Dataset Information

Re-estimation improved the performance of two Framingham cardiovascular risk equations and the Pooled Cohort equations: A nationwide registry analysis.

ABSTRACT: Equations predicting the risk of occurrence of cardiovascular disease (CVD) are used in primary care to identify high-risk individuals among the general population. To improve the predictive performance of such equations, we updated the Framingham general CVD 1991 and 2008 equations and the Pooled Cohort equations for atherosclerotic CVD within five years in a contemporary cohort of individuals who participated in the Austrian health-screening program from 2009-2014. The cohort comprised 1.7?M individuals aged 30-79 without documented CVD history. CVD was defined by hospitalization or death from cardiovascular cause. Using baseline and follow-up data, we recalibrated and re-estimated the equations. We evaluated the gain in discrimination and calibration and assessed explained variation. A five-year general CVD risk of 4.61% was observed. As expected, discrimination c-statistics increased only slightly and ranged from 0.73-0.79. The two original Framingham equations overestimated the CVD risk, whereas the original Pooled Cohort equations underestimated it. Re-estimation improved calibration of all equations adequately, especially for high-risk individuals. Half of the individuals were reclassified into another risk category using the re-estimated equations. Predictors in the re-estimated Framingham equations explained 7.37% of the variation, whereas the Pooled Cohort equations explained 5.81%. Age was the most important predictor.

SUBMITTER: Wallisch C

PROVIDER: S-EPMC7235230 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Re-estimation improved the performance of two Framingham cardiovascular risk equations and the Pooled Cohort equations: A nationwide registry analysis.

Wallisch Christine C Heinze Georg G Rinner Christoph C Mundigler Gerald G Winkelmayer Wolfgang C WC Dunkler Daniela D

Scientific reports 20200518 1

Equations predicting the risk of occurrence of cardiovascular disease (CVD) are used in primary care to identify high-risk individuals among the general population. To improve the predictive performance of such equations, we updated the Framingham general CVD 1991 and 2008 equations and the Pooled Cohort equations for atherosclerotic CVD within five years in a contemporary cohort of individuals who participated in the Austrian health-screening program from 2009-2014. The cohort comprised 1.7 M i ...[more]

PMID: 32424214

Similar Datasets

Project description:BackgroundThe Framingham risk models and pooled cohort equations (PCE) are widely used and advocated in guidelines for predicting 10-year risk of developing coronary heart disease (CHD) and cardiovascular disease (CVD) in the general population. Over the past few decades, these models have been extensively validated within different populations, which provided mounting evidence that local tailoring is often necessary to obtain accurate predictions. The objective is to systematically review and summarize the predictive performance of three widely advocated cardiovascular risk prediction models (Framingham Wilson 1998, Framingham ATP III 2002 and PCE 2013) in men and women separately, to assess the generalizability of performance across different subgroups and geographical regions, and to determine sources of heterogeneity in the findings across studies.MethodsA search was performed in October 2017 to identify studies investigating the predictive performance of the aforementioned models. Studies were included if they externally validated one or more of the original models in the general population for the same outcome as the original model. We assessed risk of bias for each validation and extracted data on population characteristics and model performance. Performance estimates (observed versus expected (OE) ratio and c-statistic) were summarized using a random effects models and sources of heterogeneity were explored with meta-regression.ResultsThe search identified 1585 studies, of which 38 were included, describing a total of 112 external validations. Results indicate that, on average, all models overestimate the 10-year risk of CHD and CVD (pooled OE ratio ranged from 0.58 (95% CI 0.43-0.73; Wilson men) to 0.79 (95% CI 0.60-0.97; ATP III women)). Overestimation was most pronounced for high-risk individuals and European populations. Further, discriminative performance was better in women for all models. There was considerable heterogeneity in the c-statistic between studies, likely due to differences in population characteristics.ConclusionsThe Framingham Wilson, ATP III and PCE discriminate comparably well but all overestimate the risk of developing CVD, especially in higher risk populations. Because the extent of miscalibration substantially varied across settings, we highly recommend that researchers further explore reasons for overprediction and that the models be updated for specific populations.

Project description:ImportanceObesity is a global health challenge and a risk factor for atherosclerotic cardiovascular disease (ASVCD). Performance of the pooled cohort equations (PCE) for ASCVD risk by body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is unknown.ObjectiveTo assess performance of the PCE across clinical BMI categories.Design, setting, and participantsThis cohort study used pooled individual-level data from 8 community-based, prospective, longitudinal cohort studies with 10-year ASCVD event follow-up from 1996 to 2016. We included all adults ages 40 to 79 years without baseline ASCVD or statin use, resulting in a sample size of 37 311 participants. Data were analyzed from August 2017 to July 2020.ExposuresParticipant BMI category: underweight (<18.5), normal weight (18.5 to <25), overweight (25 to <30), mild obesity (30 to <35), and moderate to severe obesity (≥35).Main outcomes and measuresDiscrimination (Harrell C statistic) and calibration (Nam-D'Agostino χ2 goodness-of-fit test) of the PCE across BMI categories. Improvement in discrimination and net reclassification with addition of BMI, waist circumference, and high-sensitivity C-reactive protein (hsCRP) to the PCE.ResultsAmong 37 311 participants (mean [SD] age, 58.6 [11.8] years; 21 897 [58.7%] women), 380 604 person-years of follow-up were conducted. Mean (SD) baseline BMI was 29.0 (6.2), and 360 individuals (1.0%) were in the underweight category, 9937 individuals (26.6%) were in the normal weight category, 13 601 individuals (36.4%) were in the overweight category, 7783 individuals (20.9%) were in the mild obesity category, and 5630 individuals (15.1%) were in the moderate to severe obesity category. Median (interquartile range [IQR]) 10-year estimated ASCVD risk was 7.1% (2.5%-15.4%), and 3709 individuals (9.9%) developed ASCVD over a median (IQR) 10.8 [8.5-12.6] years. The PCE overestimated ASCVD risk in the overall cohort (estimated/observed [E/O] risk ratio, 1.22; 95% CI, 1.18-1.26) and across all BMI categories except the underweight category. Calibration was better near the clinical decision threshold in all BMI groups but worse among individuals with moderate or severe obesity (E/O risk ratio, 1.36; 95% CI, 1.25-1.47) and among those with the highest estimated ASCVD risk ≥20%. The PCE C statistic overall was 0.760 (95% CI, 0.753-0.767), with lower discrimination in the moderate or severe obesity group (C statistic, 0.742; 95% CI, 0.721-0.763) compared with the normal-range BMI group (C statistic, 0.785; 95% CI, 0.772-0.798). Waist circumference (hazard ratio, 1.07 per 1-SD increase; 95% CI, 1.03-1.11) and hsCRP (hazard ratio, 1.07 per 1-SD increase; 95% CI, 1.05-1.09), but not BMI, were associated with increased ASCVD risk when added to the PCE. However, these factors did not improve model performance (C statistic, 0.760; 95% CI, 0.753-0.767) with or without added metrics.Conclusions and relevanceThese findings suggest that the PCE had acceptable model discrimination and were well calibrated at clinical decision thresholds but overestimated risk of ASCVD for individuals in overweight and obese categories, particularly individuals with high estimated risk. Incorporation of the usual clinical measures of obesity did not improve risk estimation of the PCE. Future research is needed to determine whether incorporation of alternative high-risk obesity markers (eg, weight trajectory or measures of visceral or ectopic fat) into the PCE may improve risk prediction.

Project description:ImportanceThe American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort risk equations were developed to estimate atherosclerotic cardiovascular disease (CVD) risk and guide statin initiation.ObjectiveTo assess calibration and discrimination of the Pooled Cohort risk equations in a contemporary US population.Design, setting, and participantsAdults aged 45 to 79 years enrolled in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study between January 2003 and October 2007 and followed up through December 2010. We studied participants for whom atherosclerotic CVD risk may trigger a discussion of statin initiation (those without clinical atherosclerotic CVD or diabetes, low-density lipoprotein cholesterol level between 70 and 189 mg/dL, and not taking statins; n = 10,997).Main outcomes and measuresPredicted risk and observed adjudicated atherosclerotic CVD incidence (nonfatal myocardial infarction, coronary heart disease [CHD] death, nonfatal or fatal stroke) at 5 years because REGARDS participants have not been followed up for 10 years. Additional analyses, limited to Medicare beneficiaries (n = 3333), added atherosclerotic CVD events identified in Medicare claims data.ResultsThere were 338 adjudicated events (192 CHD events, 146 strokes). The observed and predicted 5-year atherosclerotic CVD incidence per 1000 person-years for participants with a 10-year predicted atherosclerotic CVD risk of less than 5% was 1.9 (95% CI, 1.3-2.7) and 1.9, respectively, risk of 5% to less than 7.5% was 4.8 (95% CI, 3.4-6.7) and 4.8, risk of 7.5% to less than 10% was 6.1 (95% CI, 4.4-8.6) and 6.9, and risk of 10% or greater was 12.0 (95% CI, 10.6-13.6) and 15.1 (Hosmer-Lemeshow χ2 = 19.9, P = .01). The C index was 0.72 (95% CI, 0.70-0.75). There were 234 atherosclerotic CVD events (120 CHD events, 114 strokes) among Medicare-linked participants and the observed and predicted 5-year atherosclerotic CVD incidence per 1000 person-years for participants with a predicted risk of less than 7.5% was 5.3 (95% CI, 2.8-10.1) and 4.0, respectively, risk of 7.5% to less than 10% was 7.9 (95% CI, 4.6-13.5) and 6.4, and risk of 10% or greater was 17.4 (95% CI, 15.3-19.8) and 16.4 (Hosmer-Lemeshow χ2 = 5.4, P = .71). The C index was 0.67 (95% CI, 0.64-0.71).Conclusions and relevanceIn this cohort of US adults for whom statin initiation is considered based on the ACC/AHA Pooled Cohort risk equations, observed and predicted 5-year atherosclerotic CVD risks were similar, indicating that these risk equations were well calibrated in the population for which they were designed to be used, and demonstrated moderate to good discrimination.

Project description:ImportanceThe American Heart Association/American College of Cardiology pooled cohort equations (PCEs) are used for predicting 10-year atherosclerotic cardiovascular disease (ASCVD) risk. Pooled cohort equation risk prediction capabilities across self-reported leisure-time physical activity (LTPA) levels and the change in model performance with addition of LTPA to the PCE are unclear.ObjectiveTo evaluate PCE risk prediction performance across self-reported LTPA levels and the change in model performance by adding LTPA to the existing PCE model.Design, setting, and participantsIndividual-level pooling of data from 3 longitudinal cohort studies-Atherosclerosis Risk in Communities, Multi-Ethnic Study of Atherosclerosis, and Cardiovascular Health Study-was performed. A total of 18 824 participants were stratified into 4 groups based on self-reported LTPA levels: inactive (0 metabolic equivalent of task [MET]-min/wk), less than guideline-recommended (<500 MET-min/wk), guideline-recommended (500-1000 MET-min/week), and greater than guideline-recommended (>1000 MET-min/wk). Pooled cohort equation risk discrimination was studied using the C statistic and reclassification capabilities were studied using the Greenwood Nam-D'Agostino χ2 goodness-of-fit test. Change in risk discrimination and reclassification on adding LTPA to PCEs was evaluated using change in C statistic, integrated discrimination index, and categorical net reclassification index.Main outcomes and measuresAdjudicated ASCVD events during 10-year follow-up.ResultsAmong 18 824 participants studied, 10 302 were women (54.7%); mean (SD) age was 57.6 (8.2) years. A total of 5868 participants (31.2%) were inactive, 3849 (20.4%) had less than guideline-recommended LTPA, 3372 (17.9%) had guideline-recommended LTPA, and 5735 (30.5%) had greater than guideline-recommended LTPA level. Higher LTPA levels were associated with a lower risk of ASCVD after adjustment for risk factors (hazard ratio [HR] per 1-SD higher LTPA, 0.91; 95% CI, 0.86-0.96). Across LTPA groups, PCE risk discrimination (C statistic, 0.76-0.78) and risk calibration (all χ2 P > .10) was similar. Addition of LTPA to the PCE model resulted in no significant change in the C statistic (0.0005; 95% CI, -0.0004 to 0.0015; P = .28) and categorical net reclassification index (-0.003; 95% CI, -0.010 to 0.010; P = .95), but a minimal improvement in the integrated discrimination index (0.0008; 95% CI, 0.0002-0.0013; P = .005) was observed. Similar results were noted when cohort-specific coefficients were used for creating the baseline model.Conclusions and relevanceHigher self-reported LTPA levels appear to be associated with lower ASCVD risk and increasing LTPA promotes cardiovascular wellness. These findings suggest the American Heart Association/American College of Cardiology PCEs are accurate at estimating the probability of 10-year ASCVD risk regardless of LTPA level. The addition of self-reported LTPA to PCEs does not appear to be associated with improvement in risk prediction model performance.

Project description:BackgroundNon-alcoholic fatty liver disease (NAFLD) is common and is associated with cardiovascular (CV) disease and mortality. The Framingham steatosis index (FSI) was recently proposed as a diagnostic marker of NAFLD and was calculated from age, body mass index, triglyceride, aspartate aminotransferase, alanine aminotransferase, diabetes history, and hypertension status. We aimed to evaluate the predictive ability of FSI for CV risk using a large-scale population dataset from the Korean National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS).MethodsAmong 514,866 individuals in the NHIS-HEALS, we excluded those who died, had a history of admission due to a CV event, and were heavy drinkers. The final study cohort comprised 283,427 participants. We employed both unadjusted and covariate-adjusted models in Cox proportional hazards regression analyses to determine the association between FSI and major adverse cardiovascular events (MACEs), CV events, and CV mortality.ResultsDuring a median follow-up of 5.9 years, we documented 9,674, 8,798, and 1,602 cases of MACEs, CV events, and CV mortality, respectively. The incidence of MACEs was 1.28%, 2.99%, 3.94%, and 4.82% in the first to fourth quartiles of FSI, respectively. The adjusted hazard ratios (95% confidence interval) for MACEs gradually and significantly increased with the FSI quartiles [1.302 (1.215-1.395) in Q2, 1.487 (1.390-1.590) in Q3, and 1.792 (1.680-1.911) in Q4], following an adjustment for conventional CV risk factors, including age, sex, smoking, drinking, physical activities, low-density lipoprotein cholesterol, estimated glomerular filtration rate, and waist circumference. Participants in the higher quartiles of FSI exhibited a noteworthy increase in the occurrence of CV event. However, upon adjusting for relevant risk factors, the association between FSI and CV mortality did not reach statistical significance.ConclusionOur study suggests that the FSI, which is a surrogate marker of NAFLD, has a prognostic value for detecting individuals at higher risk of CV events.

Project description:Background Contemporary guidelines recommend using atherosclerotic cardiovascular disease screening tools to guide primary prevention. The performance of these scores is not well known in patients with moderate to advanced chronic kidney disease, particularly in combination with clinically available cardiac biomarkers including N-terminal pro-brain-type natriuretic peptide and high-sensitivity troponin T (hsTnT). Methods and Results We studied 1027 participants from the Chronic Renal Insufficiency Cohort without self-reported atherosclerotic cardiovascular disease who were not taking aspirin or statins at enrollment. Framingham Risk Score, Pooled Cohort Equation, N-terminal pro-brain-type natriuretic peptide, and hsTnT were measured at baseline. Outcomes included fatal and nonfatal myocardial infarction, stroke, and cardiac death. We calculated 10-fold cross-validated Harrell's C-indices for each risk score and cardiac biomarker alone and in combination. The C-index (95% CI) for discrimination of atherosclerotic cardiovascular disease was 0.72 (0.67, 0.77) for the Framingham Risk Score, and 0.72 (0.67, 0.76) for the Pooled Cohort Equation. HsTnT had comparable discrimination to each risk score, and improved the discrimination of each (change in Framingham 0.029, 95% CI 0.003, 0.055; change in Pooled Cohort Equation 0.027, 95% CI 0.002, 0.052). N-terminal pro-brain-type natriuretic peptide had poorer discrimination than the risk scores and did not significantly improve their discrimination (change in Framingham 0.009, 95% CI -0.001, 0.018; change in Pooled Cohort Equation 0.011, 95% CI -0.001, 0.024). Conclusions The Framingham Risk Score and Pooled Cohort Equation demonstrated moderate discrimination for atherosclerotic cardiovascular disease in patients with chronic kidney disease. HsTnT, but not N-terminal pro-brain-type natriuretic peptide, improved their discrimination overall. Until chronic kidney disease-specific atherosclerotic cardiovascular disease risk scores can be developed, it may be worth considering how to incorporate hsTnT into existing clinical risk scores.

Dataset Information

Re-estimation improved the performance of two Framingham cardiovascular risk equations and the Pooled Cohort equations: A nationwide registry analysis.

Publications

Re-estimation improved the performance of two Framingham cardiovascular risk equations and the Pooled Cohort equations: A nationwide registry analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets