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Refining Long-Term Prediction of Cardiovascular Risk in Diabetes - The VILDIA Score.

ABSTRACT: Cardiovascular risk assessment in patients with diabetes relies on traditional risk factors. However, numerous novel biomarkers have been found to be independent predictors of cardiovascular disease, which might significantly improve risk prediction in diabetic patients. We aimed to improve prediction of cardiovascular risk in diabetic patients by investigating 135 evolving biomarkers. Based on selected biomarkers a clinically applicable prediction algorithm for long-term cardiovascular mortality was designed. We prospectively enrolled 864 diabetic patients of the LUdwigshafen RIsk and Cardiovascular health (LURIC) study with a median follow-up of 9.6 years. Independent risk factors were selected using bootstrapping based on a Cox regression analysis. The following seven variables were selected for the final multivariate model: NT-proBNP, age, male sex, renin, diabetes duration, Lp-PLA2 and 25-OH vitamin D3. The risk score based on the aforementioned variables demonstrated an excellent discriminatory power for 10-year cardiovascular survival with a C-statistic of 0.76 (P?

SUBMITTER: Goliasch G

PROVIDER: S-EPMC5498499 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Refining Long-Term Prediction of Cardiovascular Risk in Diabetes - The VILDIA Score.

Goliasch Georg G Silbernagel Günther G Kleber Marcus E ME Grammer Tanja B TB Pilz Stefan S Tomaschitz Andreas A Bartko Philipp E PE Maurer Gerald G Koenig Wolfgang W Niessner Alexander A März Winfried W

Scientific reports 20170705 1

Cardiovascular risk assessment in patients with diabetes relies on traditional risk factors. However, numerous novel biomarkers have been found to be independent predictors of cardiovascular disease, which might significantly improve risk prediction in diabetic patients. We aimed to improve prediction of cardiovascular risk in diabetic patients by investigating 135 evolving biomarkers. Based on selected biomarkers a clinically applicable prediction algorithm for long-term cardiovascular mortalit ...[more]

PMID: 28680124

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Project description:ImportanceLong-term cumulative systolic blood pressure (SBP) is significantly associated with increased rates of atherosclerotic cardiovascular disease (ASCVD) development independent of single SBP levels. However, published ASCVD risk prediction algorithms only include currently measured SBP.ObjectiveTo determine whether including long-term (5- and 10-year) cumulative SBP in risk equations improves the predictive ability compared with single SBP measurements.Design, setting, and participantsAdults aged 45 to 65 years at the time of risk estimation with at least 20 years of follow-up (5 and 10 years prior to risk estimation and 10 years of event follow-up). The Lifetime Risk Pooling Project included data from the following cohorts: Coronary Artery Risk Development in Young Adults Study, Atherosclerosis Risk in Communities Study, and Framingham Heart Study (both the original and offspring).ExposuresTen-year ASCVD risk, calculated using the approach of the 2013 American College of Cardiology/American Heart Association 10-year ASCVD risk equations, first with current SBP and then substituting 5- and 10-year cumulative SBP levels.Main outcomes and measuresIncident ASCVD events that occurred over 10 years of follow-up, compared with the predicted risks, using the C statistic, net reclassification index at event rate, and the integrated discrimination index.ResultsThis study included 11 767 participants with a mean (SD) age of 59.1 (4.7) years at risk estimation. A total of 6873 participants (58%) were women, and 1499 (13%) were African American. In the 10 years of follow-up from risk estimation, 1887 participants (16%) had an ASCVD event. There were no significant improvements in the C statistic when including 5- or 10-year cumulative SBP. However, the addition of cumulative SBP resulted in significant improvements in the net reclassification index at event rate (10-year net reclassification index for men, 0.04 [95% CI, 0.02-0.06]; 10-year net reclassification index for women, 0.03 [95% CI, 0.01-0.06]) and the relative integrated discrimination index (10-year relative integrated discrimination index for men, 0.12; 10-year relative integrated discrimination index for women, 0.10).Conclusions and relevanceUsing long-term measures of cumulative blood pressure, instead of single measurements, can modestly improve the ability of cardiovascular disease risk prediction models to correctly classify individuals in terms of their risk for cardiovascular disease.

Project description:BackgroundLong-term childhood cancer survivors (CCS) are at increased risk of adverse cardiovascular events; however, there is a paucity of risk-stratification tools to identify those at higher-than-normal risk.Subjects, materials, and methodsThis was a population-based study using data from the Surveillance, Epidemiology, and End Results Program (1973-2013). Long-term CCS (age at diagnosis ≤19 years, survival ≥5 years) were followed up over a median time period of 12.3 (5-40.9) years. Independent predictors of cardiovascular mortality (CVM) were combined into a risk score, which was developed in a derivation set (n = 22,374), and validated in separate patient registries (n = 6,437).ResultsIn the derivation registries, older age at diagnosis (≥10 years vs. reference group of 1-5 years), male sex, non-white race, a history of lymphoma, and a history of radiation were independently associated with an increased risk of CVM among long-term CCS (p < .05). A risk score derived from this model (Childhood and Adolescence Cancer Survivor CardioVascular score [CHACS-CV], range: 0-8) showed good discrimination for CVM (Harrell's C-index [95% confidence interval (CI)]: 0.73 [0.68-0.78], p < .001) and identified a high-risk group (CHACS-CV ≥6), with cumulative CVM incidence over 30 years of 6.0% (95% CI: 4.3%-8.1%) versus 2.6% (95% CI: 1.8%-3.7%), and 0.7% (95% CI: 0.5%-1.0%) in the mid- (CHACS-CV = 4-5) and low-risk groups (CHACS-CV ≤3), respectively (plog-rank < .001). In the validation set, the respective cumulative incidence rates were 4.7%, 3.1%, and 0.8% (plog-rank < .001).ConclusionWe propose a simple risk score that can be applied in everyday clinical practice to identify long-term CCS at increased cardiovascular risk, who may benefit from early cardiovascular screening, and risk-reduction strategies.Implications for practiceChildhood cancer survivors (CCS) are known to be at increased cardiovascular risk. Currently available prognostic tools focus on treatment-related adverse events and late development of congestive heart failure, but there is no prognostic model to date to estimate the risk of cardiovascular mortality among long-term CCS. A simple clinical tool is proposed for cardiovascular risk stratification of long-term CCS based on easily obtainable information from their medical history. This scoring system may be used as a first-line screening tool to assist health care providers in identifying those who may benefit from closer follow-up and enable timely deployment of preventive strategies.

Project description:BACKGROUND:Poor glycemic control is associated with increased risk of cardiovascular disease (CVD) in type 1 diabetes mellitus (T1DM); however, little is known about mechanisms specific to T1DM. In T1DM, myocardial injury can induce persistent cardiac autoimmunity. Chronic hyperglycemia causes myocardial injury, raising the possibility that hyperglycemia-induced cardiac autoimmunity could contribute to long-term CVD complications in T1DM. METHODS:We measured the prevalence and profiles of cardiac autoantibodies (AAbs) in longitudinal samples from the DCCT (Diabetes Control and Complications Trial) in participants with mean hemoglobin A1c (HbA1c) ?9.0% (n=83) and ?7.0% (n=83) during DCCT. We assessed subsequent coronary artery calcification (measured once during years 7-9 in the post-DCCT EDIC [Epidemiology of Diabetes Interventions and Complications] observational study), high-sensitivity C-reactive protein (measured during EDIC years 4-6), and CVD events (defined as nonfatal myocardial infarction, stroke, death resulting from CVD, heart failure, or coronary artery bypass graft) over a 26-year median follow-up. Cardiac AAbs were also measured in matched patients with type 2 diabetes mellitus with HbA1c ?9.0% (n=70) and ?7.0% (n=140) and, as a control for cardiac autoimmunity, patients with Chagas cardiomyopathy (n=51). RESULTS:Apart from HbA1c levels, the DCCT groups shared similar CVD risk factors at the beginning and end of DCCT. The DCCT HbA1c ?9.0% group showed markedly higher cardiac AAb levels than the HbA1c ?7.0% group during DCCT, with a progressive increase and decrease in AAb levels over time in the 2 groups, respectively ( P<0.001). In the HbA1c ?9.0% group, 46%, 22%, and 11% tested positive for ?1, ?2, and ?3 different cardiac AAb types, respectively, similar to patients with Chagas cardiomyopathy, compared with 2%, 1%, and 0% in the HbA1c ?7.0% group. Glycemic control was not associated with AAb prevalence in type 2 diabetes mellitus. Positivity for ?2 AAbs during DCCT was associated with increased risk of CVD events (4 of 6; hazard ratio, 16.1; 95% CI, 3.0-88.2) and, in multivariable analyses, with detectable coronary artery calcification (13 of 31; odds ratio, 60.1; 95% CI, 8.4-410.0). Patients with ?2 AAbs subsequently also showed elevated high-sensitivity C-reactive protein levels (6.0 mg/L versus 1.4 mg/L in patients with ?1 AAbs; P=0.003). CONCLUSIONS:Poor glycemic control is associated with cardiac autoimmunity in T1DM. Furthermore, cardiac AAb positivity is associated with an increased risk of CVD decades later, suggesting a role for autoimmune mechanisms in the development of CVD in T1DM, possibly through inflammatory pathways.

Project description:BackgroundIn childhood cancer survivors (CCS) at risk for heart failure, echocardiographic surveillance recommendations are currently based on anthracyclines and chest-directed radiotherapy dose. Whether the ejection fraction (EF) measured at an initial surveillance echocardiogram can refine these recommendations is unknown.ObjectivesThe purpose of this study was to assess the added predictive value of EF at >5 years after cancer diagnosis to anthracyclines and chest-directed radiotherapy dose in CCS, for the development of left ventricular dysfunction with an ejection fraction <40% (LVD40).MethodsEchocardiographic surveillance was performed in 299 CCS from the Emma Children's Hospital in the Netherlands. Cox regression models were built including cardiotoxic cancer treatment exposures with and without EF to estimate the probability of LVD40 at 10-year follow-up. Calibration, discrimination, and reclassification were assessed. Results were externally validated in 218 CCS.ResultsCumulative incidences of LVD40 at 10-year follow-up were 3.7% and 3.6% in the derivation and validation cohort, respectively. The addition of EF resulted in an integrated area under the curve increase from 0.74 to 0.87 in the derivation cohort and from 0.72 to 0.86 in the validation cohort (likelihood ratio p < 0.001). Reclassification of CCS without LVD40 improved significantly (noncase continuous net reclassification improvement 0.50; 95% confidence interval [CI]: 0.40 to 0.60). A predicted LVD40 probability ≤3%, representing 75% of the CCS, had a negative predictive value of 99% (95% CI: 98% to 100%) for LVD40 within 10 years. However, patients with midrange EF (40% to 49%) at initial screening had an incidence of LVD40 of 11% and a 7.81-fold (95% CI: 2.07- to 29.50-fold) increased risk of LV40 at follow-up.ConclusionsIn CCS, an initial surveillance EF, in addition to anthracyclines and chest-directed radiotherapy dose, improves the 10-year prediction for LVD40. Through this strategy, both the identification of low-risk survivors in whom the surveillance frequency may be reduced and a group of survivors at increased risk of LVD40 could be identified.

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Refining Long-Term Prediction of Cardiovascular Risk in Diabetes - The VILDIA Score.

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Refining Long-Term Prediction of Cardiovascular Risk in Diabetes - The VILDIA Score.

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