol, respectively): Group 0: known T2DM; group 1: elevated FPG/HbA1c; group 2: elevated FPG, non-elevated HbA1c; group 3: non-elevated FPG, elevated HbA1c; group 1 + 2: elevated FPG, regardless of HbA1c; group 1 + 3: elevated HbA1c, regardless of FPG; and group 4 (reference), non-elevated FPG/HbA1c. RESULTS: During a median follow-up of 6.3 years (IQR 3.3-9.8), 712 cardiovascular events occurred. Compared to the reference (group 4), group 0 was at increased risk (HR 1.40; 95 % CI 1.16-1.68), but group 1 (HR 1.16; 95 % CI 0.62-2.18), 2 (HR 1.18; 95 % CI 0.84-1.67), 3 (HR 0.61; 95 % CI 0.15-2.44), 1 + 2 (HR 1.17; 95 % CI 0.86-1.59) and 1 + 3 (HR 1.01; 95 % CI 0.57-1.79) were not. However, spline interpolation showed a linearly increasing risk with increasing HbA1c/FPG, but did not allow for identification of other cut-off points. CONCLUSIONS: Based on current cut-offs, FPG and HbA1c at screening were equally related to incident CVD in high-risk populations without known T2DM. Hence, neither FPG, nor HbA1c, is preferential for diabetes screening in this population with respect to risk of incident CVD.

Development and validation of a lifetime prediction model for incident type 2 diabetes in patients with established cardiovascular disease: the CVD2DM model.

AIMS: Identifying patients with established cardiovascular disease (CVD) who are at high risk of type 2 diabetes (T2D) may allow for early interventions, reducing the development of T2D and associated morbidity. The aim of this study was to develop and externally validate the CVD2DM model to estimate the 10-year and lifetime risks of T2D in patients with established CVD. METHODS AND RESULTS: Sex-specific, competing risk-adjusted Cox proportional hazard models were derived in 19 281 participants with established CVD and without diabetes at baseline from the UK Biobank. The core model's pre-specified predictors were age, current smoking, family history of diabetes mellitus, body mass index, systolic blood pressure, fasting plasma glucose, and HDL cholesterol. The extended model also included HbA1c. The model was externally validated in 3481 patients from the UCC-SMART study. During a median follow-up of 12.2 years (interquartile interval 11.3-13.1), 1628 participants with established CVD were diagnosed with T2D in the UK Biobank. External validation c-statistics were 0.79 [95% confidence interval (CI) 0.76-0.82] for the core model and 0.81 (95% CI 0.78-0.84) for the extended model. Calibration plots showed agreement between predicted and observed 10-year risk of T2D. CONCLUSION: The 10-year and lifetime risks of T2D can be estimated with the CVD2DM model in patients with established CVD, using readily available clinical predictors. The model would benefit from further validation across diverse ethnic groups to enhance its applicability. Informing patients about their T2D risk could motivate them further to adhere to a healthy lifestyle.

In this study, we developed and externally validated the CVD2DM model, which predicts the 10-year and lifetime risk of type 2 diabetes (T2D) in individuals who already have cardiovascular disease (CVD). The key findings are as follows: The CVD2DM model is the first model to estimate the risk of developing T2D applicable in all patients with atherosclerotic CVD. The model is based on several factors available in clinical practice, such as age, fasting plasma glucose, family history of diabetes, and body mass index. It was developed in 19 281 patients from the UK Biobank. The model performed well in 3481 patients from the UCC-SMART study.Informing patients about their T2D risk could motivate them further to adhere to a healthy lifestyle.

Effect of adipose tissue quantity and dysfunction on the risk of cancer in individuals with and without type 2 diabetes.

OBJECTIVE: To determine the role of waist circumference and metabolic dysfunction in the risk of cancer in individuals with type 2 diabetes (T2D) and to compare this to individuals without T2D. METHODS: Individuals with (n = 1925) and without T2D (n = 10,204) were included from the UCC-SMART cohort. Incident cancer diagnoses were obtained by linkage with the Netherlands Cancer Registry. Metabolic dysfunction was defined as ≥ 3 adapted NCEP ATP-III metabolic syndrome criteria. The effects of waist circumference and metabolic dysfunction on cancer were assessed using Cox proportional hazards models, adjusted for confounders. RESULTS: During a median follow-up of 8.3 years (IQR 4.2-13.1), 1740 individuals were diagnosed with cancer. Incidence rates of total cancer were 19.3 and 15.5/1000 person-years for individuals with and without T2D, respectively. In individuals without T2D, a higher waist circumference was associated with an increased risk of colorectal (per standard deviation: HR 1.23; 95%CI 1.03-1.46), urinary tract (HR 1.28; 95%CI 1.05-1.56) and total cancer (HR 1.06; 95%CI 1.02-1.13). Metabolic dysfunction was related to an increased risk of colorectal (HR 1.35; 95%CI 1.01-1.82), lung (HR 1.37; 95%CI 1.07-1.75) and total cancer (HR 1.13; 95%CI 1.01-1.25) in individuals without T2D. In individuals with T2D, no significant associations were found. CONCLUSION: Incidence rates of cancer are higher among individuals with T2D. However, higher waist circumference and metabolic dysfunction are only associated with an increased cancer risk in patients without T2D. These findings provide novel insights into the role of metabolic dysfunction in the occurrence of cancer.

Cohort profile: the Utrecht Cardiovascular Cohort-Second Manifestations of Arterial Disease (UCC-SMART) Study-an ongoing prospective cohort study of patients at high cardiovascular risk in the Netherlands.

PURPOSE: The Utrecht Cardiovascular Cohort-Second Manifestations of Arterial Disease (UCC-SMART) Study is an ongoing prospective single-centre cohort study with the aim to assess important determinants and the prognosis of cardiovascular disease progression. This article provides an update of the rationale, design, included patients, measurements and findings from the start in 1996 to date. PARTICIPANTS: The UCC-SMART Study includes patients aged 18-90 years referred to the University Medical Center Utrecht, the Netherlands, for management of cardiovascular disease (CVD) or severe cardiovascular risk factors. Since September 1996, a total of 14 830 patients have been included. Upon inclusion, patients undergo a standardised screening programme, including questionnaires, vital signs, laboratory measurements, an ECG, vascular ultrasound of carotid arteries and aorta, ankle-brachial index and ultrasound measurements of adipose tissue, kidney size and intima-media thickness. Outcomes of interest are collected through annual questionnaires and adjudicated by an endpoint committee. FINDINGS TO DATE: By May 2022, the included patients contributed to a total follow-up time of over 134 000 person-years. During follow-up, 2259 patients suffered a vascular endpoint (including non-fatal myocardial infarction, non-fatal stroke and vascular death) and 2794 all-cause deaths, 943 incident cases of diabetes and 2139 incident cases of cancer were observed up until January 2020. The UCC-SMART cohort contributed to over 350 articles published in peer-reviewed journals, including prediction models recommended by the 2021 European Society of Cardiology CVD prevention guidelines. FUTURE PLANS: The UCC-SMART Study guarantees an infrastructure for research in patients at high cardiovascular risk. The cohort will continue to include about 600 patients yearly and follow-up will be ongoing to ensure an up-to-date cohort in accordance with current healthcare and scientific knowledge. In the near future, UCC-SMART will be enriched by echocardiography, and a food frequency questionnaire at baseline enabling the assessment of associations between nutrition and CVD and diabetes.

Insulin resistance and risk of vascular events, interventions and mortality in type 1 diabetes.

OBJECTIVE: To identify determinants associated with insulin resistance and to assess the association between insulin resistance and cardiovascular events, vascular interventions and mortality in people with type 1 diabetes at high risk of cardiovascular disease. DESIGN: Prospective cohort study. METHODS: One hundred and ninety-five people with type 1 diabetes from the Secondary Manifestations of ARTerial disease (SMART) cohort were included. Insulin resistance was quantified by the estimated glucose disposal rate (eGDR) with higher eGDR levels indicating higher insulin sensitivity (i.e. lower eGDR levels indicating higher insulin resistance). Linear regression models were used to evaluate determinants associated with eGDR. The effect of eGDR on cardiovascular events, cardiovascular events or vascular interventions (combined endpoint) and on all-cause mortality was analysed using Cox proportional hazards models adjusted for confounders. RESULTS: In 195 individuals (median follow-up 12.9 years, IQR 6.7-17.0), a total of 25 cardiovascular events, 26 vascular interventions and 27 deaths were observed. High eGDR as a marker for preserved insulin sensitivity was independently associated with a lower risk of cardiovascular events (HR: 0.75; 95% CI: 0.61-0.91), a lower risk of cardiovascular events and vascular interventions (HR: 0.74; 95% CI: 0.63-0.87) and a lower risk of all-cause mortality (HR: 0.81; 95% CI: 0.67-0.98). CONCLUSIONS: Insulin resistance as measured by eGDR is an additional risk factor for cardiovascular disease in individuals with type 1 diabetes. Modification of insulin resistance by lifestyle interventions or pharmacological treatment could be a viable therapeutic target to lower the risk of cardiovascular disease.