Prognostic value of 12 novel cardiological biomarkers in stable coronary artery disease. A 10-year follow-up of the placebo group of the Copenhagen CLARICOR trial (original) (raw)
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Journal of the American College of Cardiology, 2017
Currently, there is no generally accepted model to predict outcomes in stable coronary heart disease (CHD). This study evaluated and compared the prognostic value of biomarkers and clinical variables to develop a biomarker-based prediction model in patients with stable CHD. In a prospective, randomized trial cohort of 13,164 patients with stable CHD, we analyzed several candidate biomarkers and clinical variables and used multivariable Cox regression to develop a clinical prediction model based on the most important markers. The primary outcome was cardiovascular (CV) death, but model performance was also explored for other key outcomes. It was internally bootstrap validated, and externally validated in 1,547 patients in another study. During a median follow-up of 3.7 years, there were 591 cases of CV death. The 3 most important biomarkers were N-terminal pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and low-density lipoprotein cholestero...
Circulation. Cardiovascular genetics, 2015
S everal predictive models are currently being used for risk stratification and clinical decision-making in cardiovascular medicine and primary healthcare. 1,2 Most models are based on the traditional cardiovascular risk factors (TRF), that is, age, sex, blood pressure, total cholesterol, high-density lipoprotein cholesterol, and smoking status, and with the estimated 10-year risk of either cardiovascular mortality or event rate as outcome. However, it is evident that the traditional risk factors do not adequately reflect all cardiovascular risk because the majority of individuals who experience a first time cardiovascular event have adverse levels in <2 traditional risk factors and are misidentified as being at low risk. 3 Both the successes and shortcomings of the traditional risk factors have stimulated research into identifying additional biomarkers, that is, biological signals, which can be used to improve on current cardiovascular disease risk models, or are indicators of progressive subclinical disease and, as such, would have utility in predicting cardiovascular event risk, improve on traditional predictive models, and lead to more accurate treatment decisions. Blood-based biomarkers that can be easily integrated into patient management in the primary care setting are particularly desirable. Of the <60 different proteins screened to date, only 3, C-reactive protein (CRP), N-terminal prohormone of brain natriuretic peptide, and cardiac troponin I, have been shown, in combination only, to add incremental value to TRF-based predictive models of first-time CVD. 4 However, their clinical utility in preventive cardiology has not been clearly established. CRP, like other acute phase proteins, such as fibrinogen, is widely recognized to be a marker of a general inflammatory state that contributes to cardiovascular Background-Identification of individuals with high risk for first-ever myocardial infarction (MI) can be improved. The objectives of the study were to survey multiple protein biomarkers for association with the 10-year risk of incident MI and identify a clinically significant risk model that adds information to current common risk models. Methods and Results-We used an immunoassay platform that uses a sensitive, sample-efficient molecular counting technology to measure 51 proteins in samples from the fourth survey (1994) in the Tromsø Study, a longitudinal study of men and women in Tromsø, Norway. A case control design was used with 419 first-ever MI cases (169 females/250 males) and 398 controls (244 females/154 males). Of the proteins measured, 17 were predictors of MI when considered individually after adjustment for traditional risk factors either in men, women, or both. The 6 biomarkers adjusted for traditional risk factors that were selected in a multivariable model (odds ratios [OR] per standard deviation) using a stepwise procedure were apolipoprotein B/apolipoprotein A1 ratio (1.40), kallikrein (0.73), lipoprotein a (1.29), matrix metalloproteinase 9 (1.30), the interaction term IP-10/CXCL10×women (0.69), and the interaction term thrombospondin 4×men (1.38). The composite risk of these biomarkers added significantly to the traditional risk factor model with a net reclassification improvement of 14% (P=0.0002), whereas the receiver operating characteristic area increased from 0.757 to 0.791, P=0.0004. Conclusions-Novel protein biomarker models improve identification of 10-year MI risk above and beyond traditional risk factors with 14% better allocation to either high or low risk group.
International journal of cardiology, 2015
In patients with stable coronary heart disease (CHD), we aimed to assess 1. the prognostic power of biomarkers reflecting haemodynamics, micronecrosis, inflammation, coagulation, lipids, neurohumoral activity, and renal function; 2. whether changes in concentrations of these biomarkers over 12months affected subsequent CHD risk; and 3. whether pravastatin modified the change in biomarker concentrations and this influenced the risk of future events. In the LIPID study, 9014 patients were randomised to pravastatin 40mg or placebo 3-36months after an acute coronary syndrome. Eight biomarkers were measured at baseline (n=7863) and 12months later (n=6434). During a median of 6.0 (IQR 5.5-6.5) years follow-up, 1100 CHD-related deaths and nonfatal myocardial infarctions occurred, 694 after biomarker measurement at 12months. Baseline BNP, CRP, cystatin C, D-dimer, midregional pro-adrenomedullin, and sensitive troponin I predicted recurrent CHD events. In a multivariable model, sensitive tro...
Prognostic biomarkers in cardiovascular diseases
International journal of health sciences
The use of biomarkers as a reliable and reproducible indicative of the risk, severity, and progression of cardiovascular diseases (CVDs) may greatly enhance the prognostic capability of primary healthcare clinicians. In primary healthcare, the realistic and wise use of reliable biomarkers could minimize the time and costs for effective diagnosis and suitable personalized therapy for CVD patients. Therefore, the aim of the present scoping review is to evaluate the prognostic significance of biomarkers in the progression and monitoring of CVDs. The review was conducted according to the PRISMA-ScR guidelines. Eight databases were searched for articles published as of June 2021 using search terms: cardiovascular diseases AND biomarkers AND prognosis. A total of 21 studies were included in this scoping review. This review identified biomarkers BNP, cTnT yielded better accuracy of disease progression prediction in ACS and HF respectively. The availability of CVDs prognostic biomarkers in ...
Clinical Chemistry, 2007
We investigated multiple biomarkers of various pathophysiologic pathways to determine their relationships with adverse outcomes in patients presenting with symptoms of acute coronary syndrome. Methods: We obtained plasma specimens from 457 patients on admission and measured 7 biomarkers: myeloperoxidase (MPO), soluble CD40 ligand (CD40L), placental growth factor (PlGF), metalloproteinase-9 (MMP-9), high-sensitivity C-reactive protein (hsCRP), cardiac troponin I (cTnI), and N-terminal pro-B-type natriuretic peptide (NT-proBNP). We used the Modification of Diet in Renal Disease formula to calculate the estimated glomerular filtration rate (eGFR). Endpoints were cardiac events (myocardial infarction, percutaneous coronary intervention, coronary artery bypass graft, cardiac death) and all-cause mortality. We estimated cumulative event rates over a 4-month period with the Kaplan-Meier method and relative risk (RR) with the Cox proportional hazards model. Results: Patients with increased PlGF, NT-proBNP, hsCRP, or cTnI or decreased eGFR had 11% to 20% higher all-cause mortality rates than patients with concentrations within reference intervals: 20.4% (eGFR), 16.0% (PlGF), 15.8% (hsCRP), 12.7% (NT-proBNP), and 11.3% (cTnI; all P <0.03). No differences in mortality rates were observed between those with increased vs normal concentrations of MPO, CD40L, or MMP-9. Decreased eGFR (RR 3.4, P ؍ 0.004) and increased NT-proBNP (RR 7.9, P ؍ 0.04) were independently predictive of mortality, and PlGF (RR 2.0, P ؍ 0.08) approached significance. Patients with increased NT-proBNP (12.3%) or cTnI (33.8%) had higher cardiac event rates (each P <0.02), with increased MPO (11.1%) showing a trend (P ؍ 0.09). Patients in whom both cTnI and MPO were increased had a cardiac event rate of 43%. Conclusion: Multiple biomarkers that are likely indicative of different underlying pathophysiologic mechanisms are independently predictive of increased risk for adverse events in patients with acute coronary syndrome.