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.

Recurrent venous thromboembolism and bleeding with extended anticoagulation: the VTE-PREDICT risk score.

AIMS: Deciding to stop or continue anticoagulation for venous thromboembolism (VTE) after initial treatment is challenging, as individual risks of recurrence and bleeding are heterogeneous. The present study aimed to develop and externally validate models for predicting 5-year risks of recurrence and bleeding in patients with VTE without cancer who completed at least 3 months of initial treatment, which can be used to estimate individual absolute benefits and harms of extended anticoagulation. METHODS AND RESULTS: Competing risk-adjusted models were derived to predict recurrent VTE and clinically relevant bleeding (non-major and major) using 14 readily available patient characteristics. The models were derived from combined individual patient data from the Bleeding Risk Study, Hokusai-VTE, PREFER-VTE, RE-MEDY, and RE-SONATE (n = 15,141, 220 recurrences, 189 bleeding events). External validity was assessed in the Danish VTE cohort, EINSTEIN-CHOICE, GARFIELD-VTE, MEGA, and Tromsø studies (n = 59 257, 2283 recurrences, 3335 bleeding events). Absolute treatment effects were estimated by combining the models with hazard ratios from trials and meta-analyses. External validation in different settings showed agreement between predicted and observed risks up to 5 years, with C-statistics ranging from 0.48-0.71 (recurrence) and 0.61-0.68 (bleeding). In the Danish VTE cohort, 5-year risks ranged from 4% to 19% for recurrent VTE and 1% -19% for bleeding. CONCLUSION: The VTE-PREDICT risk score can be applied to estimate the effect of extended anticoagulant treatment for individual patients with VTE and to support shared decision-making.

Estimation of recurrent atherosclerotic cardiovascular event risk in patients with established cardiovascular disease: the updated SMART2 algorithm.

AIMS: The 10-year risk of recurrent atherosclerotic cardiovascular disease (ASCVD) events in patients with established ASCVD can be estimated with the Secondary Manifestations of ARTerial disease (SMART) risk score, and may help refine clinical management. To broaden generalizability across regions, we updated the existing tool (SMART2 risk score) and recalibrated it with regional incidence rates and assessed its performance in external populations. METHODS AND RESULTS: Individuals with coronary artery disease, cerebrovascular disease, peripheral artery disease, or abdominal aortic aneurysms were included from the Utrecht Cardiovascular Cohort-SMART cohort [n = 8355; 1706 ASCVD events during a median follow-up of 8.2 years (interquartile range 4.2-12.5)] to derive a 10-year risk prediction model for recurrent ASCVD events (non-fatal myocardial infarction, non-fatal stroke, or cardiovascular mortality) using a Fine and Gray competing risk-adjusted model. The model was recalibrated to four regions across Europe, and to Asia (excluding Japan), Japan, Australia, North America, and Latin America using contemporary cohort data from each target region. External validation used data from seven cohorts [Clinical Practice Research Datalink, SWEDEHEART, the international REduction of Atherothrombosis for Continued Health (REACH) Registry, Estonian Biobank, Spanish Biomarkers in Acute Coronary Syndrome and Biomarkers in Acute Myocardial Infarction (BACS/BAMI), the Norwegian COgnitive Impairment After STroke, and Bialystok PLUS/Polaspire] and included 369 044 individuals with established ASCVD of whom 62 807 experienced an ASCVD event. C-statistics ranged from 0.605 [95% confidence interval (CI) 0.547-0.664] in BACS/BAMI to 0.772 (95% CI 0.659-0.886) in REACH Europe high-risk region. The clinical utility of the model was demonstrated across a range of clinically relevant treatment thresholds for intensified treatment options. CONCLUSION: The SMART2 risk score provides an updated, validated tool for the prediction of recurrent ASCVD events in patients with established ASCVD across European and non-European populations. The use of this tool could allow for a more personalized approach to secondary prevention based upon quantitative rather than qualitative estimates of residual risk.

Prediction of individualized lifetime benefit from cholesterol lowering, blood pressure lowering, antithrombotic therapy, and smoking cessation in apparently healthy people.

AIMS: The benefit an individual can expect from preventive therapy varies based on risk-factor burden, competing risks, and treatment duration. We developed and validated the LIFEtime-perspective CardioVascular Disease (LIFE-CVD) model for the estimation of individual-level 10 years and lifetime treatment-effects of cholesterol lowering, blood pressure lowering, antithrombotic therapy, and smoking cessation in apparently healthy people. METHODS AND RESULTS: Model development was conducted in the Multi-Ethnic Study of Atherosclerosis (n = 6715) using clinical predictors. The model consists of two complementary Fine and Gray competing-risk adjusted left-truncated subdistribution hazard functions: one for hard cardiovascular disease (CVD)-events, and one for non-CVD mortality. Therapy-effects were estimated by combining the functions with hazard ratios from preventive therapy trials. External validation was performed in the Atherosclerosis Risk in Communities (n = 9250), Heinz Nixdorf Recall (n = 4177), and the European Prospective Investigation into Cancer and Nutrition-Netherlands (n = 25 833), and Norfolk (n = 23 548) studies. Calibration of the LIFE-CVD model was good and c-statistics were 0.67-0.76. The output enables the comparison of short-term vs. long-term therapy-benefit. In two people aged 45 and 70 with otherwise identical risk-factors, the older patient has a greater 10-year absolute risk reduction (11.3% vs. 1.0%) but a smaller gain in life-years free of CVD (3.4 vs. 4.5 years) from the same therapy. The model was developed into an interactive online calculator available via www.U-Prevent.com. CONCLUSION: The model can accurately estimate individual-level prognosis and treatment-effects in terms of improved 10-year risk, lifetime risk, and life-expectancy free of CVD. The model is easily accessible and can be used to facilitate personalized-medicine and doctor-patient communication.

Individual Treatment Effect Estimation of 2 Doses of Dabigatran on Stroke and Major Bleeding in Atrial Fibrillation.

BACKGROUND: We aimed to estimate absolute benefit and harm from treatment with dabigatran in individual patients with atrial fibrillation, and to select the optimal dose for each individual. METHODS: We derived and validated a prediction model for ischemic stroke/systemic embolism and major bleeding in patients with atrial fibrillation from the 3 treatment arms of the RE-LY trial (Randomized Evaluation of Long-Term Anticoagulation Therapy With Dabigatran Etexilate) (n=11 955 in derivation cohort, n=6158 in validation cohort). Readily available patient characteristics were included in Fine and Gray competing risk models (sex, age, smoking, antiplatelet drugs, previous vascular disease, diabetes mellitus, blood pressure, estimated glomerular filtration rate, and hemoglobin). Five-year risks for ischemic stroke/systemic embolism and major bleeding were estimated without anticoagulation therapy, and compared with high- and low-dose dabigatran. RESULTS: Model calibration was good, and discrimination was adequate with a c-statistic of 0.65 (95% CI, 0.62-0.70) for ischemic stroke/systemic embolism and 0.69 (95% CI, 0.66-0.71) for major bleeding. The 5-year absolute risk reduction for ischemic stroke/systemic embolism with dabigatran 150 mg twice daily ranged from <10% in 20% of patients to >25% in 14% of patients, and the 5-year absolute risk increase for major bleeding ranged from <5% in 53% of patients to 15% to 20% in 1% of patients. Comparing high-dose to low-dose dabigatran, the net benefit (absolute risk reduction minus absolute risk increase) was positive for 46% of patients. CONCLUSIONS: The absolute treatment benefits and harms of dabigatran in atrial fibrillation can be estimated based on readily available patient characteristics. Such treatment effect estimations can be used for shared decision making before starting dabigatran treatment and to determine the optimal dose. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT00262600.

Estimating individual lifetime benefit and bleeding risk of adding rivaroxaban to aspirin for patients with stable cardiovascular disease: results from the COMPASS trial.

AIMS: Adding rivaroxaban to aspirin in patients with stable atherosclerotic disease reduces the recurrence of cardiovascular disease (CVD) but increases the risk of major bleeding. The aim of this study was to estimate the individual lifetime treatment benefit and harm of adding low-dose rivaroxaban to aspirin in patients with stable cardiovascular disease. METHODS AND RESULTS: Patients with established CVD from the COMPASS trial (n = 27 390) and SMART prospective cohort study (n = 8139) were used. Using the pre-existing lifetime SMART-REACH model for recurrent CVD, and a newly developed Fine and Gray competing risk-adjusted lifetime model for major bleeding, individual treatment effects from adding low-dose rivaroxaban to aspirin in patients with stable CVD were estimated, expressed in terms of (i) life-years free of stroke or myocardial infarction (MI) gained; and (ii) life-years free from major bleeding lost. Calibration of the SMART-REACH model for prediction of recurrent CVD events in the COMPASS study was good. The major bleeding risk model as derived in the COMPASS trial showed good external calibration in the SMART cohort. Predicted individual gain in life expectancy free of stroke or MI from added low-dose rivaroxaban had a median of 16 months (range 1-48 months), while predicted individualized lifetime lost in terms of major bleeding had a median of 2 months (range 0-20 months). CONCLUSION: There is a wide distribution in lifetime gain and harm from adding low-dose rivaroxaban to aspirin in individual patients with stable CVD. Using these lifetime models, benefits and bleeding risk can be weighed for each individual patient, which could facilitate treatment decisions in clinical practice.

Prediction of individual life-years gained without cardiovascular events from lipid, blood pressure, glucose, and aspirin treatment based on data of more than 500 000 patients with Type 2 diabetes mellitus.

AIMS: Although group-level effectiveness of lipid, blood pressure, glucose, and aspirin treatment for prevention of cardiovascular disease (CVD) has been proven by trials, important differences in absolute effectiveness exist between individuals. We aim to develop and validate a prediction tool for individualizing lifelong CVD prevention in people with Type 2 diabetes mellitus (T2DM) predicting life-years gained without myocardial infarction or stroke. METHODS AND RESULTS: We developed and validated the Diabetes Lifetime-perspective prediction (DIAL) model, consisting of two complementary competing risk adjusted Cox proportional hazards functions using data from people with T2DM registered in the Swedish National Diabetes Registry (n = 389 366). Competing outcomes were (i) CVD events (vascular mortality, myocardial infarction, or stroke) and (ii) non-vascular mortality. Predictors were age, sex, smoking, systolic blood pressure, body mass index, haemoglobin A1c, estimated glomerular filtration rate, non- high-density lipoprotein cholesterol, albuminuria, T2DM duration, insulin treatment, and history of CVD. External validation was performed using data from the ADVANCE, ACCORD, ASCOT and ALLHAT-LLT-trials, the SMART and EPIC-NL cohorts, and the Scottish diabetes register (total n = 197 785). Predicted and observed CVD-free survival showed good agreement in all validation sets. C-statistics for prediction of CVD were 0.83 (95% confidence interval: 0.83-0.84) and 0.64-0.65 for internal and external validation, respectively. We provide an interactive calculator at www.U-Prevent.com that combines model predictions with relative treatment effects from trials to predict individual benefit from preventive treatment. CONCLUSION: Cardiovascular disease-free life expectancy and effects of lifelong prevention in terms of CVD-free life-years gained can be estimated for people with T2DM using readily available clinical characteristics. Predictions of individual-level treatment effects facilitate translation of trial results to individual patients.

The prediction of therapy-benefit for individual cardiovascular disease prevention: rationale, implications, and implementation.

PURPOSE OF REVIEW: We aim to outline the importance and the clinical implications of using predicted individual therapy-benefit in making patient-centered treatment decisions in cardiovascular disease (CVD) prevention. Therapy-benefit concepts will be illustrated with examples of patients undergoing lipid management. RECENT FINDINGS: In both primary and secondary CVD prevention, the degree of variation in individual therapy-benefit is large. An individual's therapy-benefit can be estimated by combining prediction algorithms and clinical trial data. Measures of therapy-benefit can be easily integrated into clinical practice via a variety of online calculators. Lifetime estimates (e.g., gain in healthy life expectancy) look at therapy-benefit over the course of an individual's life, and are less influenced by age than short-term estimates (e.g., 10-year absolute risk reduction). Lifetime estimates can thus identify people who could substantially benefit from early initiation of CVD prevention. Compared with current guidelines, treatment based on predicted therapy-benefit would increase eligibility for therapy among young people with a moderate risk-factor burden and individuals with a high residual risk. SUMMARY: The estimation of individual therapy-benefit is an important part of individualized medicine. Implementation tools allow for clinicians to readily estimate both short-term and lifetime therapy-benefit.

Validation of Systematic Coronary Risk Evaluation 2 (SCORE2) and SCORE2-Older Persons in the EPIC-Norfolk prospective population cohort.

AIMS: The European Systematic Coronary Risk Evaluation 2 (SCORE2) and SCORE2-Older Persons (OP) models are recommended to identify individuals at high 10-year risk for cardiovascular disease (CVD). Independent validation and assessment of clinical utility is needed. This study aims to assess discrimination, calibration, and clinical utility of low-risk SCORE2 and SCORE2-OP. METHODS AND RESULTS: Validation in individuals aged 40-69 years (SCORE2) and 70-79 years (SCORE2-OP) without baseline CVD or diabetes from the European Prospective Investigation of Cancer (EPIC) Norfolk prospective population study. We compared 10-year CVD risk estimates with observed outcomes (cardiovascular mortality, non-fatal myocardial infarction, and stroke). For SCORE2, 19 560 individuals (57% women) had 10-year CVD risk estimates of 3.7% [95% confidence interval (CI) 3.6-3.7] vs. observed 3.8% (95% CI 3.6-4.1) [observed (O)/expected (E) ratio 1.0 (95% CI 1.0-1.1)]. The area under the curve (AUC) was 0.75 (95% CI 0.74-0.77), with underestimation of risk in men [O/E 1.4 (95% CI 1.3-1.6)] and overestimation in women [O/E 0.7 (95% CI 0.6-0.8)]. Decision curve analysis (DCA) showed clinical benefit. Systematic Coronary Risk Evaluation 2-Older Persons in 3113 individuals (58% women) predicted 10-year CVD events in 10.2% (95% CI 10.1-10.3) vs. observed 15.3% (95% CI 14.0-16.5) [O/E ratio 1.6 (95% CI 1.5-1.7)]. The AUC was 0.63 (95% CI 0.60-0.65) with underestimation of risk across sex and risk ranges. Decision curve analysis showed limited clinical benefit. CONCLUSION: In a UK population cohort, the SCORE2 low-risk model showed fair discrimination and calibration, with clinical benefit for preventive treatment initiation decisions. In contrast, in individuals aged 70-79 years, SCORE2-OP demonstrated poor discrimination, underestimated risk in both sexes, and limited clinical utility.

To effectively prevent heart disease, it is important to identify individuals who are at a higher risk of developing it. Researchers have developed models that can estimate the likelihood of a healthy person developing heart disease within the next 10 years. This study, involving 22 673 healthy individuals in the UK, aimed to determine if these risk estimation models are accurate and can guide decisions about who should receive preventive treatment.

Long-term lifestyle change and risk of mortality and Type 2 diabetes in patients with cardiovascular disease.

AIMS: To quantify the relationship between self-reported, long-term lifestyle changes (smoking, waist circumference, physical activity, and alcohol consumption) and clinical outcomes in patients with established cardiovascular disease (CVD). METHODS AND RESULTS: Data were used from 2011 participants (78% male, age 57 ± 9 years) from the Utrecht Cardiovascular Cohort-Second Manifestations of ARTerial disease cohort who returned for a re-assessment visit (SMART2) after ∼10 years. Self-reported lifestyle change was classified as persistently healthy, improved, worsened, or persistently unhealthy. Cox proportional hazard models were used to quantify the relationship between lifestyle changes and the risk of (cardiovascular) mortality and incident Type 2 diabetes (T2D). Fifty-seven per cent of participants was persistently healthy, 17% improved their lifestyle, 8% worsened, and 17% was persistently unhealthy. During a median follow-up time of 6.1 (inter-quartile range 3.6-9.6) years after the SMART2 visit, 285 deaths occurred, and 99 new T2D diagnoses were made. Compared with a persistently unhealthy lifestyle, individuals who maintained a healthy lifestyle had a lower risk of all-cause mortality [hazard ratio (HR) 0.48, 95% confidence interval (CI) 0.36-0.63], cardiovascular mortality (HR 0.57, 95% CI 0.38-0.87), and incident T2D (HR 0.46, 95% CI 0.28-0.73). Similarly, those who improved their lifestyle had a lower risk of all-cause mortality (HR 0.52, 95% CI 0.37-0.74), cardiovascular mortality (HR 0.46, 95% CI 0.26-0.81), and incident T2D (HR 0.50, 95% CI 0.27-0.92). CONCLUSION: These findings suggest that maintaining or adopting a healthy lifestyle can significantly lower mortality and incident T2D risk in CVD patients. This study emphasizes the importance of ongoing lifestyle optimization in CVD patients, highlighting the potential for positive change regardless of previous lifestyle habits.

In this study, we investigated whether lifestyle changes were related to improved health outcomes in individuals with cardiovascular disease (CVD). We assessed self-reported lifestyle behaviours (smoking, waist circumference, alcohol consumption, and physical activity), at inclusion in the cohort and again ∼10 years later. The results emphasize the importance of making healthy lifestyle choices, even for individuals already diagnosed with CVD, and suggest that it is never too late to improve one's lifestyle.

Estimating uncertainty when providing individual cardiovascular risk predictions: A Bayesian survival analysis.

BACKGROUND: Cardiovascular disease (CVD) risk scores provide point estimates of individual risk without uncertainty quantification. The objective of the current study was to demonstrate the feasibility and clinical utility of calculating uncertainty surrounding individual CVD-risk predictions using Bayesian methods. METHODS AND RESULTS: Individuals with established atherosclerotic CVD were included from the Utrecht Cardiovascular Cohort - Secondary Manifestations of ARTerial disease (UCC-SMART). In 8,355 individuals, followed for median of 8.2 years (IQR 4.2-12.5), a Bayesian Weibull model was derived to predict the 10-year risk of recurrent CVD events. Model coefficients and individual predictions were very similar to that of a traditional ('frequentist') model but the Bayesian model also predicted 95% credible intervals (CIs) surrounding individual risk estimates. The median width of the individual 95%CrI was 5.3% (IQR 3.6-6.5) and 17% of the population had a 95%CrI width of 10% or greater. The uncertainty decreased with increasing sample size used for derivation of the model. Combining the Bayesian Weibull model with sampled hazard ratios based on trial reports may be used to estimate individual absolute risk reduction with uncertainty measures and the probability that a treatment option will result in a clinically relevant risk reduction. INTERPRETATION: Estimating uncertainty surrounding individual CVD risk predictions using Bayesian methods is feasible. The uncertainty regarding individual risk predictions could have several applications in clinical practice, like the comparison of different treatment options or by calculating the probability of the individual risk being below a certain treatment threshold. However, as the individual uncertainty measures only reflect sampling error and no biases in risk prediction, physicians should be familiar with the interpretation before widespread clinical adaption.

Impact of the 2021 European Society for Cardiology prevention guideline's stepwise approach for cardiovascular risk factor treatment in patients with established atherosclerotic cardiovascular disease.

AIMS: This study aimed to evaluate the stepwise approach for cardiovascular (CV) risk factor treatment as outlined by the European Society for Cardiology 2021 guidelines on CV disease (CVD) prevention in patients with established atherosclerotic CVD (ASCVD). METHODS AND RESULTS: In patients with ASCVD, included in UCC-SMART (n = 8730) and European parts of the REACH registry (n = 18 364), the 10-year CV risk was estimated using SMART2. Treatment effects were derived from meta-analyses and trials. Step 1 recommendations were LDL cholesterol (LDLc) < 1.8 mmol/L, systolic blood pressure (SBP) < 140 mmHg, using any antithrombotic medication, sodium-glucose co-transporter 2 (SGLT2) inhibition, and smoking cessation. Step 2 recommendations were LDLc < 1.4 mmol/L, SBP < 130 mmHg, dual-pathway inhibition (DPI, aspirin plus low-dose rivaroxaban), colchicine, glucagon-like peptide (GLP)-1 receptor agonists, and eicosapentaenoic acid. Step 2 was modelled accounting for Step 1 non-attainment. With current treatment, residual CV risk was 22%, 32%, and 60% in the low, moderate, and pooled (very) high European risk regions, respectively. Step 2 could prevent up to 198, 223 and 245 events per 1000 patients treated, respectively. Intensified LDLc reduction, colchicine, and DPI could be applied to most patients, preventing up to 57, 74, and 59 events per 1000 patients treated, respectively. Following Step 2, the number of patients with a CV risk of <10% could increase from 20%, 6.4%, and 0.5%, following Step 1, to 63%, 48%, and 12%, in the respective risk regions. CONCLUSION: With current treatment, residual CV risk in patients with ASCVD remains high across all European risk regions. The intensified Step 2 treatment options result in marked further reduction of residual CV risk in patients with established ASCVD. KEY FINDINGS: Guideline-recommended intensive treatment of patients with cardiovascular disease could prevent additional 198-245 new cardiovascular events for every 1000 patients treated.

Patients with established cardiovascular disease are at high risk for new cardiovascular events. The European Society of Cardiology guideline for the prevention of cardiovascular disease introduced a stepwise treatment approach. Step 1 in this approach are treatments that apply to all patients, and Step 2 are intensive treatments that can be prescribed to patients who are still at high risk of new events even with Step 1 treatments. The current study investigates the effect of Steps 1 and 2 on the risk of cardiovascular disease in 27 094 patients all across Europe. With the conventional treatments of Step 1 the risk of cardiovascular disease remains high, with a 10-year risk of new events higher than 10% in 80­99% of patients. The intensive treatment options from Step 2 could prevent additional 198­245 new cardiovascular events for every 1000 patients that are treated. With intensive treatment, up to 63% of patients could achieve a 10-year risk of new cardiovascular disease below 10%.

Effects of icosapent ethyl according to baseline residual risk in patients with atherosclerotic cardiovascular disease: results from REDUCE-IT.

BACKGROUND AND AIMS: Icosapent ethyl lowers triglycerides and significantly reduces major adverse cardiovascular events (MACE), though treatment effects may vary between individuals. This study aimed to determine the relative and absolute effects of icosapent ethyl on MACE according to baseline CVD risk in patients with atherosclerotic cardiovascular disease (ASCVD). METHODS: Participants from REDUCE-IT with ASCVD were included (n = 5,785). The primary outcome was 3-point MACE, i.e. non-fatal myocardial infarction, non-fatal stroke, or cardiovascular death. Baseline 5-year risk of MACE was estimated using the ESC guideline-recommended SMART2 risk score. Modification of the relative treatment effects of icosapent ethyl by baseline risk was assessed using Cox proportional hazards models including a treatment-by-risk interaction. Next, treatment effects were assessed stratified by quartiles of baseline risk. RESULTS: During a median follow-up of 4.8 years (interquartile range 3.2-5.3), MACE occurred in 361 vs 489 patients in the icosapent ethyl vs placebo group (95% confidence interval [CI]); hazard ratio (HR) 0.72 (0.63-0.82), absolute risk reduction (ARR) 4.4% (2.6-6.2%), number needed to treat (NNT) 23 (16-38), 5-year Kaplan-Meier estimated cumulative incidence reduction (CIR) 5.7% (3.5-7.9%). Icosapent ethyl significantly reduced MACE in all risk quartiles, with an HR (95% CI) of 0.62 (0.43-0.88), 0.66 (0.48-0.92), 0.69 (0.53-0.90), and 0.78 (0.63-0.96) respectively (p for treatment-by-risk interaction = 0.106). The ARR (95% CI) increased across risk quartiles, i.e. was 3.9% (1.0-6.8%), 4.3% (1.2-7.3%), 5.1% (1.4-8.7%), and 5.6% (1.3-10.0%) respectively. This translates to NNTs (95% CI) of 26 (15-98), 24 (14-84), 20 (11-70), and 18 (10-77). The 5-year CIR (95% CI) was 4.8% (1.3-8.2%), 5.0% (1.3-8.7%), 6.1% (1.7-10.5%), and 7.7% (2.3-13.2%) respectively. Consistent results were obtained for 5-point MACE, additionally including coronary revascularization and unstable angina. CONCLUSIONS: Among patients with ASCVD and elevated triglyceride levels, icosapent ethyl significantly reduces the risk of MACE irrespective of baseline CVD risk, though absolute benefits are largest for patients at the highest risk.

Dietary habits and compliance with dietary guidelines in patients with established cardiovascular disease.

BACKGROUND: Unhealthy dietary habits are an important risk factor for cardiovascular disease (CVD) and adopting a healthy diet is a central recommendation in CVD prevention. This study assessed the dietary habits of patients with established CVD, their compliance to dietary guidelines, and the relationship between guideline-compliance and recurrent cardiovascular event risk. METHODS: 2656 patients with established CVD from the Utrecht Cardiovascular Cohort-Secondary Manifestations of ARTerial disease (UCC-SMART) prospective cohort study, were included between 1996 and 2022. Data on dietary intake was retrospectively collected for all participants in December 2022 using a 160-item food frequency questionnaire. Compliance with dietary guidelines was quantified using an amended version of the Dutch Healthy Diet 2015 (DHD-15) index (range: 0-135). Cox proportional hazard models were used to quantify the relationship with cardiovascular events (stroke and myocardial infarction). RESULTS: Among 2656 CVD patients (77% male, mean age 59 ± 9 years), median energy intake was 1922 [IQR: 1536-2351] kcal/day. The median DHD-15 index was 81.7 [IQR 71.2-92.0], with high compliance scores for recommendations on legumes and fish, and low scores for recommendations on whole grains, red meat, processed meat, and dairy. A higher DHD-15 score was associated with lower stroke risk (HR 0.78, 95% CI 0.66-0.92 per 10-point increase) but not with myocardial infarction. CONCLUSION: Compliance with dietary guidelines was suboptimal in patients with established CVD. High compliance was associated with a clinically significant reduction in stroke risk in patients with established CVD, emphasizing the importance of dietary counseling.

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.

The relevance of competing risk adjustment in cardiovascular risk prediction models for clinical practice.

BACKGROUND: Many models developed for predicting the risk of cardiovascular disease (CVD) are adjusted for the competing risk of non-CVD mortality, which has been suggested to reduce potential overestimation of cumulative incidence in populations where the risk of competing events is high. The objective was to evaluate and illustrate the clinical impact of competing risk adjustment when deriving a CVD prediction model in a high-risk population. METHODS AND RESULTS: Individuals with established atherosclerotic CVD were included from the Utrecht Cardiovascular Cohort-Secondary Manifestations of ARTerial disease (UCC-SMART). In 8355 individuals, followed for a median of 8.2 years (IQR 4.2-12.5), two similar prediction models for the estimation of 10-year residual CVD risk were derived: with competing risk adjustment using a Fine and Gray model and without competing risk adjustment using a Cox proportional hazards model. On average, predictions were higher from the Cox model. The Cox model predictions overestimated the cumulative incidence [predicted-observed ratio 1.14 (95% CI 1.09-1.20)], which was most apparent in the highest risk quartiles and in older persons. Discrimination of both models was similar. When determining treatment eligibility on thresholds of predicted risks, more individuals would be treated based on the Cox model predictions. If, for example, individuals with a predicted risk > 20% were considered eligible for treatment, 34% of the population would be treated according to the Fine and Gray model predictions and 44% according to the Cox model predictions. INTERPRETATION: Individual predictions from the model unadjusted for competing risks were higher, reflecting the different interpretations of both models. For models aiming to accurately predict absolute risks, especially in high-risk populations, competing risk adjustment must be considered.

C-Reactive Protein and Risk of Incident Heart Failure in Patients With Cardiovascular Disease.

BACKGROUND: Patients with established cardiovascular disease (CVD) are at high risk of incident heart failure (HF), which may in part reflect the impact of systemic inflammation. OBJECTIVES: The goal of this study was to determine the association between C-reactive protein (CRP) and incident HF in patients with established CVD. METHODS: Patients from the prospective UCC-SMART (Utrecht Cardiovascular Cohort-Second Manifestations of ARTerial disease) cohort with established CVD, but without prevalent HF were included (n = 8,089). Incident HF was defined as a first hospitalization for HF. The association between baseline CRP and incident HF was assessed using Cox proportional hazards models adjusted for established risk factors (ie, age, sex, myocardial infarction, smoking, diabetes mellitus, body mass index, blood pressure, cholesterol, and kidney function). RESULTS: During a median follow-up of 9.7 years (IQR 5.4-14.1 years), 810 incident HF cases were observed (incidence rate 1.01/100 person-years). Higher CRP was independently associated with an increased risk of incident HF: HR per 1 mg/L: 1.10 (95% CI: 1.07-1.13), and for last vs first CRP quartile: 2.22 (95% CI: 1.76-2.79). The association was significant for both HF with reduced (HR: 1.09; 95% CI: 1.04-1.14) and preserved ejection fraction (HR: 1.12; 95% CI: 1.07-1.18) (P for difference = 0.137). Additional adjustment for medication use and interim myocardial infarction did not attenuate the association, and the association remained consistent beyond 15 years after the CRP measurement. CONCLUSIONS: In patients with established CVD, CRP is an independent risk marker of incident HF. These data support ongoing trial efforts to assess whether anti-inflammatory agents can reduce the burden of HF.

C-Reactive Protein and Risk of Cardiovascular Events and Mortality in Patients with Various Cardiovascular Disease Locations.

Anti-inflammatory drugs reduce the risk of cardiovascular events in patients with coronary artery disease (CAD), but less is known about the relation between inflammation and outcomes in patients with cerebrovascular disease (CeVD), peripheral artery disease (PAD), and abdominal aortic aneurysm (AAA). This study assessed the association between C-reactive protein (CRP) and clinical outcomes in patients with CAD (n = 4,517), CeVD (n = 2,154), PAD (n = 1,154), and AAA (n = 424) from the prospective Utrecht Cardiovascular Cohort-Second Manifestations of ARTerial disease study. The primary outcome was recurrent cardiovascular disease (CVD), defined as myocardial infarction, ischemic stroke, or cardiovascular death. Secondary outcomes were major adverse limb events and all-cause mortality. Associations between baseline CRP and outcomes were assessed using Cox proportional hazards models adjusted for age, sex, smoking, diabetes mellitus, body mass index, systolic blood pressure, non-high-density lipoprotein cholesterol, and glomerular filtration rate. Results were stratified by CVD location. During a median follow-up of 9.5 years, 1,877 recurrent CVD events, 887 major adverse limb events, and 2,341 deaths were observed. CRP was independently associated with recurrent CVD (hazard ratio [HR] per 1 mg/L 1.08, 95% confidence interval [CI] 1.05 to 1.10), and all secondary outcomes. Compared with the first quintile of CRP, HRs for recurrent CVD were 1.60 (95% CI 1.35 to 1.89) for the last quintile ≤10 mg/L and 1.90 (95% CI 1.58 to 2.29) for the subgroup with CRP >10 mg/L. CRP was associated with recurrent CVD in patients with CAD (HR per 1 mg/L 1.08, 95% CI 1.04 to 1.11), CeVD (HR 1.05, 95% CI 1.01 to 1.10), PAD (HR 1.08, 95% CI 1.03 to 1.13), and AAA (HR 1.08, 95% CI 1.01 to 1.15). The association between CRP and all-cause mortality was stronger for patients with CAD (HR 1.13, 95% CI 1.09 to 1.16) than for patients with other CVD locations (HRs 1.06 to 1.08; p = 0.002). Associations remained consistent beyond 15 years after the CRP measurement. In conclusion, greater CRP is independently associated with an increased risk of recurrent CVD and mortality, irrespective of previous CVD location.

Metabolic syndrome and risk of incident heart failure in non-diabetic patients with established cardiovascular disease.

BACKGROUND: In patients with established cardiovascular disease (CVD), the relation between metabolic syndrome (MetS) and incident heart failure (HF) in the absence of diabetes mellitus (DM) is largely unknown. This study assessed this relation in non-diabetic patients with established CVD. METHODS: Patients from the prospective UCC-SMART cohort with established CVD, but without DM or HF at baseline were included (n = 4653). MetS was defined according to the Adult Treatment Panel III criteria. Insulin resistance was quantified using the homeostasis model of insulin resistance (HOMA-IR). The outcome was a first hospitalization for HF. Relations were assessed using Cox proportional hazards models adjusted for established risk factors: age, sex, prior myocardial infarction (MI), smoking, cholesterol, and kidney function. RESULTS: During a median follow-up of 8.0 years, 290 cases of incident HF were observed (0.81/100 person years). MetS was significantly related to an increased risk of incident HF independent of established risk factors (hazard ratio [HR] 1.32; 95% confidence interval [CI] 1.04-1.68, HR per criterion 1.17; 95% CI 1.06-1.29), as was HOMA-IR (HR per standard deviation [SD] 1.15; 95% CI 1.03-1.29). Of the individual MetS components, only higher waist circumference independently increased the risk of HF (HR per SD 1.34; 95% CI 1.17-1.53). Relations were independent of the occurrence of interim DM and MI, and were not significantly different for HF with reduced vs preserved ejection fraction. CONCLUSION: In CVD patients without a current diagnosis of DM, MetS and insulin resistance increase the risk of incident HF independent of established risk factors.

Physical exercise volume, type, and intensity and risk of all-cause mortality and cardiovascular events in patients with cardiovascular disease: a mediation analysis.

Aims: To estimate the relation between physical exercise volume, type, and intensity with all-cause mortality and recurrent vascular events in patients with cardiovascular disease (CVD) and to quantify to what extent traditional cardiovascular risk factors mediate these relations. Methods and results: In the prospective UCC-SMART cohort (N = 8660), the associations of clinical endpoints and physical exercise volume (metabolic equivalent of task hours per week, METh/wk), type (endurance vs. endurance + resistance), and intensity (moderate vs. vigorous) were estimated using multivariable-adjusted Cox models. The proportion mediated effect (PME) through body mass index, systolic blood pressure, low-density lipoprotein cholesterol, insulin sensitivity, and systemic inflammation was assessed using structural equation models. Sixty-one percent of patients (73% male, age 61 ± 10 years, >70% receiving lipid-lowering and blood pressure-lowering medications) reported that they did not exercise. Over a median follow-up of 9.5 years [interquartile range (IQR) 5.1-14.0], 2256 deaths and 1828 recurrent vascular events occurred. The association between exercise volume had a reverse J-shape with a nadir at 29 (95% CI 24-29) METh/wk, corresponding with a HR 0.56 (95% CI 0.48-0.64) for all-cause mortality and HR 0.63 (95% CI 0.55-0.73) for recurrent vascular events compared with no exercise. Up to 38% (95% CI 24-61) of the association was mediated through the assessed risk factors of which insulin sensitivity (PME up to 12%, 95% CI 5-25) and systemic inflammation (PME up to 18%, 95% CI 9-37) were the most important. Conclusion: Regular physical exercise is significantly related with reduced risks of all-cause mortality and recurrent vascular events in patients with CVD. In this population with high rates of lipid-lowering and blood pressure--lowering medication use, exercise benefits were mainly mediated through systemic inflammation and insulin resistance.