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

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          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 (χ 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 (χ 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.

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          Most cited references20

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          General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

          Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.
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            Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation.

            The Framingham Heart Study produced sex-specific coronary heart disease (CHD) prediction functions for assessing risk of developing incident CHD in a white middle-class population. Concern exists regarding whether these functions can be generalized to other populations. To test the validity and transportability of the Framingham CHD prediction functions per a National Heart, Lung, and Blood Institute workshop organized for this purpose. Sex-specific CHD functions were derived from Framingham data for prediction of coronary death and myocardial infarction. These functions were applied to 6 prospectively studied, ethnically diverse cohorts (n = 23 424), including whites, blacks, Native Americans, Japanese American men, and Hispanic men: the Atherosclerosis Risk in Communities Study (1987-1988), Physicians' Health Study (1982), Honolulu Heart Program (1980-1982), Puerto Rico Heart Health Program (1965-1968), Strong Heart Study (1989-1991), and Cardiovascular Health Study (1989-1990). The performance, or ability to accurately predict CHD risk, of the Framingham functions compared with the performance of risk functions developed specifically from the individual cohorts' data. Comparisons included evaluation of the equality of relative risks for standard CHD risk factors, discrimination, and calibration. For white men and women and for black men and women the Framingham functions performed reasonably well for prediction of CHD events within 5 years of follow-up. Among Japanese American and Hispanic men and Native American women, the Framingham functions systematically overestimated the risk of 5-year CHD events. After recalibration, taking into account different prevalences of risk factors and underlying rates of developing CHD, the Framingham functions worked well in these populations. The sex-specific Framingham CHD prediction functions perform well among whites and blacks in different settings and can be applied to other ethnic groups after recalibration for differing prevalences of risk factors and underlying rates of CHD events.
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              Cardiovascular disease risk profiles.

              This article presents prediction equations for several cardiovascular disease endpoints, which are based on measurements of several known risk factors. Subjects (n = 5573) were original and offspring subjects in the Framingham Heart Study, aged 30 to 74 years, and initially free of cardiovascular disease. Equations to predict risk for the following were developed: myocardial infarction, coronary heart disease (CHD), death from CHD, stroke, cardiovascular disease, and death from cardiovascular disease. The equations demonstrated the potential importance of controlling multiple risk factors (blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking, glucose intolerance, and left ventricular hypertrophy) as opposed to focusing on one single risk factor. The parametric model used was seen to have several advantages over existing standard regression models. Unlike logistic regression, it can provide predictions for different lengths of time, and probabilities can be expressed in a more straightforward way than the Cox proportional hazards model.
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                Author and article information

                Journal
                Eur J Prev Cardiol
                Eur J Prev Cardiol
                CPR
                spcpr
                European Journal of Preventive Cardiology
                SAGE Publications (Sage UK: London, England )
                2047-4873
                2047-4881
                27 July 2017
                October 2017
                : 24
                : 15
                : 1660-1669
                Affiliations
                [1 ]School of Population and Global Health, University of Melbourne, Australia
                [2 ]Centre for Chronic Disease Prevention, James Cook University, Australia
                [3 ]School of Health Sciences, University of South Australia, Australia
                [4 ]The George Institute for Global Health, University of New South Wales, Sydney, Australia
                [5 ]Apunipima Cape York Health Council, Cairns, Australia
                Author notes
                [*]Philip Clarke, Level 4, 207 Bouverie Street, The University of Melbourne, Victoria 3010, Australia. Email: philip.clarke@ 123456unimelb.edu.au Twitter: @pmc868
                Article
                10.1177_2047487317722913
                10.1177/2047487317722913
                5648047
                28749178
                1d980017-e495-4660-b787-d8fbccb4f446
                © The European Society of Cardiology 2017

                This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 16 May 2017
                : 7 July 2017
                Categories
                Risk Prediction
                Full Research Papers

                cardiovascular disease,risk prediction,survival analysis,indigenous population

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