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.

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.

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%.

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.

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.

Improving 10-year cardiovascular risk prediction in apparently healthy people: flexible addition of risk modifiers on top of SCORE2.

AIMS: In clinical practice, factors associated with cardiovascular disease (CVD) like albuminuria, education level, or coronary artery calcium (CAC) are often known, but not incorporated in cardiovascular risk prediction models. The aims of the current study were to evaluate a methodology for the flexible addition of risk modifying characteristics on top of SCORE2 and to quantify the added value of several clinically relevant risk modifying characteristics. METHODS AND RESULTS: Individuals without previous CVD or DM were included from the UK Biobank; Atherosclerosis Risk in Communities (ARIC); Multi-Ethnic Study of Atherosclerosis (MESA); European Prospective Investigation into Cancer, The Netherlands (EPIC-NL); and Heinz Nixdorf Recall (HNR) studies (n = 409 757) in whom 16 166 CVD events and 19 149 non-cardiovascular deaths were observed over exactly 10.0 years of follow-up. The effect of each possible risk modifying characteristic was derived using competing risk-adjusted Fine and Gray models. The risk modifying characteristics were applied to individual predictions with a flexible method using the population prevalence and the subdistribution hazard ratio (SHR) of the relevant predictor. Risk modifying characteristics that increased discrimination most were CAC percentile with 0.0198 [95% confidence interval (CI) 0.0115; 0.0281] and hs-Troponin-T with 0.0100 (95% CI 0.0063; 0.0137). External validation was performed in the Clinical Practice Research Datalink (CPRD) cohort (UK, n = 518 015, 12 675 CVD events). Adjustment of SCORE2-predicted risks with both single and multiple risk modifiers did not negatively affect calibration and led to a modest increase in discrimination [0.740 (95% CI 0.736-0.745) vs. unimproved SCORE2 risk C-index 0.737 (95% CI 0.732-0.741)]. CONCLUSION: The current paper presents a method on how to integrate possible risk modifying characteristics that are not included in existing CVD risk models for the prediction of CVD event risk in apparently healthy people. This flexible methodology improves the accuracy of predicted risks and increases applicability of prediction models for individuals with additional risk known modifiers.

Heart disease is a major health concern worldwide, and predicting an individual's risk for developing heart disease is an important tool for prevention. Current risk prediction models often use factors such as age, gender, smoking, and blood pressure, but other factors like education level, albuminuria (protein in the urine), and coronary artery calcium (CAC) may also affect an individual's risk. The aim of this study was to develop a new method for using these additional risk factors for predicting risk even more accurately. The researchers used data from several large studies that included over 400 000 apparently healthy individuals who were followed for 10 years. They examined the effect of various risk factors on cardiovascular disease (CVD) risk using a statistical model. They found that adding coronary scan ('CAC score'); NT-proBNP, a biomarker of heart strain; and hs-Troponin-T, a marker of heart damage, to the existing risk prediction model (SCORE2) improved the accuracy of predicted CVD risk. The key findings are: The methods presented in the current study can help to add additional risk factors to predictions of existing models, such as SCORE2. This flexible method may help identify individuals who are at higher risk for CVD and guide prevention strategies.

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.

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.

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.

Redefining clinical venous thromboembolism phenotypes: a novel approach using latent class analysis.

BACKGROUND: Patients with venous thromboembolism (VTE) are commonly classified by the presence or absence of provoking factors at the time of VTE to guide treatment decisions. This approach may not capture the heterogeneity of the disease and its prognosis. OBJECTIVES: To evaluate clinically important novel phenotypic clusters among patients with VTE without cancer and to explore their association with anticoagulant treatment and clinical outcomes. METHODS: Latent class analysis was performed with 18 baseline clinical variables in 3062 adult patients with VTE without active cancer participating in PREFER in VTE, a noninterventional disease registry. The derived latent classes were externally validated in a post hoc analysis of Hokusai-VTE (n = 6593), a randomized trial comparing edoxaban with warfarin. The associations between cluster membership and anticoagulant treatment, recurrent VTE, bleeding, and mortality after initial treatment were studied. RESULTS: The following 5 clusters were identified: young men cluster (n = 1126, 37%), young women cluster (n = 215, 7%), older people cluster (n = 1106, 36%), comorbidity cluster (n = 447, 15%), and history of venous thromboembolism cluster (n = 168, 5%). Patient characteristics varied by age, sex, medical history, and treatment patterns. Consistent clusters were evident on external validation. In Cox proportional hazard models, recurrence risk was lower in the young women cluster (hazard ratio [HR], 0.27; 95% CI, 0.12-0.61) compared with the comorbidity cluster, after adjusting for extended anticoagulation. The risk of bleeding was lower in young men, young women, and older people clusters (HR, 0.50; 95% CI, 0.38-0.66; HR, 0.23; 95% CI, 0.11-0.46; and HR, 0.55; 95% CI 0.41-0.73, respectively). CONCLUSION: The heterogeneity of VTE cases extends beyond the distinction between provoked and unprovoked VTE.

Estimating Bleeding Risk in Patients with Cancer-Associated Thrombosis: Evaluation of Existing Risk Scores and Development of a New Risk Score.

BACKGROUND: Bleeding risk is highly relevant for treatment decisions in cancer-associated thrombosis (CAT). Several risk scores exist, but have never been validated in patients with CAT and are not recommended for practice. OBJECTIVES: To compare methods of estimating clinically relevant (major and clinically relevant nonmajor) bleeding risk in patients with CAT: (1) existing risk scores for bleeding in venous thromboembolism, (2) pragmatic classification based on cancer type, and (3) new prediction model. METHODS: In a posthoc analysis of the Hokusai VTE Cancer study, a randomized trial comparing edoxaban with dalteparin for treatment of CAT, seven bleeding risk scores were externally validated (ACCP-VTE, HAS-BLED, Hokusai, Kuijer, Martinez, RIETE, and VTE-BLEED). The predictive performance of these scores was compared with a pragmatic classification based on cancer type (gastrointestinal; genitourinary; other) and a newly derived competing risk-adjusted prediction model based on clinical predictors for clinically relevant bleeding within 6 months after CAT diagnosis with nonbleeding-related mortality as the competing event ("CAT-BLEED"). RESULTS: Data of 1,046 patients (149 events) were analyzed. Predictive performance of existing risk scores was poor to moderate (C-statistics: 0.50-0.57; poor calibration). Internal validation of the pragmatic classification and "CAT-BLEED" showed moderate performance (respective C-statistics: 0.61; 95% confidence interval [CI]: 0.56-0.66, and 0.63; 95% CI 0.58-0.68; good calibration). CONCLUSION: Existing risk scores for bleeding perform poorly after CAT. Pragmatic classification based on cancer type provides marginally better estimates of clinically relevant bleeding risk. Further improvement may be achieved with "CAT-BLEED," but this requires external validation in practice-based settings and with other DOACs and its clinical usefulness is yet to be demonstrated.

Risk Stratification in Patients with Ischemic Stroke and Residual Cardiovascular Risk with Current Secondary Prevention.

PURPOSE: Suboptimal secondary prevention in patients with stroke causes a remaining cardiovascular risk desirable to reduce. We have validated a prognostic model for secondary preventive settings and estimated future cardiovascular risk and theoretical benefit of reaching guideline recommended risk factor targets. PATIENTS AND METHODS: The SMART-REACH (Secondary Manifestations of Arterial Disease-Reduction of Atherothrombosis for Continued Health) model for 10-year and lifetime risk of cardiovascular events was applied to 465 patients in the Norwegian Cognitive Impairment After Stroke (Nor-COAST) study, a multicenter observational study with two-year follow-up by linkage to national registries for cardiovascular disease and mortality. The residual risk when reaching recommended targets for blood pressure, low-density lipoprotein cholesterol, smoking cessation and antithrombotics was estimated. RESULTS: In total, 11.2% had a new event. Calibration plots showed adequate agreement between estimated and observed 2-year prognosis (C-statistics 0.63, 95% confidence interval 0.55-0.71). Median estimated 10-year risk of recurrent cardiovascular events was 42% (Interquartile range (IQR) 32-54%) and could be reduced to 32% by optimal guideline-based therapy. The corresponding numbers for lifetime risk were 70% (IQR 63-76%) and 61%. We estimated an overall median gain of 1.4 (IQR 0.2-3.4) event-free life years if guideline targets were met. CONCLUSION: Secondary prevention was suboptimal and residual risk remains elevated even after optimization according to current guidelines. Considerable interindividual variation in risk exists, with a corresponding variation in benefit from intensification of treatment. The SMART-REACH model can be used to identify patients with the largest benefit from more intensive treatment and follow-up.

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.

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.

Estimated Life Expectancy Without Recurrent Cardiovascular Events in Patients With Vascular Disease: The SMART-REACH Model.

Background In patients with vascular disease, risk models may support decision making on novel risk reducing interventions, such as proprotein convertase subtilisin/kexin type 9 inhibitors or anti-inflammatory agents. We developed and validated an innovative model to estimate life expectancy without recurrent cardiovascular events for individuals with coronary, cerebrovascular, and/or peripheral artery disease that enables estimation of preventive treatment effect in lifetime gained. Methods and Results Study participants originated from prospective cohort studies: the SMART (Secondary Manifestations of Arterial Disease) cohort and REACH (Reduction of Atherothrombosis for Continued Health) cohorts of 14 259 ( REACH Western Europe), 19 170 ( REACH North America) and 6959 ( SMART , The Netherlands) patients with cardiovascular disease. The SMART-REACH model to estimate life expectancy without recurrent events was developed in REACH Western Europe as a Fine and Gray competing risk model incorporating cardiovascular risk factors. Validation was performed in REACH North America and SMART . Outcomes were (1) cardiovascular events (myocardial infarction, stroke, cardiovascular death) and (2) noncardiovascular death. Predictors were sex, smoking, diabetes mellitus, systolic blood pressure, total cholesterol, creatinine, number of cardiovascular disease locations, atrial fibrillation, and heart failure. Calibration plots showed high agreement between estimated and observed prognosis in SMART and REACH North America. C-statistics were 0.68 (95% confidence interval, 0.67-0.70) in SMART and 0.67 (95% confidence interval, 0.66-0.68) in REACH North America. Performance of the SMART-REACH model was better compared with existing risk scores and adds the possibility of estimating lifetime gained by novel therapies. Conclusions The externally validated SMART-REACH model could be used for estimation of anticipated improvements in life expectancy without recurrent cardiovascular events in individual patients with cardiovascular disease in Western Europe and North America.