Dataset Information

Validation and recalibration of the Framingham cardiovascular disease risk models in an Australian Indigenous cohort.

ABSTRACT: Background In Australia, clinical guidelines for primary prevention of cardiovascular disease recommend the use of the Framingham model to help identify those at high risk of developing the disease. However, this model has not been validated for the Indigenous population. Design Cohort study. Methods Framingham models were applied to the Well Person's Health Check (WPHC) cohort (followed 1998-2014), which included 1448 Aboriginal and Torres Strait Islanders from remote Indigenous communities in Far North Queensland. Cardiovascular disease risk predicted by the original and recalibrated Framingham models were compared with the observed risk in the WPHC cohort. Results The observed five- and 10-year cardiovascular disease probability of the WPHC cohort was 10.0% (95% confidence interval (CI): 8.5-11.7) and 18.7% (95% CI: 16.7-21.0), respectively. The Framingham models significantly underestimated the cardiovascular disease risk for this cohort by around one-third, with a five-year cardiovascular disease risk estimate of 6.8% (95% CI: 6.4-7.2) and 10-year risk estimates of 12.0% (95% CI: 11.4-12.6) and 14.2% (95% CI: 13.5-14.8). The original Framingham models showed good discrimination ability (C-statistic of 0.67) but a significant lack of calibration (?² between 82.56 and 134.67). After recalibration the 2008 Framingham model corrected the underestimation and improved the calibration for five-year risk prediction (?² of 18.48). Conclusions The original Framingham models significantly underestimate the absolute cardiovascular disease risk for this Australian Indigenous population. The recalibrated 2008 Framingham model shows good performance on predicting five-year cardiovascular disease risk in this population and was used to calculate the first risk chart based on empirical validation using long-term follow-up data from a remote Australian Indigenous population.

SUBMITTER: Hua X

PROVIDER: S-EPMC5648047 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Validation and recalibration of the Framingham cardiovascular disease risk models in an Australian Indigenous cohort.

Hua Xinyang X McDermott Robyn R Lung Thomas T Wenitong Mark M Tran-Duy An A Li Ming M Clarke Philip P

European journal of preventive cardiology 20170727 15

Background In Australia, clinical guidelines for primary prevention of cardiovascular disease recommend the use of the Framingham model to help identify those at high risk of developing the disease. However, this model has not been validated for the Indigenous population. Design Cohort study. Methods Framingham models were applied to the Well Person's Health Check (WPHC) cohort (followed 1998-2014), which included 1448 Aboriginal and Torres Strait Islanders from remote Indigenous communities in ...[more]

PMID: 28749178

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: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:Objectives To develop and validate updated QRISK3 prediction algorithms to estimate the 10 year risk of cardiovascular disease in women and men accounting for potential new risk factors.Design Prospective open cohort study.Setting General practices in England providing data for the QResearch database.Participants 1309 QResearch general practices in England: 981 practices were used to develop the scores and a separate set of 328 practices were used to validate the scores. 7.89 million patients aged 25-84 years were in the derivation cohort and 2.67 million patients in the validation cohort. Patients were free of cardiovascular disease and not prescribed statins at baseline.Methods Cox proportional hazards models in the derivation cohort to derive separate risk equations in men and women for evaluation at 10 years. Risk factors considered included those already in QRISK2 (age, ethnicity, deprivation, systolic blood pressure, body mass index, total cholesterol: high density lipoprotein cholesterol ratio, smoking, family history of coronary heart disease in a first degree relative aged less than 60 years, type 1 diabetes, type 2 diabetes, treated hypertension, rheumatoid arthritis, atrial fibrillation, chronic kidney disease (stage 4 or 5)) and new risk factors (chronic kidney disease (stage 3, 4, or 5), a measure of systolic blood pressure variability (standard deviation of repeated measures), migraine, corticosteroids, systemic lupus erythematosus (SLE), atypical antipsychotics, severe mental illness, and HIV/AIDs). We also considered erectile dysfunction diagnosis or treatment in men. Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for individual subgroups by age group, ethnicity, and baseline disease status.Main outcome measures Incident cardiovascular disease recorded on any of the following three linked data sources: general practice, mortality, or hospital admission records.Results 363?565 incident cases of cardiovascular disease were identified in the derivation cohort during follow-up arising from 50.8 million person years of observation. All new risk factors considered met the model inclusion criteria except for HIV/AIDS, which was not statistically significant. The models had good calibration and high levels of explained variation and discrimination. In women, the algorithm explained 59.6% of the variation in time to diagnosis of cardiovascular disease (R2, with higher values indicating more variation), and the D statistic was 2.48 and Harrell's C statistic was 0.88 (both measures of discrimination, with higher values indicating better discrimination). The corresponding values for men were 54.8%, 2.26, and 0.86. Overall performance of the updated QRISK3 algorithms was similar to the QRISK2 algorithms.Conclusion Updated QRISK3 risk prediction models were developed and validated. The inclusion of additional clinical variables in QRISK3 (chronic kidney disease, a measure of systolic blood pressure variability (standard deviation of repeated measures), migraine, corticosteroids, SLE, atypical antipsychotics, severe mental illness, and erectile dysfunction) can help enable doctors to identify those at most risk of heart disease and stroke.

Project description:ObjectivesLevel of education and genetic risk are key predictors of cardiovascular disease (CVD). While several studies have explored the causal mechanisms of education effects, it remains uncertain to what extent genetic risk is mediated by established CVD risk factors. This study sought to investigate this and explored the mediation of education and genetic effects on CVD by established cardiovascular risk factors in the Framingham Heart Study (FHS).DesignProspective observational cohort study.Participants7017 participants from the FHS.SettingCommunity-based cohort of adults in Framingham, Massachusetts, USA.Primary outcome measureIncident CVD. The total effects of education and genetic predisposition using a 63-variant genetic risk score (GRS) on CVD, as well as those mediated by established CVD risk factors, were assessed via mediation analysis based on the counterfactual framework using Cox proportional hazards regression models.ResultsOver a median follow-up time of 12.0 years, 1091 participants experienced a CVD event. Education and GRS displayed significant associations with CVD after adjustment for age and sex and the established risk factors smoking, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), body mass index, systolic blood pressure (SBP) and diabetes. For education effects, smoking, HDL-C and SBP were estimated to mediate 18.8% (95% CI 9.5% to 43%), 11.5% (95% CI 5.7% to 29.0%) and 4.5% (95% CI 1.6% to 13.3%) of the total effect of graduate degree, respectively, with the collective of all risk factors combined mediating 38.5% (95% 24.1% to 64.9%). A much smaller proportion of the effects of GRS were mediated by established risk factors combined (17.6%, 95% CI 2.4% to 35.7%), with HDL-C and TC mediating 11.5% (95% CI 6.2% to 21.5%) and 3.1% (95% CI 0.2% to 8.3%), respectively.ConclusionsUnlike education inequalities, established risk factors mediated only a fraction of GRS effects on CVD. Further research is required to elucidate the underlying causal mechanisms of genetic contributions to CVD.

Dataset Information

Validation and recalibration of the Framingham cardiovascular disease risk models in an Australian Indigenous cohort.

Publications

Validation and recalibration of the Framingham cardiovascular disease risk models in an Australian Indigenous cohort.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets