The diversity of the remaining risk equations has prompted us to compare the discriminatory power and calibration of the main national and international risk calculators in the DETECT study (Diabetes and Cardiovascular Risk Evaluation: Targets and Essential Data for Commitment of Treatment) which included a representative German primary care population. Since these risk scores are difficult to translate to other countries, we did not evaluate them in the current analysis. The UKPDS risk engine 19 has been recommended for patients with diabetes mellitus only, but the NICE clinical guideline (CG181) 20 has recommended QRISK for risk assessment in type 2 diabetes mellitus, because the UKPDS risk engine had significant bias. The CUORE risk equation has been developed for Italy 17, 18. The QRISK score 14 and the ASSIGN score 15, which have been derived from large United Kingdom primary care population datasets and which also include specific items such as deprivation indices and multiple ethnic subgroups, and the JBS3 risk calculator 16 are common in the United Kingdom. The ASCVD specifically incorporates cohorts with individuals of Hispanic and African-American descent to allow its use in a contemporary US population 2.īesides these risk scores, the PROCAM (Prospective Cardiovascular Muenster Study) algorithm ( and the ARRIBA – algorithm (which is derived from the FRS, but has not previously been validated empirically) are commonly used in Germany. The current North American guideline uses the ASCVD (atherosclerotic cardiovascular disease score, sometimes coined Pooled Cohort Equation) to account for the historical nature and ethnic population limitations of the FRS. Unlike other calculators, the ESC-HS provides the risk of cardiovascular mortality only, but not of non-fatal events and a factor for the conversion of the results of this algorithm into other is not available. The guideline of the NCEP/ATP (National Cholesterol Education Program Adult Treatment Panel) III from 2002 3, the guidelines of the European Society of Cardiology (ESC) and the European Atherosclerosis Society (EAS) for prevention and for the treatment of dyslipidemia 4, 5 have recommended the Framingham risk score (FRS) 12 and the ESC Heart Score (ESC-HS) 13, respectively. To determine this risk, US American 2, 3, European 4, 5 and German 6, 7, 8, 9, 10 guidelines recommend different risk equations. In 2015, 17,7 million people died from cardiovascular diseases worldwide of which an estimated 7,4 million were due to coronary heart disease and 6,7 million due to stroke ( In Germany, the direct costs for the treatment of cardiac and circulatory diseases are approximately 46 billion euros per year (2015) and they contribute to about one-sixth of the total healthcare costs, not including indirect costs of productivity losses ( ).Īccording to relevant international and national guidelines for cardiovascular disease prevention, the intensity of drug interventions in primary prevention depends on the assessment of an individual´s cardiovascular risk. Due to the most precise calibration over a wide range of risks, the large age range covered and the combined endpoint including non-fatal and fatal events, the ASCVD equation provides valid risk prediction for primary prevention in Germany.Ĭardiovascular diseases are the leading cause of death in Europe and worldwide 1. At a risk threshold of 10 percent in 10 years, the ACC/AHA atherosclerotic cardiovascular disease (ASCVD) equation has a sensitivity to identify future CVD events of approximately 80%, with the highest specificity (69%) and positive predictive value (17%) among all the equations. With three out of 10 risk scores calculated and observed risks well coincided. Absolute risks differ widely, in part due to the components of clinical endpoints predicted: The risk equations produced median risks between 8.4% and 2.0%. All risk equations have a similar discriminatory power. The risk equations correlate well with each other. We have evaluated the correlation, discrimination and calibration of ten commonly used risk equations in primary care in 4044 participants of the DETECT (Diabetes and Cardiovascular Risk Evaluation: Targets and Essential Data for Commitment of Treatment) study. A comparison of these scores in a German population has not been performed. Guidelines for prevention of cardiovascular diseases use risk scores to guide the intensity of treatment.
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