Comparative performance of pooled cohort equations and Framingham risk scores in cardiovascular disease risk classification in a slum setting in Nairobi Kenya.
ABSTRACT: Background:Cardiovascular diseases (CVD) cause 18 million deaths annually. Low- and middle-income countries (LMICs) account for 80% of the CVD burden, and the burden is expected to grow in the region in the coming years. Screening for and identification of individuals at high risk for CVD in primary care settings can be accomplished using available CVD risk scores. However, few of these scores have been validated/recalibrated for use in sub-Saharan Africa (SSA). Methods:Pooled cohort equations (PCE) and Framingham risk scores for 10-year CVD risk were applied on 1960 men and women aged 40 years and older from the AWI-Gen (Africa, Wits-INDEPTH Partnership for GENomic studies) study 2015. Low, moderate/intermediate or high CVD risk classifications correspond to <10%, 10-20% and >20% chance of developing CVD in 10 years respectively. Agreement between the risk scores was assessed using kappa and correlation coefficients. Results:High CVD risk was 10.3% in PCE 2013, 0.4% in PCE 2018, 2.9% in Framingham and 3.6% in Framingham non-laboratory scores. Conversely, low CVD risk was 62.2% in PCE 2013 and 95.6% in PCE 2018, 84.0% and 80.1% in Framingham and Framingham non-laboratory scores, respectively. A moderate agreement existed between the Framingham functions (kappa = 0.64, 95% CI 0.59-0.68, correlation, rs = 0.711). There was no agreement between the PCE 2013 and 2018 functions (kappa = 0.05, 95% CI 0.04-0.06). Conclusions:Newer cohort-based data is necessary to validate and recalibrate existing CVD risk scores in order to develop appropriate functions for use in SSA.
Project description:OBJECTIVES:Cardiovascular disease (CVD) risk prediction models are useful tools for identifying those at high risk of cardiovascular events in a population. No studies have evaluated the performance of such risk models in an Arab population. Therefore, in this study, the accuracy and clinical usefulness of two commonly used Framingham-based risk models and the 2013 Pooled Cohort Risk Equation (PCE) were assessed in a United Arab Emirates (UAE) national population. DESIGN:A 10-year retrospective cohort study. SETTING:Outpatient clinics at a tertiary care hospital, Al-Ain, UAE. PARTICIPANTS:The study cohort included 1041 UAE nationals aged 30-79 who had no history of CVD at baseline. Patients were followed until 31 December 2019. Eligible patients were grouped into the PCE and the Framingham validation cohorts. EXPOSURE:The 10-year predicted risk for CVD for each patient was calculated using the 2008 Framingham risk model, the 2008 office-based Framingham risk model, and the 2013 PCE model. PRIMARY OUTCOME MEASURE:The discrimination, calibration and clinical usefulness of the three models for predicting 10-year cardiovascular risk were assessed. RESULTS:In women, the 2013 PCE model showed marginally better discrimination (C-statistic: 0.77) than the 2008 Framingham models (C-statistic: 0.74-0.75), whereas all three models showed moderate discrimination in men (C-statistic: 0.69?0.70). All three models overestimated CVD risk in both men and women, with higher levels of predicted risk. The 2008 Framingham risk model (high-risk threshold of 20%) classified only 46% of women who subsequently developed incident CVD within 10 years as high risk. The 2013 PCE risk model (high-risk threshold of 7.5%) classified 74% of men who did not develop a cardiovascular event as high risk. CONCLUSIONS:None of the three models is accurate for predicting cardiovascular risk in UAE nationals. The performance of the models could potentially be improved by recalibration.
Project description:BACKGROUND:To investigate the performance of the 2013 American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) in a large, prospective, community-based cohort in Korea and to compare it with that of the Framingham Global Cardiovascular Disease Risk Score (FRS-CVD) and the Korean Risk Prediction Model (KRPM). METHODS:In the Korean Genome and Epidemiology Study (KOGES)-Ansan and Ansung study, we evaluated calibration and discrimination of the PCE for non-Hispanic whites (PCE-WH) and for African Americans (PCE-AA) and compared their predictive abilities with the FRS-CVD and the KRPM. RESULTS:The present study included 7,932 individuals (3,778 men and 4,154 women). The PCE-WH and PCE-AA moderately overestimated the risk of atherosclerotic cardiovascular disease (ASCVD) for men (6% and 13%, respectively) but underestimated the risk for women (-49% and -25%, respectively). The FRS-CVD overestimated ASCVD risk for men (91%) but provided a good risk prediction for women (3%). The KRPM underestimated ASCVD risk for men (-31%) and women (-31%). All the risk prediction models showed good discrimination in both men (C-statistic 0.730 to 0.735) and women (C-statistic 0.726 to 0.732). Recalibration of the PCE using data from the KOGES-Ansan and Ansung study substantially improved the predictive accuracy in men. CONCLUSION:In the KOGES-Ansan and Ansung study, the PCE overestimated ASCVD risk for men and underestimated the risk for women. The PCE-WH and the FRS-CVD provided an accurate prediction of ASCVD in men and women, respectively.
Project description:This research aims to assess application of different cardiovascular disease (CVD) mortality risk prediction models in Chinese rural population. Data was collected from a 6-year follow-up survey in rural area of Henan Province, China. 10338 participants aged 40 to 65 years were included. Baseline study was conducted between 2007 and 2008, and followed up from 2013 to 2014. Seven models: general Framingham risk score (general-FRS), simplified-FRS, Systematic Coronary Risk Evaluation for high (SCORE-high), SCORE-low, Chinese ischemic CVD (CN-ICVD), Pooled Cohort Risk Equation for white (PCE-white) and for African-American (PCE-AA) were assessed and recalibrated. The model performance was evaluated by C-statistics and modified Nam-D'Agostino test. 168 CVD deaths occurred during follow-up. All seven models showed moderate C-statics ranging from 0.727 to 0.744. Following recalibration, general-FRS, simplified-FRS, CN-ICVD, PCE-white and PCE-AA had improved C-statistics of 0.776, 0.795, 0.793, 0.779, and 0.776 for men and 0.756, 0.753, 0.755, 0.758 and 0.760 for women, respectively. Calibrations ?2 of general-FRS, simplified-FRS, SCORE-high, CN-ICVD and PCE-AA model for men, and general-FRS, CN-ICVD and PCE-white model for women were statistically acceptable, indicating these models predicts CVD mortality risk more accurately than others and could be recommended in Chinese rural population.
Project description:BACKGROUND:The 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. METHODS:A 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. RESULTS:The 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. CONCLUSIONS:The 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:BACKGROUND: We aimed to explore the agreement among World Health Organization (WHO), European Group for the Study of Insulin Resistance (EGIR), National Cholesterol Education Program (NCEP), American College of Endocrinology (ACE), and International Diabetes Federation (IDF) definitions of the metabolic syndrome. METHODS: 1568 subjects (532 men, 1036 women, mean age 45 and standard deviation (SD) 13 years) were evaluated in this cross-sectional, methodological study. Cardiometabolic risk factors were determined. Insulin sensitivity was calculated by HOMA-IR. Agreement among definitions was determined by the kappa statistic. ANOVA and post hoc Tukey's test were used to compare multiple groups. RESULTS: The agreement between WHO and EGIR definitions was very good (kappa: 0.83). The agreement between NCEP, ACE, and IDF definitions was substantial to very good (kappa: 0.77-0.84). The agreement between NCEP or ACE or IDF and WHO or EGIR definitions was fair (kappa: 0.32-0.37). The age and sex adjusted prevalence of metabolic syndrome was 38% by NCEP, 42% by ACE and IDF, 20% by EGIR and 19% by WHO definition. The evaluated definitions were dichotomized after analysis of design, agreement and prevalence: insulin measurement requiring definitions (WHO and EGIR) and definitions not requiring insulin measurement (NCEP, ACE, IDF). One definition was selected from each set for comparison. WHO-defined subjects were more insulin resistant than subjects without the metabolic syndrome (mean and SD for log HOMA-IR, 0.53 +/- 0.14 vs. 0.07 +/- 0.23, respectively, p < 0.05) and had higher Framingham risk scores (mean and SD, 2.99 +/- 4.64% vs. 1.10 +/- 1.87%, respectively, p < 0.05). The additional subjects identified by IDF definition, but not by WHO definition also had more insulin resistance and higher Framingham risk scores than subjects without the metabolic syndrome (mean and SD, log HOMA-IR 0.18 +/- 0.18 vs. 0.07 +/- 0.23, p < 0.05 and Framingham risk score 2.93 +/- 4.54% vs. 1.10 +/- 1.87%, p < 0.05). The IDF-identified additional subjects had similar Framingham risk scores as WHO-identified subjects (p > 0.05), but lower log HOMA-IR values (p < 0.05). CONCLUSION: The metabolic syndrome definitions that do not require measurement of insulin levels (NCEP, ACE and IDF) identify twice more patients with insulin resistance and increased Framingham risk scores and are more useful than the definitions that require measurement of insulin levels (WHO and EGIR).
Project description:<h4>Background</h4>National and international primary CVD risk screening guidelines focus on using total CVD risk scores. Recently, we developed a non-laboratory-based CVD risk score (inputs: age, sex, smoking, diabetes, systolic blood pressure, treatment of hypertension, body-mass index), which can assess risk faster and at lower costs compared to laboratory-based scores (inputs include cholesterol values). We aimed to assess the exchangeability of the non-laboratory-based risk score to four commonly used laboratory-based scores (Framingham CVD [2008, 1991 versions], and Systematic COronary Risk Evaluation [SCORE] for low and high risk settings) in an external validation population.<h4>Methods and findings</h4>Analyses were based on individual-level, score-specific rankings of risk for adults in the Third National Health and Nutrition Examination Survey (NHANES III) aged 25-74 years, without history of CVD or cancer (n?=?5,999). Risk characterization agreement was based on overlap in dichotomous risk characterization (thresholds of 10-year risk >10-20%) and Spearman rank correlation. Risk discrimination was assessed using receiver operator characteristic curve analysis (10-year CVD death outcome). Risk characterization agreement ranged from 91.9-95.7% and 94.2-95.1% with Spearman correlation ranges of 0.957-0.980 and 0.946-0.970 for men and women, respectively. In men, c-statistics for the non-laboratory-based, Framingham (2008, 1991), and SCORE (high, low) functions were 0.782, 0.776, 0.781, 0.785, and 0.785, with p-values for differences relative to the non-laboratory-based score of 0.44, 0.89, 0.68 and 0.65, respectively. In women, the corresponding c-statistics were 0.809, 0.834, 0.821, 0.792, and 0.792, with corresponding p-values of 0.04, 0.34, 0.11 and 0.09, respectively.<h4>Conclusions</h4>Every score discriminated risk of CVD death well, and there was high agreement in risk characterization between non-laboratory-based and laboratory-based risk scores, which suggests that the non-laboratory-based score can be a useful proxy for Framingham or SCORE functions in resource-limited settings. Future external validation studies can assess whether the sex-specific risk discrimination results hold in other populations.
Project description:It is unclear how well currently available risk scores predict cardiovascular disease (CVD) risk in low-income and middle-income countries. We aim to compare the American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort risk equations (ACC/AHA model) with 6 other CVD risk tools to assess the concordance of predicted CVD risk in a random sample from 5 geographically diverse Peruvian populations. We used data from 2 Peruvian, age and sex-matched, population-based studies across 5 geographical sites. The ACC/AHA model were compared with 6 other CVD risk prediction tools: laboratory Framingham risk score for CVD, non-laboratory Framingham risk score for CVD, Reynolds risk score, systematic coronary risk evaluation, World Health Organization risk charts, and the Lancet chronic diseases risk charts. Main outcome was in agreement with predicted CVD risk using Lin's concordance correlation coefficient. Two thousand one hundred and eighty-three subjects, mean age 54.3 (SD ± 5.6) years, were included in the analysis. Overall, we found poor agreement between different scores when compared with ACC/AHA model. When each of the risk scores was used with cut-offs specified in guidelines, ACC/AHA model depicted the highest proportion of people at high CVD risk predicted at 10 years, with a prevalence of 29.0% (95% confidence interval, 26.9-31.0%), whereas prevalence with World Health Organization risk charts was 0.6% (95% confidence interval, 0.2-8.6%). In conclusion, poor concordance between current CVD risk scores demonstrates the uncertainty of choosing any of them for public health and clinical interventions in Latin American populations. There is a need to improve the evidence base of risk scores for CVD in low-income and middle-income countries.
Project description:Cardiovascular disease (CVD) risk prediction tools are often applied to populations beyond those in which they were designed when validated tools for specific subpopulations are unavailable.?Using data from 2283 human immunodeficiency virus (HIV)-infected adults aged ?18 years, who were active in the HIV Outpatient Study (HOPS), we assessed performance of 3 commonly used CVD prediction models developed for general populations: Framingham general cardiovascular Risk Score (FRS), American College of Cardiology/American Heart Association Pooled Cohort equations (PCEs), and Systematic COronary Risk Evaluation (SCORE) high-risk equation, and 1 model developed in HIV-infected persons: the Data Collection on Adverse Effects of Anti-HIV Drugs (D:A:D) study equation. C-statistics assessed model discrimination and the ratio of expected to observed events (E/O) and Hosmer-Lemeshow ?2 P value assessed calibration.?From January 2002 through September 2013, 195 (8.5%) HOPS participants experienced an incident CVD event in 15 056 person-years. The FRS demonstrated moderate discrimination and was well calibrated (C-statistic: 0.66, E/O: 1.01, P = .89). The PCE and D:A:D risk equations demonstrated good discrimination but were less well calibrated (C-statistics: 0.71 and 0.72 and E/O: 0.88 and 0.80, respectively; P < .001 for both), whereas SCORE performed poorly (C-statistic: 0.59, E/O: 1.72; P = .48).?Only the FRS accurately estimated risk of CVD events, while PCE and D:A:D underestimated risk. Although these models could potentially be used to rank US HIV-infected individuals at higher or lower risk for CVD, the models may fail to identify substantial numbers of HIV-infected persons with elevated CVD risk who could potentially benefit from additional medical treatment.
Project description:BACKGROUND:The utility and validity of cardiovascular diseases (CVD) risk scores are not well studied in sub-Saharan Africa. We compared and correlated CVD risk scores with carotid intima media thickness (c-IMT) among HIV-infected and uninfected people in Uganda. METHODS:We first calculated CVD risk using the (1) Framingham laboratory-based score; (2) Framingham nonlaboratory score (FRS-BMI); (3) Reynolds risk score; (4) American College of Cardiology and American Heart Association score; and (5) the Data collection on Adverse Effects of Anti-HIV Drugs score. We then compared absolute risk scores and risk categories across each score using Pearson correlation and kappa statistics, respectively. Finally, we fit linear regression models to estimate the strength of association between each risk score and c-IMT. RESULTS:Of 205 participants, half were females and median age was 49 years [interquartile range (IQR) 46-53]. Median CD4 count was 430 cells/mm (IQR 334-546), with median 7 years of antiretroviral therapy exposure (IQR 6.4-7.5). HIV-uninfected participants had a higher median systolic blood pressure (121 vs. 110 mm Hg), prevalent current smokers (18% vs. 4%, P = 0.001), higher median CVD risk scores (P < 0.003), and greater c-IMT (0.68 vs. 0.63, P = 0.003). Overall, FRS-BMI was highly correlated with other risk scores (all rho >0.80). In linear regression models, we found significant correlations between increasing CVD risk and higher c-IMT (P < 0.01 in all models). CONCLUSIONS:In this cross-sectional study from Uganda, the FRS-BMI correlated well with standard risk scores and c-IMT. HIV-uninfected individuals had higher risk scores than HIV-infected individuals, and the difference seemed to be driven by modifiable factors.
Project description:All rigorous primary cardiovascular disease (CVD) prevention guidelines recommend absolute CVD risk scores to identify high- and low-risk patients, but laboratory testing can be impractical in low- and middle-income countries. The purpose of this study was to compare the ranking performance of a simple, non-laboratory-based risk score to laboratory-based scores in various South African populations.We calculated and compared 10-year CVD (or coronary heart disease (CHD)) risk for 14,772 adults from thirteen cross-sectional South African populations (data collected from 1987 to 2009). Risk characterization performance for the non-laboratory-based score was assessed by comparing rankings of risk with six laboratory-based scores (three versions of Framingham risk, SCORE for high- and low-risk countries, and CUORE) using Spearman rank correlation and percent of population equivalently characterized as 'high' or 'low' risk. Total 10-year non-laboratory-based risk of CVD death was also calculated for a representative cross-section from the 1998 South African Demographic Health Survey (DHS, n = 9,379) to estimate the national burden of CVD mortality risk.Spearman correlation coefficients for the non-laboratory-based score with the laboratory-based scores ranged from 0.88 to 0.986. Using conventional thresholds for CVD risk (10% to 20% 10-year CVD risk), 90% to 92% of men and 94% to 97% of women were equivalently characterized as 'high' or 'low' risk using the non-laboratory-based and Framingham (2008) CVD risk score. These results were robust across the six risk scores evaluated and the thirteen cross-sectional datasets, with few exceptions (lower agreement between the non-laboratory-based and Framingham (1991) CHD risk scores). Approximately 18% of adults in the DHS population were characterized as 'high CVD risk' (10-year CVD death risk >20%) using the non-laboratory-based score.We found a high level of correlation between a simple, non-laboratory-based CVD risk score and commonly-used laboratory-based risk scores. The burden of CVD mortality risk was high for men and women in South Africa. The policy and clinical implications are that fast, low-cost screening tools can lead to similar risk assessment results compared to time- and resource-intensive approaches. Until setting-specific cohort studies can derive and validate country-specific risk scores, non-laboratory-based CVD risk assessment could be an effective and efficient primary CVD screening approach in South Africa.