Minimal and Null Predictive Effects for the Most Popular Blood Biomarkers of Cardiovascular Disease

Negative findings but positive contributions in cardiovascular research

Researchers have always concluded that results that do not support the hypothesis as unimportant, unworthy, or simply not good enough for publication. However, negative findings are essential for the progress of science and its self-correcting nature. We also believe in the importance and indispensability of negative results. Therefore, in this review, we discussed the factors contributing to the publication bias of negative results and the problems to assess the factuality and validity of negative results. Moreover, we emphasized the importance of reporting negative results in cardiovascular research, including treatments, and suggest that the negative results could clarify previously controversial topics in the treatment of cardiovascular diseases and prompt the translation of research on precision cardiovascular disease prevention and treatment.

2022 Prevention of chronic non-communicable diseases in Of the Russian Federation. National guidelines

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High baseline fetuin-A levels are associated with lower atherosclerotic plaque progression as measured by 3D ultrasound

Background and aims

The glycoprotein fetuin-A has anti-inflammatory effects, increases insulin resistance and plays an important role in calcium metabolism. The aim of our study was to assess the predictive value of fetuin-A on atherosclerotic plaque progression in comparison to the established cardiovascular biomarker high sensitivity C-reactive protein (hsCRP).

Methods

In this prospective, single center-, cohort study, we included 194 patients with at least one cardiovascular risk factor or established cardiovascular disease (CVD). Over a period of 4 years, each patient underwent 3D plaque volumetry of the carotid and femoral arteries on a yearly basis. To evaluate the predictive value of biomarkers in terms of plaque progression, the baseline values of fetuin-A and hsCRP were correlated with the plaque progression from baseline to the last follow up visit.

Results

171 patients were included in the final analysis. Baseline fetuin-A levels showed a significant negative correlation with plaque progression (r = -0.244; p = 0.001). In contrast, baseline hsCRP levels showed no correlation with plaque progression (r = 0.096, p = 0.20). In the ROC-analysis, fetuin-A had a significantly better predictive value than hsCRP (fetuin-A AUC 0.67; p = 0.001 vs hsCRP AUC 0.49; p = 0.88) with an optimal cut-off value at 712 μg/ml. In patients with high fetuin A levels (>712 μg/ml), a significantly lower plaque progression was observed compared to the group with low fetuin-A levels <712 μg/ml (high fetuin-A 197 mm³ vs. low fetuin-A 279 mm³; p = 0.01).

Conclusions

Higher fetuin-A levels appear to predict lower atherosclerotic plaque progression in patients with or at risk of cardiovascular disease.

Internal-external cross-validation helped to evaluate the generalizability of prediction models in large clustered datasets

OBJECTIVE

To illustrate how to evaluate the need of complex strategies for developing generalizable prediction models in large clustered datasets.

STUDY DESIGN AND SETTING

We developed eight Cox regression models to estimate the risk of heart failure using a large population-level dataset. These models differed in the number of predictors, the functional form of the predictor effects (non-linear effects and interaction) and the estimation method (maximum likelihood and penalization). Internal-external cross-validation was used to evaluate the models' generalizability across the included general practices.

RESULTS

Among 871,687 individuals from 225 general practices, 43,987 (5.5%) developed heart failure during a median follow-up time of 5.8 years. For discrimination, the simplest prediction model yielded a good concordance statistic, which was not much improved by adopting complex strategies. Between-practice heterogeneity in discrimination was similar in all models. For calibration, the simplest model performed satisfactorily. Although accounting for non-linear effects and interaction slightly improved the calibration slope, it also led to more heterogeneity in the observed/expected ratio. Similar results were found in a second case study involving patients with stroke.

CONCLUSION

In large clustered datasets, prediction model studies may adopt internal-external cross-validation to evaluate the generalizability of competing models, and to identify promising modelling strategies.

IGFBP-1 and IGFBP-2 are associated with a decreased pulse-wave velocity in young, healthy adults

Background and aims

In healthy, young adults we analyzed a panel of cardiovascular disease related proteins in plasma and compared them with the vascular health of the subjects. The aim was to identify proteins with a relationship to the early atherosclerotic process in healthy individuals.

Methods

We employed the proximity extension assay from OLINK proteomics to analyze 92 cardiovascular disease (CVD) related proteins on 833 subjects (men and women, ages 18–26). The women were further divided into an estrogen-using group and non-users. Protein expression was analyzed using principal component analysis (PCA). The following vascular examinations were performed: Pulse-wave velocity (PWV), augmentation index (AIX), carotid-intima media thickness (cIMT).

Results

Three principal components were obtained using PCA to analyze the protein expression. None of the obtained principal components correlated significantly with AIX or cIMT. One of the components, explaining 6% of the total variance of the data, was significantly correlated with PWV. Upon examination of the proteins with the highest factor loadings on this component independently in a multivariable model, adjusting for established CVD risk biomarkers, insulin-like growth factor-binding protein 1 (IGFBP-1) and insulin-like growth factor-binding protein 2 (IGFBP-2) were found to independently, negatively correlate with PWV. Among the established risk factors included in the multivariable model, age was significantly and adversely correlated with all vascular measurements.

Conclusions

In this population of healthy, young adults, groups of CVD related proteins correlate with PWV, but not AIX or cIMT. This group of proteins, of which IGFBP-1 and IGFBP-2 were independently, negatively correlated in a multivariable model with PWV, could have benificial effects on vascular stiffness. The robust association between age and PWV, AIX and cIMT provide insight into the impact of aging on the vasculature, which is detectable even in a population of young, healthy, non-smoking individuals of ages spanning only 8 years.

Supplementary information

The online version contains supplementary material available at 10.1186/s12872-021-01914-w.

Implications of the ACC/AHA risk score for prediction of heart failure: the Rotterdam Study

BACKGROUND

Despite the growing burden of heart failure (HF), there have been no recommendations for use of any of the primary prevention models in the existing guidelines. HF was also not included as an outcome in the American College of Cardiology/American Heart Association (ACC/AHA) risk score.

METHODS

Among 2743 men and 3646 women aged ≥ 55 years, free of HF, from the population-based Rotterdam Study cohort, 4 Cox models were fitted using the predictors of the ACC/AHA, ARIC and Health-ABC risk scores. Performance of the models for 10-year HF prediction was evaluated. Afterwards, performance and net reclassification improvement (NRI) for adding NT-proBNP to the ACC/AHA model were assessed.

RESULTS

During a median follow-up of 13 years, 429 men and 489 women developed HF. The ARIC model had the highest performance [c-statistic (95% confidence interval [CI]): 0.80 (0.78; 0.83) and 0.80 (0.78; 0.83) in men and women, respectively]. The c-statistic for the ACC/AHA model was 0.76 (0.74; 0.78) in men and 0.77 (0.75; 0.80) in women. Adding NT-proBNP to the ACC/AHA model increased the c-statistic to 0.80 (0.78 to 0.83) in men and 0.81 (0.79 to 0.84) in women. Sensitivity and specificity of the ACC/AHA model did not drastically change after addition of NT-proBNP. NRI(95%CI) was - 23.8% (- 19.2%; - 28.4%) in men and - 27.6% (- 30.7%; - 24.5%) in women for events and 57.9% (54.8%; 61.0%) in men and 52.8% (50.3%; 55.5%) in women for non-events.

CONCLUSIONS

Acceptable performance of the model based on risk factors included in the ACC/AHA model advocates use of this model for prediction of HF risk in primary prevention setting. Addition of NT-proBNP modestly improved the model performance but did not lead to relevant discrimination improvement in clinical risk reclassification.

On the present and future role of Lp-PLA2 in atherosclerosis-related cardiovascular risk prediction and management

Circulating concentration and activity of secretory phospholipase A₂ (sPLA₂) and lipoprotein-associated phospholipase A₂ (Lp-PLA₂) have been proven as biomarkers of increased risk of atherosclerosis-related cardiovascular disease (ASCVD). Lp-PLA₂ might be part of the atherosclerotic process and may contribute to plaque destabilisation through inflammatory activity within atherosclerotic lesions. However, all attempts to translate the inhibition of phospholipase into clinically beneficial ASCVD risk reduction, including in randomised studies, by either non-specific inhibition of sPLA₂ (by varespladib) or specific Lp-PLA₂ inhibition by darapladib, unexpectedly failed. This gives us a strong imperative to continue research aimed at a better understanding of how Lp-PLA₂ and sPLA₂ regulate vascular inflammation and atherosclerotic plaque development. From the clinical viewpoint there is a need to establish and validate the existing and emerging novel anti-inflammatory therapeutic strategies to fight against ASCVD development, by using potentially better animal models and differently designed clinical trials in humans.

Natural products: The role and mechanism in low-density lipoprotein oxidation and atherosclerosis

Atherosclerosis is a chronic inflammatory, metabolic, and epigenetic disease, which leads to the life-threatening coronary artery disease. Emerging studies from bench to bedside have demonstrated the pivotal role of low-density lipoprotein (LDL) oxidation in the initiation and progression of atherosclerosis. This article hereby reviews oxidation mechanism of LDL, and the pro-atherogenic and biomarker role of oxidized LDL in atherosclerosis. We also review the pharmacological effects of several representative natural products (vitamin E, resveratrol, quercetin, probucol, tanshinone IIA, epigallocatechin gallate, and Lycopene) in protecting against LDL oxidation and atherosclerosis. Clinical and basic research supports the beneficial effects of these natural products in inhibiting LDL oxidation and preventing atherosclerosis, but the data are still controversial. This may be related to factors such as the population and the dosage and time of taking natural products involved in different studies. Understanding the mechanism of LDL oxidation and effect of oxidized LDL help researchers to find novel therapies against atherosclerosis.

4-Hydroxyglutamate is a novel predictor of pre-eclampsia

Background

Pre-term pre-eclampsia is a major cause of maternal and perinatal morbidity and mortality worldwide. A multi-centre randomized–controlled trial has shown that first-trimester screening followed by treatment of high-risk women with aspirin reduces the risk of pre-term pre-eclampsia. However, the biomarkers currently employed in risk prediction are only weakly associated with the outcome.

Methods

We conducted a case–cohort study within the Pregnancy Outcome Prediction study to analyse untargeted maternal serum metabolomics in samples from 12, 20, 28 and 36 weeks of gestational age (wkGA) in women with pre-eclampsia delivering at term (n = 165) and pre-term (n = 29), plus a random sample of the cohort (n = 325). We used longitudinal linear mixed models to identify candidate metabolites at 20/28 wkGA that differed by term pre-eclampsia status. Candidates were validated using measurements at 36 wkGA in the same women. We then tested the association between the 12-, 20- and 28-wkGA measurements and pre-term pre-eclampsia. We externally validated the association using 24- to 28-wkGA samples from the Born in Bradford study (25 cases and 953 controls).

Results

We identified 100 metabolites that differed most at 20/28 wkGA in term pre-eclampsia. Thirty-three of these were validated (P < 0.0005) at 36 wkGA. 4-Hydroxyglutamate and C-glycosyltryptophan were independently predictive at 36 wkGA of term pre-eclampsia. 4-Hydroxyglutamate was also predictive (area under the receiver operating characteristic curve, 95% confidence interval) of pre-term pre-eclampsia at 12 (0.673, 0.558–0.787), 20 (0.731, 0.657–0.806) and 28 wkGA (0.733, 0.627–0.839). The predictive ability of 4-hydroxyglutamate at 12 wkGA was stronger than two existing protein biomarkers, namely PAPP-A (0.567, 0.439–0.695) and placenta growth factor (0.589, 0.463–0.714). Finally, 4-hydroxyglutamate at 24–28 wkGA was positively associated with pre-eclampsia (term or pre-term) among women from the Born in Bradford study.

Conclusions

4-hydroxyglutamate is a novel biochemical predictor of pre-eclampsia that provides better first-trimester prediction of pre-term disease than currently employed protein biomarkers.

Interleukin 6 trans-signalling and risk of future cardiovascular events

Aims

The pro-inflammatory response to interleukin 6 (IL6) trans-signalling in atherosclerosis is driven by the IL6 and soluble IL6 receptor (sIL6R) binary complex. The binary IL6:sIL6R complex is inactivated by sgp130 through the formation of the ternary IL6:sIL6R:sgp130 complex. The aim of this study was to investigate if IL6 trans-signalling, estimated by a ratio between the binary and ternary complexes, associates with the risk of future cardiovascular events (CVE) in a Swedish cohort of 60-year-old men and women (n = 4232).

Methods and results

Binary and ternary complex levels expressed in nanomol/Litre were derived from serum concentrations of IL6, sIL6R, and sgp130. Cox regression models were used to assess the risk of CVE (myocardial infarction, angina pectoris, and ischaemic stroke, n = 525), expressed as hazard ratio (HR) with 95% confidence interval (CI), associated with increasing circulating levels of the three molecules and with the binary/ternary complex ratio. Estimates were adjusted for the common cardiovascular (CV) risk factors. To assess the level of IL6-trans-signalling, we estimated the binary/ternary complex ratio and then analysed the association with CVE risk. A ratio higher than the median, representing a relative excess of the active binary complex was associated with increased CVE risk (adjusted HR 1.44, 95% CI 1.21-1.72).

Conclusion

The ratio between the functional moieties of IL6 trans-signalling, IL6:sIL6R, and IL6:sIL6R:sgp130, was associated with CVE risk indicating that it could be a promising marker of CV risk and possibly be used in selecting patients for anti-inflammatory therapy.

Circulating biomarkers for long-term cardiovascular risk stratification in apparently healthy individuals from the MONICA 10 cohort

Aims

The aim of this study was to examine whether high-sensitivity C-reactive protein (hs-CRP), N-terminal pro-brain natriuretic peptide (NT-proBNP), and soluble urokinase plasminogen activator receptor (suPAR) carried incremental prognostic value in predicting cardiovascular morbidity and mortality beyond traditional risk factors in apparently healthy individuals.

Methods and results

This was a prospective population-based cohort study comprising 1951 subjects included in the 10-year follow-up of the MONItoring of trends and determinants in CArdiovascular disease (MONICA) study, between 1993 and 1994. The principal endpoint was death from cardiovascular causes. Secondary endpoints were death from any cause, coronary artery disease, heart failure, and cerebrovascular disease. Predictive capabilities of each of the three biomarkers were tested using Cox proportional-hazards regression, Harrell’s concordance index (C-index), and net reclassification improvement (NRI). Study participants were aged 41, 51, 61, or 71 years, and equally distributed between the two sexes. During a median follow-up of 18.5 years (interquartile range: 18.1–19.0), 177 (9.1%) subjects died from a cardiovascular cause. Hs-CRP (adjusted standardized hazard ratio (HR): 1.37, 95% confidence interval (CI): 1.17–1.60), NT-proBNP (HR: 1.90, 95% CI: 1.58–2.29), and suPAR (HR: 1.35, 95% CI: 1.17–1.57) were all significantly associated with cardiovascular deaths after adjustment for age, sex, smoking status, systolic blood pressure, and total cholesterol ( p < 0.001 for all). Furthermore, all three biomarkers were significantly associated with significant NRI. However, only NT-proBNP significantly raised the C-index in predicting death from cardiovascular causes when added to the risk factors (C-index 0.860 versus 0.847; p = 0.02).

Conclusions

Hs-CRP, suPAR, and particularly NT-proBNP predicted cardiovascular death and may enhance prognostication beyond traditional risk factors in apparently healthy individuals.

Diagnosis: From classification to prediction

Over the last two decades diagnostic labels have increasingly been sub-divided based on molecular and genetic 'signatures'. But this emphasis on disease sub-types defined in molecular terms, elides the central role of population-based predictive technologies in determining these new diagnoses. While molecular diagnostic sub-types might flow from the laboratory, the clinical validity of every putative diagnostic category must ultimately be tested against its predictive powers. In effect, the former logic of prognosis following diagnosis is reversed. This paper explores the emergence of this new method of diagnostic practice over the last half century.

Modified and Dysfunctional Lipoproteins in Atherosclerosis: Effectors or Biomarkers?

Atherosclerotic diseases are the leading cause of mortality in industrialized countries. Correspondingly, studying the pathogenesis of atherosclerosis and developing new methods for its diagnostic and treatment remain in the focus of current medicine and health care. This review aims to discuss the mechanistic role of low-density lipoprotein (LDL) and high-density lipoprotein (HDL) in atherogenesis. In particular, the generally accepted hypothesis about the key role of oxidized LDL in atherogenesis is questioned, and an alternative concept of multiple modification of LDL is presented. The fundamental question discussed in this review is whether LDL and HDL are effectors or biomarkers, or both. This is important for understanding whether lipoproteins are a therapeutic target or just diagnostic indicators.

Evaluating Longitudinal Associations Between Depressive Symptoms, Smoking, and Biomarkers of Cardiovascular Disease in the CARDIA Study

OBJECTIVE

The aim of the study was to evaluate associations between 15-year trajectories of co-occurring depressive symptoms and smoking with biomarkers of cardiovascular disease at year 15.

METHODS

In the Coronary Artery Risk Development in Young Adults study, we modeled trajectories of depressive symptoms (Center for Epidemiologic Studies-Depression scale [CES-D]) and smoking (cigarettes per day [CPD]) among 3614 adults followed from year 0 (ages 18-30 years) through year 15 (ages 33-45 years). Biomarkers of inflammation (high-sensitivity C-reactive protein), oxidative stress (superoxide dismutase, F2-isoprostanes), and endothelial dysfunction (soluble intercellular adhesion molecule 1, soluble P-selectin) were assessed at year 15. We conducted separate linear regression analyses with CES-D trajectory, CPD trajectory, and their interaction with each of the five biomarkers.

RESULTS

The sample was 56% women, 47% black, and 40 years old on average at year 15. The CES-D trajectory by CPD trajectory interaction was not associated with any of the biomarkers (all p's > .01). Removing the interaction term, CES-D trajectory was associated with inflammation: higher levels of high-sensitivity C-reactive protein were observed in the subthreshold (β = 0.57, p = .004) and increasing depressive symptoms (β = 1.36, p < .001) trajectories compared with the no depression trajectory. CPD trajectory was associated with oxidative stress and endothelial dysfunction: compared with never smokers, heavy smokers had significantly higher levels of F2-isoprostanes (β = 6.20, p = .001), soluble intercellular adhesion molecule 1 (β = 24.98, p < .001), and soluble P-selectin (β = 2.91, p < .001).

CONCLUSIONS

Co-occurring depressive symptoms and smoking do not seem to synergistically convey risk for cardiovascular disease via processes of inflammation, oxidative stress, or endothelial dysfunction. Nonetheless, these results advance our understanding of the complex relationships between modifiable risk factors and chronic disease.

New technological devices for the assessment of systemic inflammation in the primary prevention of cardiovascular disease

PURPOSE OF REVIEW

The prediction of cardiovascular disease (CVD) events is of strategic importance for the primary prevention of one of the big killers in the world. Predictive models have a history of decades, but still the desired accuracy is not reached by any of the existing models. The inclusion of inflammatory factors in the models did not increase their accuracy. In this review, we discuss the possible reasons for that failure and we propose a paradigm shift.

RECENT FINDINGS

Systemic inflammation is a very volatile phenomenon. The blood concentration of inflammatory biomarkers may change considerably in one individual with a timescale of seconds. Sudden changes in environmental conditions can trigger rapid modifications in the inflammatory profile of an individual. In routine clinical practice, the blood tests for inflammation are carried out at one point in time, not in standard environmental conditions, and are therefore inadequate.

SUMMARY

We have to direct CVD research toward the understanding of the synchronic relationship between external environmental conditions and internal physiological reactions. CVD risk assessment must be carried out by using continuous real-time monitoring of external and internal parameters together, something that may become possible with the advent of new technological devices.

Increased Levels of Circulating Fatty Acids Are Associated with Protective Effects against Future Cardiovascular Events in Nondiabetics

Cardiovascular disease (CVD) is a major cause of morbidity and mortality worldwide, particularly in individuals with diabetes. The current study objective was to determine the circulating metabolite profiles associated with the risk of future cardiovascular events, with emphasis on diabetes status. Nontargeted metabolomics analysis was performed by LC-HRMS in combination with targeted quantification of eicosanoids and endocannabinoids. Plasma from 375 individuals from the IMPROVE pan-European cohort was included in a case-control study design. Following data processing, the three metabolite data sets were concatenated to produce a single data set of 267 identified metabolites. Factor analysis identified six factors that described 26.6% of the variability in the given set of predictors. An association with cardiovascular events was only observed for one factor following adjustment (p = 0.026). From this factor, we identified a free fatty acid signature (n = 10 lipids, including saturated, monounsaturated, and polyunsaturated fatty acids) that was associated with lower risk of future cardiovascular events in nondiabetics only (OR = 0.65, 0.27-0.80 95% CI, p = 0.030), whereas no association was observed among diabetic individuals. These observations support the hypothesis that increased levels of circulating omega-6 and omega-3 fatty acids are associated with protective effects against future cardiovascular events. However, these effects were only observed in the nondiabetic population, further highlighting the need for patient stratification in clinical investigations.

Improvement of myocardial infarction risk prediction via inflammation-associated metabolite biomarkers

OBJECTIVE

The comprehensive assaying of low-molecular-weight compounds, for example, metabolomics, provides a unique tool to uncover novel biomarkers and understand pathways underlying myocardial infarction (MI). We used a targeted metabolomics approach to identify biomarkers for MI and evaluate their involvement in the pathogenesis of MI.

METHODS AND RESULTS

Using three independent, prospective cohorts (KORA S4, KORA S2 and AGES-REFINE), totalling 2257 participants without a history of MI at baseline, we identified metabolites associated with incident MI (266 cases). We also investigated the association between the metabolites and high-sensitivity C reactive protein (hsCRP) to understand the relation between these metabolites and systemic inflammation. Out of 140 metabolites, 16 were nominally associated (p<0.05) with incident MI in KORA S4. Three metabolites, arginine and two lysophosphatidylcholines (LPC 17:0 and LPC 18:2), were selected as biomarkers via a backward stepwise selection procedure in the KORA S4 and were significant (p<0.0003) in a meta-analysis comprising all three studies including KORA S2 and AGES-REFINE. Furthermore, these three metabolites increased the predictive value of the Framingham risk score, increasing the area under the receiver operating characteristic score in KORA S4 (from 0.70 to 0.78, p=0.001) and AGES-REFINE study (from 0.70 to 0.76, p=0.02), but was not observed in KORA S2. The metabolite biomarkers attenuated the association between hsCRP and MI, indicating a potential link to systemic inflammatory processes.

CONCLUSIONS

We identified three metabolite biomarkers, which in combination increase the predictive value of the Framingham risk score. The attenuation of the hsCRP-MI association by these three metabolites indicates a potential link to systemic inflammation.

Single and multiple cardiovascular biomarkers in subjects without a previous cardiovascular event

Aims To assess the incremental value of biomarkers, including N-terminal prohormone of brain natriuretic peptide (NT-proBNP), high-sensitivity troponin T (hs-TnT), high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), growth differentiation factor 15 (GDF-15), and procollagen type 1 N-terminal propeptide (P1NP), in predicting incident cardiovascular events and mortality among asymptomatic individuals from the general population, beyond traditional risk factors, including fasting glucose and renal function (cystatin C), medication use, and echocardiographic measures. Methods and results Prospective population-based cohort study of 1324 subjects without a previous cardiovascular event, who underwent baseline echocardiography and biomarker assessment between 2002 and 2006. The clinical endpoint was the composite of myocardial infarction, invasively treated stable/unstable ischemic heart disease, heart failure, stroke, or all-cause mortality. Predictive capabilities were evaluated using Cox proportional-hazards regression, Harrell's concordance index (C-index), and net reclassification improvement. Median age was 66 (interquartile range: 60-70) years, and 413 (31%) were female. During median 8.6 (interquartile range: 8.1-9.2) follow-up years, 368 (28%) composite events occurred. NT-proBNP, hs-TnT, GDF-15, and IL-6 were significantly associated with outcome, independently of traditional risk factors, medications, and echocardiography ( p < 0.05 for all). Separate addition of NT-proBNP and GDF-15 to traditional risk factors, medications, and echocardiographic measurements provided significant improvements in discriminative ability (NT-proBNP: C-index 0.714 vs. 0.703, p = 0.03; GDF-15: C-index 0.721 vs. 0.703, p = 0.02). Both biomarkers remained significant predictors of outcome upon inclusion in the same model ( p < 0.05 for both). Conclusions NT-proBNP and GDF-15 each enhance prognostication beyond traditional risk factors, glucose levels, renal function, and echocardiography in individuals without known cardiovascular disease.

Predictive model for the development of hypertensive cardiopathy: A prospective cohort study

INTRODUCTION

Predictive models of cardiovascular conditions are useful tools for risk stratification. The high morbidity and mortality resulting from hypertensive cardiopathy creates a need for the use of tools to predict the risk of cardiovascular disease.

OBJECTIVE

To evaluate the capacity of a model based on risk factors to predict the development of hypertensive cardiopathy after ten years in patients with a diagnosis of essential arterial hypertension.

METHODS

A prospective cohort study was carried out in hypertensive patients cared for at the specialized arterial hypertension physician’s office of the Specialty Policlinic attached to “Carlos Manuel de Céspedes” Hospital, Bayamo Municipality, Granma Province, Cuba, from January 1, 2000 to December 31, 2009. A predictive model was constructed and validated through a process that included the random split of the whole sample in two parts: one for development (parameters estimation) and the other for validation.

RESULTS

The binary regression model adjusted by the “step-by-step backward method,” showed that in step six, 13 variables sufficed to estimate the risk of developing hypertensive cardiopathy. In the estimation sample, the area under the receiver operating characteristic curve obtained for the prediction of hypertensive heart disease was 0.985 (confidence interval: 0.980-0.990; p = <0.0005). In the validation sample the area under the receiver operating characteristic curve was 0.963 (confidence interval: 0.953-0, 0.973, p<0.0005). The calibration of the model was also adequate (p = 0.863).

CONCLUSIONS

The model obtained proved is a clinical and epidemiological surveillance instrument, useful to identify subjects with greater likelihood to acquire hypertensive heart disease, and to stratify their risk in the following ten-year period.

Novel Risk Markers and Risk Assessments for Cardiovascular Disease

The use of risk markers has transformed cardiovascular medicine, exemplified by the routine assessment of troponin, for both diagnosis and assessment of prognosis in patients with chest pain. Clinical risk factors form the basis for risk assessment of cardiovascular disease and the addition of biochemical, cellular, and imaging parameters offers further refinement. Identifying novel risk factors may allow greater risk stratification and a steady, but gradual progression toward precision medicine. Indeed, the generation of data in this area of research is explosive and when combined with new technologies and techniques provides the potential for more refined, targeted approaches to cardiovascular medicine. Although discussing the most recent developments in this field, this review article aims to strike a balance between novelty and validity by focusing on recent large sample-size studies that have been validated in a separate cohort in most cases. Risk markers related to atherosclerosis, thrombosis, inflammation, cardiac injury, and fibrosis are introduced in the context of their pathophysiology. Rapidly developing new areas, such as assessment of micro-RNA, are also explored. Subsequently the prognostic ability of these risk markers in coronary artery disease, heart failure, and atrial fibrillation is discussed in detail.

Worldwide Exposures to Cardiovascular Risk Factors and Associated Health Effects: Current Knowledge and Data Gaps

Information on exposure to, and health effects of, cardiovascular disease (CVD) risk factors is needed to develop effective strategies to prevent CVD events and deaths. Here, we provide an overview of the data and evidence on worldwide exposures to CVD risk factors and the associated health effects. Global comparative risk assessment studies have estimated that hundreds of thousands or millions of CVD deaths are attributable to established CVD risk factors (high blood pressure and serum cholesterol, smoking, and high blood glucose), high body mass index, harmful alcohol use, some dietary and environmental exposures, and physical inactivity. The established risk factors plus body mass index are collectively responsible for ≈9.7 million annual CVD deaths, with high blood pressure accounting for more CVD deaths than any other risk factor. Age-standardized CVD death rates attributable to established risk factors plus high body mass index are lowest in high-income countries, followed by Latin America and the Caribbean; they are highest in the region of central and eastern Europe and central Asia. However, estimates of the health effects of CVD risk factors are highly uncertain because there are insufficient population-based data on exposure to most CVD risk factors and because the magnitudes of their effects on CVDs in observational studies are likely to be biased. We identify directions for research and surveillance to better estimate the effects of CVD risk factors and policy options for reducing CVD burden by modifying preventable risk factors.

The interaction between systemic inflammation and psychosocial stress in the association with cardiac troponin elevation: A new approach to risk assessment and disease prevention

We have previously shown that there is a complex and dynamic biological interaction between acute mental stress and acute release of inflammatory factors into the blood stream in relation to heart disease. We now hypothesize that the presence of chronic psychosocial stress may modify the weight of single test results for inflammation as a predictor of heart disease. Using a cross-sectional design, 500 participants free from heart disease drawn from the Whitehall II study in UK in 2006-2008 were tested for plasma fibrinogen as an inflammatory factor, financial strain as a marker of chronic psychosocial stress, coronary calcification measured using computed tomography, and for plasma high-sensitivity cardiac troponin T (HS-CTnT) as a marker of cardiac risk. Fibrinogen concentration levels above the average were associated with a 5-fold increase in the odds of HS-CTnT positivity only among individuals with financial strain (N=208, OR=4.73, 95%CI=1.67 to 13.40, P=0.003). Fibrinogen was in fact not associated with HS-CTnT positivity in people without financial strain despite the larger size of that subsample (n=292, OR=0.84, 95%CI=0.42 to 1.67, P=0.622). A test for interaction on the full sample (N=500) showed a P value of 0.010 after adjusting for a range of demographics, health behaviours, traditional cardiovascular risk factors, psychosocial stressors, inflammatory cytokines, and coronary calcification. In conclusion, elevated fibrinogen seems to be cardio-toxic only when is combined with financial strain. Chronic psychosocial stress may modify the meaning that we should give to single test results for inflammation. Further research is needed to confirm our results.

Participant-Reported Health Status Predicts Cardiovascular and All-Cause Mortality Independent of Established and Nontraditional Biomarkers: Evidence From a Representative US Sample

Background

Participant‐reported health status is a key indicator of cardiovascular health, but its predictive value relative to traditional and nontraditional risk factors is unknown. We evaluated whether participant‐reported health status, as indexed by self‐rated health, predicted cardiovascular disease, and all‐cause mortality risk excess of 10‐year atherosclerotic cardiovascular disease (ASCVD) risk scores and 5 nontraditional risk biomarkers.

Methods and Results

Analyses used prospective observational data from the 1999–2002 National Health and Nutrition Examination Surveys among those aged 40 to 79 years (N=4677). Vital status was ascertained through 2011, during which there were 850 deaths, 206 from cardiovascular disease (CVD). We regressed CVD and all‐cause mortality on standardized values of self‐rated health in survival models, adjusting for age, sex, education, existing chronic disease, race/ethnicity, ASCVD risk, and standardized biomarkers (fibrinogen, C‐reactive protein [CRP], triglycerides, albumin, and uric acid). In sociodemographically adjusted models, a 1‐SD decrease in self‐rated health was associated with increased risk of CVD mortality (hazard ratio [HR], 1.92; 95% CI, 1.51–2.45; P<0.001), and this hazard remained strong after adjusting for ASCVD risk and nontraditional biomarkers (HR, 1.79; 95% CI, 1.42–2.26; P<0.001). Self‐rated health also predicted all‐cause mortality even after adjustment for ASCVD risk and nontraditional biomarkers (HR, 1.50; 95% CI, 1.35–1.66; P<0.001).

Conclusions

Self‐rated health provides prognostic information beyond that captured by traditional ASCVD risk assessments and by nontraditional CVD biomarkers. Consideration of self‐rated health in combination with traditional risk factors may facilitate risk assessment and clinical care.

Exposure-wide epidemiology: revisiting Bradford Hill

Fifty years after Bradford Hill published his extremely influential criteria to offer some guides for separating causation from association, we have accumulated millions of papers and extensive data on observational research that depends on epidemiologic methods and principles. This allows us to re-examine the accumulated empirical evidence for the nine criteria, and to re-approach epidemiology through the lens of exposure-wide approaches. The lecture discusses the evolution of these exposure-wide approaches and tries to use the evidence from meta-epidemiologic assessments to reassess each of the nine criteria and whether they work well as guides for causation. I argue that of the nine criteria, experiment remains important and consistency (replication) is also very essential. Temporality also makes sense, but it is often difficult to document. Of the other six criteria, strength mostly does not work and may even have to be inversed: small and even tiny effects are more plausible than large effects; when large effects are seen, they are mostly transient and almost always represent biases and errors. There is little evidence for specificity in causation in nature. Biological gradient is often unclear how it should it modeled and thus difficult to prove. Coherence remains usually unclear how to operationalize. Finally, plausibility as well as analogy do not work well in most fields of investigation, and their invocation has been mostly detrimental, although exceptions may exist.

Distinguishing bipolar from unipolar depression: the importance of clinical symptoms and illness features

BACKGROUND

Distinguishing bipolar disorder (BP) from major depressive disorder (MDD) has important relevance for prognosis and treatment. Prior studies have identified clinical features that differ between these two diseases but have been limited by heterogeneity and lack of replication. We sought to identify depression-related features that distinguish BP from MDD in large samples with replication.

METHOD

Using a large, opportunistically ascertained collection of subjects with BP and MDD we selected 34 depression-related clinical features to test across the diagnostic categories in an initial discovery dataset consisting of 1228 subjects (386 BPI, 158 BPII and 684 MDD). Features significantly associated with BP were tested in an independent sample of 1000 BPI cases and 1000 MDD cases for classifying ability in receiver operating characteristic (ROC) analysis.

RESULTS

Seven clinical features showed significant association with BPI compared with MDD: delusions, psychomotor retardation, incapacitation, greater number of mixed symptoms, greater number of episodes, shorter episode length, and a history of experiencing a high after depression treatment. ROC analyses of a model including these seven factors showed significant evidence for discrimination between BPI and MDD in an independent dataset (area under the curve = 0.83). Only two features (number of mixed symptoms, and feeling high after an antidepressant) showed an association with BPII versus MDD.

CONCLUSIONS

Our study suggests that clinical features distinguishing depression in BPI versus MDD have important classification potential for clinical practice, and should also be incorporated as 'baseline' features in the evaluation of novel diagnostic biomarkers.

Weight-of-evidence evaluation of long-term ozone exposure and cardiovascular effects

We conducted a weight-of-evidence (WoE) analysis to assess whether the current body of research supports a causal relationship between long-term ozone exposure (defined by EPA as at least 30 days in duration) at ambient levels and cardiovascular (CV) effects. We used a novel WoE framework based on the United States Environmental Protection Agency's National Ambient Air Quality Standards causal framework for this analysis. Specifically, we critically evaluated and integrated the relevant epidemiology and experimental animal data and classified a causal determination based on categories proposed by the Institute of Medicine's 2008 report, Improving the Presumptive Disability Decision-making Process for Veterans. We found that the risks of CV effects are largely null across human and experimental animal studies. The few positive associations reported in studies of CV morbidity and mortality are very small in magnitude, mainly reported in single-pollutant models, and likely attributable to bias, chance, or confounding. The few positive effects in experimental animal studies were observed mainly in ex vivo studies at high exposures, and even the in vivo findings are not likely relevant to humans. The available data also do not support a biologically plausible mechanism for the effects of ozone on the CV system. Overall, the current WoE provides no convincing case for a causal relationship between long-term exposure to ambient ozone and adverse effects on the CV system in humans, but the limitations of the available studies preclude definitive conclusions regarding a lack of causation; thus, we categorize the strength of evidence for a causal relationship between long-term exposure to ozone and CV effects as "below equipoise."

Weight-of-evidence evaluation of short-term ozone exposure and cardiovascular effects

There is a relatively large body of research on the potential cardiovascular (CV) effects associated with short-term ozone exposure (defined by EPA as less than 30 days in duration). We conducted a weight-of-evidence (WoE) analysis to assess whether it supports a causal relationship using a novel WoE framework adapted from the US EPA's National Ambient Air Quality Standards causality framework. Specifically, we synthesized and critically evaluated the relevant epidemiology, controlled human exposure, and experimental animal data and made a causal determination using the same categories proposed by the Institute of Medicine report Improving the Presumptive Disability Decision-making Process for Veterans ( IOM 2008). We found that the totality of the data indicates that the results for CV effects are largely null across human and experimental animal studies. The few statistically significant associations reported in epidemiology studies of CV morbidity and mortality are very small in magnitude and likely attributable to confounding, bias, or chance. In experimental animal studies, the reported statistically significant effects at high exposures are not observed at lower exposures and thus not likely relevant to current ambient ozone exposures in humans. The available data also do not support a biologically plausible mechanism for CV effects of ozone. Overall, the current WoE provides no convincing case for a causal relationship between short-term exposure to ambient ozone and adverse effects on the CV system in humans, but the limitations of the available studies preclude definitive conclusions regarding a lack of causation. Thus, we categorize the strength of evidence for a causal relationship between short-term exposure to ozone and CV effects as "below equipoise."

Application of credibility ceilings probes the robustness of meta-analyses of biomarkers and cancer risk

OBJECTIVES

Meta-analyses of biomarkers often present spurious significant results and large effects. We applied sensitivity analyses with the use of credibility ceilings to assess whether and how the results of meta-analyses of biomarkers and cancer risk would change.

STUDY DESIGN AND SETTING

We evaluated 98 meta-analyses, 43 (44%) of which had nominally statistically significant results. We assumed that any single study cannot give more than a maximum certainty 100 - c% (c, credibility ceiling) that the effect estimate [odds ratio (OR)] exceeds 1 (null) or 1.2.

RESULTS

Nominal statistical significance was maintained for 21 (21%) meta-analyses, for c = 10% and OR >1, and these proportions changed to 7%, 3%, and 6% with ceilings of 20%, 30%, and 40%, respectively. For ceilings for OR >1.2, the respective proportions were 37%, 21%, 7%, and 3%. Seven meta-analyses on infectious agents retained statistical significance even with a high ceiling of c = 20% for OR >1.00. Meta-analyses without other hints of bias (large between-study heterogeneity, small-study effects, excess significance) were more likely to retain statistical significance than those that had such hints of bias.

CONCLUSION

Credibility ceilings may be helpful in meta-analyses of biomarkers to understand the robustness of the results to different levels of uncertainty.

Biomarkers of tobacco smoke exposure

Diseases and death caused by exposure to tobacco smoke have become the single most serious preventable public health concern. Thus, biomarkers that can monitor tobacco exposure and health effects can play a critical role in tobacco product regulation and public health policy. Biomarkers of exposure to tobacco toxicants are well established and have been used in population studies to establish public policy regarding exposure to second-hand smoke, an example being the nicotine metabolite cotinine, which can be measured in urine. Biomarkers of biological response to tobacco smoking range from those indicative of inflammation to mRNA and microRNA patterns related to tobacco use and/or disease state. Biomarkers identifying individuals with an increased risk for a pathological response to tobacco have also been described. The challenge for any novel technology or biomarker is its translation to clinical and/or regulatory application, a process that requires first technical validation of the assay and then careful consideration of the context the biomarker assay may be used in the regulatory setting. Nonetheless, the current efforts to investigate new biomarker of tobacco smoke exposure promise to offer powerful new tools in addressing the health hazards of tobacco product use. This review will examine such biomarkers, albeit with a focus on those related to cigarette smoking.

External validation of new risk prediction models is infrequent and reveals worse prognostic discrimination

OBJECTIVES

To evaluate how often newly developed risk prediction models undergo external validation and how well they perform in such validations.

STUDY DESIGN AND SETTING

We reviewed derivation studies of newly proposed risk models and their subsequent external validations. Study characteristics, outcome(s), and models' discriminatory performance [area under the curve, (AUC)] in derivation and validation studies were extracted. We estimated the probability of having a validation, change in discriminatory performance with more stringent external validation by overlapping or different authors compared to the derivation estimates.

RESULTS

We evaluated 127 new prediction models. Of those, for 32 models (25%), at least an external validation study was identified; in 22 models (17%), the validation had been done by entirely different authors. The probability of having an external validation by different authors within 5 years was 16%. AUC estimates significantly decreased during external validation vs. the derivation study [median AUC change: -0.05 (P < 0.001) overall; -0.04 (P = 0.009) for validation by overlapping authors; -0.05 (P < 0.001) for validation by different authors]. On external validation, AUC decreased by at least 0.03 in 19 models and never increased by at least 0.03 (P < 0.001).

CONCLUSION

External independent validation of predictive models in different studies is uncommon. Predictive performance may worsen substantially on external validation.

Biomarker tests for risk assessment in coronary artery disease: will they change clinical practice?

The clinical significance and economic impact of coronary artery disease has triggered major research efforts into the discovery of novel biomarkers for risk stratification in primary and secondary prevention and then the development of assays suitable for routine measurement. Nevertheless, the clinical impact of these novel biomarkers for risk stratification is still limited because they do not add substantially to traditional risk factors and they only modestly-even with a multimarker approach-improve risk stratification and patient reclassification. The most useful markers appear to be high-sensitivity C-reactive protein, natriuretic peptides, and, eventually, high-sensitivity cardiac troponins. Further research is clearly needed.

Cardiac biomarkers in the prediction of risk in the non-cardiac surgery setting

B-Type natriuretic peptides and troponin measurements have potential in predicting risk in patients undergoing non-cardiac surgery. Using the American Heart Association framework for the evaluation of novel biomarkers, we review the current evidence supporting the peri-operative use of these two biomarkers. In patients having major non-cardiac surgery who are risk stratified using clinical risk scores, the measurement of natriuretic peptides and troponin, both before and after surgery, significantly improves risk stratification. However, only pre- and postoperative natriuretic peptide measurement and postoperative troponin measurement have shown clinical utility. It is now important for trials to be conducted to determine whether integrating pre- and postoperative natriuretic peptide and postoperative troponin measurement into clinical practice is able to improve clinical outcomes in patients undergoing non-cardiac surgery.

Perioperative cardiac biomarkers: the utility and timing

PURPOSE OF REVIEW

We presume that biomarkers will improve identification of patients at risk, leading to interventions and treatments that reduce perioperative adverse events. Risk stratification is multifactorial, and a biomarker must add information to this process, thereby redistributing patients to either higher or lower risk categories, to improve the allocation of expensive and risky interventions. This review focuses on the utility of three cardiac biomarkers in perioperative management.

RECENT FINDINGS

Using newly defined epidemiologic criteria, three distinct molecules, brain natriuretic peptide (BNP), troponin (cTn), and glycosylated hemoglobin (HbA1c) emerge as potentially useful in perioperative medicine. A meta-analysis shows, in vascular surgery, BNP improves risk stratification. Four articles highlight the utility of postoperative cTn measurements in cases of myocardial injury. These articles show that most injury is not infarction, and they present preliminary evidence of the populations that will benefit from structured surveillance protocols. HbA1c is shown to improve the prediction of mortality, but there are questions whether this risk is modifiable.

SUMMARY

The findings here suggest an expanded role for postoperative cTn surveillance; however, the precise populations that benefit, or the interventions required, are not yet defined. The encouraging data for the other two biomarkers need more investigations before adopting them into routine clinical use.

Postoperative B-type natriuretic peptide for prediction of major cardiac events in patients undergoing noncardiac surgery: systematic review and individual patient meta-analysis

BACKGROUND

It is unclear whether postoperative B-type natriuretic peptides (i.e., BNP and N-terminal proBNP) can predict cardiovascular complications in noncardiac surgery.

METHODS

The authors undertook a systematic review and individual patient data meta-analysis to determine whether postoperative BNPs predict postoperative cardiovascular complications at 30 and 180 days or more.

RESULTS

The authors identified 18 eligible studies (n = 2,051). For the primary outcome of 30-day mortality or nonfatal myocardial infarction, BNP of 245 pg/ml had an area under the curve of 0.71 (95% CI, 0.64-0.78), and N-terminal proBNP of 718 pg/ml had an area under the curve of 0.80 (95% CI, 0.77-0.84). These thresholds independently predicted 30-day mortality or nonfatal myocardial infarction (adjusted odds ratio [AOR] 4.5; 95% CI, 2.74-7.4; P < 0.001), mortality (AOR, 4.2; 95% CI, 2.29-7.69; P < 0.001), cardiac mortality (AOR, 9.4; 95% CI, 0.32-254.34; P < 0.001), and cardiac failure (AOR, 18.5; 95% CI, 4.55-75.29; P < 0.001). For greater than or equal to 180-day outcomes, natriuretic peptides independently predicted mortality or nonfatal myocardial infarction (AOR, 3.3; 95% CI, 2.58-4.3; P < 0.001), mortality (AOR, 2.2; 95% CI, 1.67-86; P < 0.001), cardiac mortality (AOR, 2.1; 95% CI, 0.05-1,385.17; P < 0.001), and cardiac failure (AOR, 3.5; 95% CI, 1.0-9.34; P = 0.022). Patients with BNP values of 0-250, greater than 250-400, and greater than 400 pg/ml suffered the primary outcome at a rate of 6.6, 15.7, and 29.5%, respectively. Patients with N-terminal proBNP values of 0-300, greater than 300-900, and greater than 900 pg/ml suffered the primary outcome at a rate of 1.8, 8.7, and 27%, respectively.

CONCLUSIONS

Increased postoperative BNPs are independently associated with adverse cardiac events after noncardiac surgery.

Validity of self-reported adult secondhand smoke exposure

OBJECTIVES

Exposure of adults to secondhand smoke (SHS) has immediate adverse effects on the cardiovascular system and causes coronary heart disease. The current study evaluated brief self-report screening measures for accurately identifying adult cardiology patients with clinically significant levels of SHS exposure in need of intervention.

DESIGN AND SETTING

A cross-sectional study conducted in a university-affiliated cardiology clinic and cardiology inpatient service.

PATIENTS

Participants were 118 non-smoking patients (59% male, mean age=63.6 years, SD=16.8) seeking cardiology services.

MAIN OUTCOME MEASURES

Serum cotinine levels and self-reported SHS exposure in the past 24 h and 7 days on 13 adult secondhand exposure to smoke (ASHES) items.

RESULTS

A single item assessment of SHS exposure in one's own home in the past 7 days was significantly correlated with serum cotinine levels (r=0.41, p<0.001) with sensitivity ≥75%, specificity >85% and correct classification rates >85% at cotinine cut-off points of >0.215 and >0.80 ng/mL. The item outperformed multi-item scales, an assessment of home smoking rules, and SHS exposure assessed in other residential areas, automobiles and public settings. The sample was less accurate at self-reporting lower levels of SHS exposure (cotinine 0.05-0.215 ng/mL).

CONCLUSIONS

The single item ASHES-7d Home screener is brief, assesses recent SHS exposure over a week's time, and yielded the optimal balance of sensitivity and specificity. The current findings support use of the ASHES-7d Home screener to detect SHS exposure and can be easily incorporated into assessment of other major vital signs in cardiology.