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Relations of biomarkers of extracellular matrix remodeling to incident cardiovascular events and mortality.

ABSTRACT: OBJECTIVE:To evaluate if biomarkers reflecting left ventricular/vascular extracellular matrix remodeling are associated with cardiovascular disease (CVD) and death in the community. METHODS AND RESULTS:In 922 Framingham Study participants (mean age, 58 years; 56% women), we related circulating concentrations of matrix metalloproteinase-9 (binary variable: detectable versus undetectable), log of tissue inhibitor of matrix metalloproteinase-1, and log of procollagen type III aminoterminal peptide (PIIINP) to incident CVD and death. On follow-up (mean, 9.9 years), 51 deaths and 81 CVD events occurred. Each SD increment of log of tissue inhibitor of matrix metalloproteinase-1 and log-PIIINP was associated with multivariable-adjusted hazards ratios of 1.72 (95% CI, 1.30 to 2.27) and 1.47 (95% CI, 1.11 to 1.96), respectively, for mortality risk. Log-PIIINP concentrations were also associated with CVD risk (hazard ratio [95% CI] per SD, 1.35 [1.05 to 1.74]). Death and CVD incidence rates were 2-fold higher in participants with both biomarkers higher than the median (corresponding hazard ratio [95% CI], 2.78 [1.43 to 5.40] and 1.77 [1.04 to 3.03], respectively) compared with those with either or both less than the median. The inclusion of both biomarkers improved the C-statistic (for predicting mortality) from 0.78 to 0.82 (P=0.03). Matrix metalloproteinase-9 was unrelated to either outcome. CONCLUSIONS:Higher circulating tissue inhibitor of matrix metalloproteinase-1 and PIIINP concentrations are associated with mortality, and higher PIIINP is associated with incident CVD, in the community.

SUBMITTER: Velagaleti RS

PROVIDER: S-EPMC2959140 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature

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Relations of biomarkers of extracellular matrix remodeling to incident cardiovascular events and mortality.

Velagaleti Raghava S RS Gona Philimon P Sundström Johan J Larson Martin G MG Siwik Deborah D Colucci Wilson S WS Benjamin Emelia J EJ Vasan Ramachandran S RS

Arteriosclerosis, thrombosis, and vascular biology 20100826 11

<h4>Objective</h4>To evaluate if biomarkers reflecting left ventricular/vascular extracellular matrix remodeling are associated with cardiovascular disease (CVD) and death in the community.<h4>Methods and results</h4>In 922 Framingham Study participants (mean age, 58 years; 56% women), we related circulating concentrations of matrix metalloproteinase-9 (binary variable: detectable versus undetectable), log of tissue inhibitor of matrix metalloproteinase-1, and log of procollagen type III aminote ...[more]

PMID: 20798380

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Project description:Prior studies have demonstrated conflicting results regarding how much information novel biomarkers add to cardiovascular risk assessment.To evaluate the utility of contemporary biomarkers for predicting cardiovascular risk when added to conventional risk factors.Cohort study of 5067 participants (mean age, 58 years; 60% women) without cardiovascular disease from Malmö, Sweden, who attended a baseline examination between 1991 and 1994. Participants underwent measurement of C-reactive protein (CRP), cystatin C, lipoprotein-associated phospholipase 2, midregional proadrenomedullin (MR-proADM), midregional proatrial natriuretic peptide, and N-terminal pro-B-type natriuretic peptide (N-BNP) and underwent follow-up until 2006 using the Swedish national hospital discharge and cause-of-death registers and the Stroke in Malmö register for first cardiovascular events (myocardial infarction, stroke, coronary death).Incident cardiovascular and coronary events.During median follow-up of 12.8 years, there were 418 cardiovascular and 230 coronary events. Models with conventional risk factors had C statistics of 0.758 (95% confidence interval [CI], 0.734 to 0.781) and 0.760 (0.730 to 0.789) for cardiovascular and coronary events, respectively. Biomarkers retained in backward-elimination models were CRP and N-BNP for cardiovascular events and MR-proADM and N-BNP for coronary events, which increased the C statistic by 0.007 (P = .04) and 0.009 (P = .08), respectively. The proportion of participants reclassified was modest (8% for cardiovascular risk, 5% for coronary risk). Net reclassification improvement was nonsignificant for cardiovascular events (0.0%; 95% CI, -4.3% to 4.3%) and coronary events (4.7%; 95% CI, -0.76% to 10.1%). Greater improvements were observed in analyses restricted to intermediate-risk individuals (cardiovascular events: 7.4%; 95% CI, 0.7% to 14.1%; P = .03; coronary events: 14.6%; 95% CI, 5.0% to 24.2%; P = .003). However, correct reclassification was almost entirely confined to down-classification of individuals without events rather than up-classification of those with events.Selected biomarkers may be used to predict future cardiovascular events, but the gains over conventional risk factors are minimal. Risk classification improved in intermediate-risk individuals, mainly through the identification of those unlikely to develop events.

Project description:Some variables including age, comorbidity of diabetes, and so on at dialysis initiation are associated with patient prognosis. Cardiovascular (CV) events are a major cause of death, and adequate models that predict prognosis in dialysis patients are warranted. Therefore, we created models using some variables at dialysis initiation. We used a database of 1,520 consecutive dialysis patients (median age, 70 years; 492 women [32.4%]) from a multicenter prospective cohort study. We established the primary endpoint as a composite of the incidence of first CV events or all-cause death. A multivariable Cox proportional hazard regression model was used to construct a model. We considered a complex and a simple model. We used area under the receiver operating characteristic curve (AUROC) to assess and compare the predictive performances of the prediction models and evaluated the improvement in discrimination using the complex model versus the simple model using net reclassification improvement (NRI). We then assessed integrated discrimination improvement (IDI) to evaluate improvements in average sensitivity and specificity. Of 392 deaths, 152 were CV-related. Totally, 506 CV events occurred during the follow-up period (median 1,285 days). Finally, 692 patients reached the primary endpoint. Baseline data were set at dialysis initiation. AUROC for the primary endpoint was 0.737 (95% confidence interval [CI], 0.712-0.761) in the simple model and 0.765 (95% CI, 0.741-0.788) in the complex model. There were significant intergroup differences in NRI (0.44; 95% CI, 0.34-0.53; p < 0.001) and IDI (0.02; 95% CI, 0.02-0.03; p < 0.001). We prepared a Shiny R application for each model to automatically calculate the predicted occurrence probability (https://statacademy.shinyapps.io/App_inaguma_20190717/). The complex model made more accurate predictions than the simple model. However, the intergroup difference was not significant. Hence, the simple model was more useful than the complex model. The tool was useful in a real-world clinical setting because it required only routinely available variables. Moreover, we emphasized that the tool could predict the incidence of CV events or all-cause mortality for individual patients. In the future, we must confirm its external validity in other prospective cohorts.

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Relations of biomarkers of extracellular matrix remodeling to incident cardiovascular events and mortality.

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Relations of biomarkers of extracellular matrix remodeling to incident cardiovascular events and mortality.

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