Aim Screening for a high cardiovascular disease (CVD) risk followed by preventive treatment can potentially reduce coronary heart disease-related morbidity and mortality. ROBINSCA (Risk Or Benefit... Show moreAim Screening for a high cardiovascular disease (CVD) risk followed by preventive treatment can potentially reduce coronary heart disease-related morbidity and mortality. ROBINSCA (Risk Or Benefit IN Screening for CArdiovascular disease) is a population-based randomized controlled screening trial that investigates the effectiveness of CVD screening in asymptomatic participants using the Systematic COronary Risk Evaluation (SCORE) model or coronary artery calcium (CAC) scoring. This study describes the distributions in risk and treatment in the ROBINSCA trial.Methods and results Individuals at expected elevated CVD risk were randomized into screening arm A (n = 14 478; SCORE, 10-year fatal and non-fatal risk); or screening arm B (n= 14 450; CAC scoring). Preventive treatment was largely advised according to current Dutch guidelines. Risk and treatment differences between the screening arms were analysed. A total of 12 185 participants (84.2%) in arm A and 12 950 (89.6%) in arm B were screened. In total, 48.7% were women, and median age was 62 (interquartile range 10) years. SCORE screening identified 45.1% at low risk (SCORE < 10%), 26.5% at intermediate risk (SCORE 10-20%), and 28.4% at high risk (SCORE >= 20%). According to CAC screening, 76.0% were at low risk (Agatston < 100), 15.1% at high risk (Agatston 100-399), and 8.9% at very high risk (Agatston >= 400). CAC scoring significantly reduced the number of individuals indicated for preventive treatment compared to SCORE (relative reduction women: 37.2%; men: 28.8%).Conclusion We showed that compared to risk stratification based on SCORE, CAC scoring classified significantly fewer men and women at increased risk, and less preventive treatment was indicated. Show less
Aims There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention... Show moreAims There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after 'recalibration', a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied.Methods and results Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at 'high' 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29 39% of individuals aged >= 40 years as high risk. By contrast, recalibration reduced this proportion to 22-24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44 51 such individuals using original algorithms, in contrast to 37-39 individuals with recalibrated algorithms.Conclusion Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need. Show less
