Cardiology Update 211 Davos 14. 18. February 211 Improvement of Risk Prediction for Coronary Events using Signs of Subclinical Atherosclerosis and Biomarkers Raimund Erbel Department of Cardiology West-German Heart Center University Duisburg-Essen www.wdhz.de erbel@uk-essen.de
Improvement of Risk Prediction for Coronary Events using Signs of Subclinical Atherosclerosis and Biomarkers Proportion of in-hospital CHD Death Proportion of CHD deaths (%) within 28 days occurring in hospital by sex, age, and calendar year, 1991 to 26. Women Men Kerstin Dudas et. al. Circulation 123:46-52, /211 Leszek K Borysiewicz
Improvement of Risk Prediction for Coronary Events using Signs of Subclinical Atherosclerosis and Biomarkers Most Deaths of AMI occur out of the hospital Mortality due to CHD in the hospital (within 28 days) and out of the hospital per 1 population 35 1 84 years of age, 1991 to 26. Kerstin Dudas et. al. Circulation 123:46-52, /211
1.Step: Score based Risk Stratification A. Framingham Assmann et al. Circulation 15:31-315, 22 B. PROCAM JAMA 385, 21 Graham I et al EJCPR 14 (suppl 2:S1-113), 27
2. Step based Risk Categorization Low risk Intermediate risk < 1% / 1 years 1 2% / 1 years advice for healthy lifestyle - detection of signs of subclinical atherosclerosis High risk = equivalent to post AMI > 2% / 1 years intensive therapy / risk factor modification + Greenland et al. Circulation 2;11:111-116 Greenland et al. Circulation 21;14:1863-1867 NCEP / ATP III JAMA 21;285:2486-97 # Erbel et al. Atherosclerosis 27;197:662-72
Observed 5-yr Event Rate [%] 2. Step: Risk Prediction for Coronary Events using Framingham Risk Score in HNR study Events / # at Risk: Relative Risk: 2 16 25 / 2165 1. 37 / 133 2.46 (1.49-4.7) p=.3 29 / 498 5.4 (2.98-8.53) 12 p=.3 8 5.8 % 4 1.2 % 2.8 % Low Intermediate High Framingham Risk Score Erbel R et. al. JACC 56:1397-46, 21
3. Step: subclinical signs of atherosclerosis used for further risk stratification Prevalence of risk categories in Germany for healthy lifestyle Low Risk Men / Women 3% / 71% < 1% / 1 years - Imaging techniques Intermediate Risk 39% / 2% 1 2% / 1 years Non imaging techniques Stress ECG (M 45-6 J) Biomarker High Risk 31% / 9% > 2% / 1 years + Data from the Heinz Nixdorf Recall Study# (incl. ATP III risk equivalents*) intensive therapy / risk factor modification Greenland et al. Circulation 2;11:111-116 Greenland et al. Circulation 21;14:1863-1867 NCEP / ATP III JAMA 21;285:2486-97 # Erbel et al. Atherosclerosis 27;197:662-72
Di82 Imaging of Coronary Subclinical Atherosclerosis Non invasive Methods MRT CT/CTA Vasomotion testing PET EKG ECHOCARDIOGRAPHY SCINTIGRAPHY Invasive Methods OCT IVUS/ICD IRS CORONARY ANGIOGRAPHY % 2% 45% 5% 7% 9% Remodeling Life time modified according to Erbel R et al HERZ 32:351-55, 27 originally ERBEL R HERZ 21: 75-77, 1996
Non-Invasive Imaging of Subclinical Coronary Atherosclerosis using Computed Tomography No CAC 56 year M Ao LM RVOT LAD Score 49 CAC 51 year M Score Score 269 115 64 year F 5 year M Detection - Distribution Quantification
Non-Invasive Imaging of Subclinical Coronary Atherosclerosis using Computed Tomography - < 2 s scan time - 1-1.3 msv X-ray exposure - 1 ms acquisition time - standardized protocols: Agatston-Score Imaging of coronary artery calcification as a specific sign of atherosclerosis - 15-2 min total time -.94 Kappa value for interinstitutional variation Agatston et al. JACC 15:827-32, 199 Hunold P et al Radiology 226:14552,23 Schmermund et al. Z Kardiol 92:I/385,23
Observed 5-yr Event Rate [%] 3. Step: Improving Risk Prediction for Coronary Events using Signs of Coronary Subclinical Atherosclerosis by CT Events / # at Risk: Crude Relative Risk: FRS-adjusted* RR: 2 16 12 8 11 / 1287 1. 1. p=.13 24 / 1624 1.73 (.85-3.52) 1.46 (.71-3.) p=.2 23 / 659 4.8 (2.-8.33) 3.6 (1.48-6.32) p=.7 33 / 396 9.75 (4.97-19.11) 6.25 (3.1-13.) 8.3 % 4.9 % 1.5 % 3.5 % <-99 1-399 4 CAC Scoring Erbel R et. al. JACC 56:1397-46, 21
Improvement of Risk Prediction for Coronary Events using Signs of Coronary Subclinical Atherosclerosis by CT categories Meta-analysis HNR study Meta-analysis HNR study Meta-analysis HNR study Meta-analysis HNR study Greenland et al. ACCF/AHA 27 Clinical expert consensus document JACC 115:42, 27 Erbel et al JACC 56:1397-46, 21
Improvement of Risk Prediction for Coronary Events using Signs of Coronary Subclinical Atherosclerosis by CT Rotterdam Study Elias-Smale SE et al JACC 56:147-14, 21
Improvement of Risk Prediction for Coronary Events using Signs of Subclinical Atherosclerosis by CT demonstrated by the Net Reclassification Improvement NRI NRI: 2.8% (p=.4) low intermediate high Erbel R et. al. JACC 56:1397-46, 21
Improvement of Risk Prediction for Coronary Events using Signs of Subclinical Atherosclerosis by CT demonstrated by the Net Reclassification Improvement NRI Classification according to FRS Reclassification accounting for CAC scores Low Intermed. High Total Coronary events <1% 1-2% >2% Total Number 25 12 37 9 9 16 29 45 25 37 29 91 No coronary events <1% 1-2% >2% Total 214 85 2945 293 293 168 469 637 214 1266 469 3875 NRI: 2.8% (p=.4) Erbel R et. al. JACC 56:1397-46, 21
Improvement of Risk Prediction for Coronary Events using Signs of Subclinical Atherosclerosis by CT demonstrated by the Net Reclassification Improvement NRI Comparison to the FRS 6-2% instead of 1-2% Classification according to FRS 1-year event rate with events - low - intermediate - high Total without events - low - intermediate - high Total Reclassification accounting for CAC scores low intermed. high Total 7 27 34 933 187 283 Erbel R et. al. JACC 56:1397-46, 21 12 12 479 479 18 29 47 246 58 754 NRI = 3.6% (p<.1) 7 57 29 93 933 2595 58 436
3. Step: Improving Risk Prediction for Coronary Events using Signs of Inflammation a Biomarker Prevalence of risk categories in Germany advice for for healthy lifestyle Low Risk Men / Women 3% / 71% < 1% / 1 years - Intermediate Risk 39% / 2% 1 2% / 1 years Detection of signs of risk for CV events Biomarker High Risk 31% / 9% > 2% / 1 years + Data from the Heinz Nixdorf Recall Study# (incl. ATP III risk equivalents*) intensive therapy / risk factor modification Greenland et al. Circulation 2;11:111-116 Greenland et al. Circulation 21;14:1863-1867 NCEP / ATP III JAMA 21;285:2486-97 # Erbel et al. Atherosclerosis 27;197:662-72
Improvement of Risk Prediction for Coronary Events using Biomarkers Lipoprotein (a) Homocystein Cholesterol (TC) LDL-Cholesterol (LDLC) Univariate Analysis for cardiac deah, AMI, revascularisation n = 28.263 * n = 4.348 TC/HDLC-Ratio HS-CRP Calcium Score *.5 1 2 3 4 5 6 7 8 9 1 11 Relative Risk of Future Cardiovascular Events Ridker PM et al Circulation 13: 1813, 21 *O Malley PG et al Am J Cardiol 85: 945, 21
Observed 5-yr Event Rate [%] 3. Step: Improving Risk Prediction for Coronary Events using the Biomarker hs-crp Events / # at Risk: Crude Relative Risk: FRS-adjusted* RR: 2 23 / 1387 1. 1. 31 / 1682 1.11 (.65-1.9).93 (.54-1.6) 37 / 897 2.49 (1.49-4.16) 1.87 (1.9-3.21) 16 p=.6 12 8 4 Möhlenkamp S et al p=.7 4.1 % 1.7 % 1.8 % <1. mg/l 1-3 mg/l >3 mg/l hscrp Categories JACC 211 in press
Improvement of Risk Prediction for Coronary Events using the Biomarker hs-crp vs CAC mg/l hs-crp Möhlenkamp S et al JACC 211 in press
Sensitivity Improvement of Risk Prediction for Coronary Events using the Biomarker hs-crp vs CAC 1.75.5.25 FRS only:.691 (.638-.744) FRS+hsCRP:.74 (.652-.757) FRS+log 2 (CAC+1):.752 (.7-.84) FRS+hsCRP+log 2 (CAC+1):.76 (.71-.81).25.5.75 1 1-Specificity AuROC-Curve: p=.34 p=.74 p=.14 p=.19 Möhlenkamp S et al JACC 211 in press
Improvement of Risk Prediction for Coronary Events using the Biomarker hs-crp Net Reclassification Improvement Classification according to FRS Coronary events <1% 1-2% >2% Total Number No coronary events <1% 1-2% >2% Total Reclassification accounting for hscrp scores Low Intermed. High Total 25 9 34 214 388 2528 14 14 579 579 14 29 43 299 469 768 25 37 29 91 214 1266 469 3875 NRI: 7.8% (p=.14) Möhlenkamp S et al JACC 211 in press
Improvement of Risk Prediction for Coronary Events using Signs of Subclinical Atherosclerosis and Biomarkers Risk Marker / Factor: NRI p-value Reference Multiple Biomarker Score 26.7% p=.5 (Zethelius, NEJM 28)* (Troponin I, NT-proBNP, Cystatin C, CRP) Multiple Biomarker Score 14.6% p=ns (Melander, JAMA 29)* (MR-proADM, NT-proBNP) HDL-Cholesterol (Framingham) 12.1% p<.1 (Pencina, Stat Med 28) HDL-Cholesterol (SCORE-Data) 2.2% p=.6 (Cooney, EJCPR 29) hscrp (women) 5.7% p<.1 (Cook, Ann Int Med 26) hscrp (men and women) 11.8% p<.9 (Wilson Cirulation 28) hscrp (men) 14.1% p<.1 (Ridker, Circulation 28)* HbA1c (men) 3.4% p=.6 (Simmons, Arch Int Med 28) HbA1c (women) - 2.2% p=.27 (Simmons, Arch Int Med 28) CAC HNR(ATP III, FRS 1-2%, 6-1%) 18.8, 21.7%, 3.6% p=.2 (Erbel, JACC 21)* Rotterdam FRS 1 2 % 14% p<.1 also hard events,older MESA FRS 6 2% 3% p<.1 also soft endpoints modified from Cooney et al. JACC 54 :129-1227, 29 Erbel R et al JACC 56 :1397-46, 21
Improvement of Risk Prediction for Coronary Events using Signs of Subclinical Atherosclerosis and Biomarkers Risk Marker / Factor: NRI p-value Reference Multiple Biomarker Score 26.7% p=.5 (Zethelius, NEJM 28)* (Troponin I, NT-proBNP, Cystatin C, CRP) Multiple Biomarker Score 14.6% p=ns (Melander, JAMA 29)* (MR-proADM, NT-proBNP) HDL-Cholesterol (Framingham) 12.1% p<.1 (Pencina, Stat Med 28) HDL-Cholesterol (SCORE-Data) 2.2% p=.6 (Cooney, EJCPR 29) Heart Rate 1.1% p=ns (Cooney, ESC 29, Abstract) hscrp (women) 5.7% p<.1 (Cook, Ann Int Med 26) hscrp (men and women) 11.8% p<.9 (Wilson Cirulation 28) hscrp (men) 14.1% p<.1 (Ridker, Circulation 28)* hscrp (total 7.8% p <.14 (Möhlenkamp JACC 211) HbA1c (men) 3.4% p=.6 (Simmons, Arch Int Med 28) HbA1c (women) - 2.2% p=.27 (Simmons, Arch Int Med 28) CAC (ATP III, FRS 1-2%, 6-1%) 18.8, 21.7%, 3.6% p=.2 (Erbel JACC 21)* modified from Cooney et al. JACC 54 :129-1227, 29 Erbel R et al JACC 56 :1397-46, 21
I dedicate my lecture to Philip Poole-Wilson and Helmut Drexler
Improvement of Risk Prediction for Coronary Events using Signs of Subclinical Atherosclerosis and Biomarkers Conclusion In comparison to other signs of subclincial atherosclerosis CAC seems to be the method of choice for improvement of risk prediction. And cardiology has to turn its attention to prevention, because here the biggest target for risk improvement has to be recognized as the majority of patient (6 to 8 %), who die from AMI, die outside the hospital and do not reach the hospital.
Background for Improving Risk Prediction Acute onset of coronary syndromes still combined with - up to 5 % rate of sudden deaths Fox CS et al Circulation 11: 522-7, 24 AHA: Heart Disease and Stroke Update 29 at a glance - 6 % of deaths outside the hospital with no improvement over the last 1 years (MONICA/KORA) Löwel H et al Dtsch Ärztebl 13:A616-22, 26 - prevention at top of list of measures to reduce case fatality from CAD Chambless et al (MONICA study) Circulation 96: 3849-59,1997
Aim of the Study Heinz Nixdorf Recall Study (HNR) Risk Factors, Evaluation of Coronary Calcium and Lifestyle coronary calcium as a sign of subclinical coronary atherosclerosis improves risk prediction for cardiovascular events in comparison to risk factors Initiated in 1999 and started in 2 Funded by the Heinz Nixdorf Foundation (chairman: G Schmidţ) International Advisory Board: Th Meinertz, (chair) supported by German Foundation of Research Erbel et al In: Late breaking clinical trial, ACC 29
Methods I of the Heinz Nixdorf Recall Study - prospective, population-based cohort study according to GEP - random samples from resident registration offices - 4814 men and women, aged 45 75 years (response: 56%) between 12/2 and 6/23 - urban population with 1.5 million inhabitants in an big city area of 8 million people - study certified and recertified according to ISO 91:2 Schmermund A et al Am Heart J 144:212-18, 22 Stang A et al Eur J Epidemiol 2: 489-96, 25 Dragano N et al Eur J Cardvasc Prev Rehab 14:568-74, 27
Mason Sones in Frankfurt 1978... we are still living in a world where almost 1/3 of the patients who die... die suddenly before we were even aware that these people were ill or that their lives were in jeopardy. So it seems to me that the most important problem we face is to find a way of recognizing these people before they drop dead and tell us that they were sick In: Coronary Heart Disease, 3rd Int. Symposium Frankfurt, Kaltenbach M, Lichtlen P, Balcon R, Bussmann WD (eds) Thieme, Stuttgart 1978; 83
1-sensitivity Improvement of Risk Prediction for Coronary Events using Signs of Subclinical Atherosclerosis by CT MESA-Study: - population-based - 6814 vs 4814 subjects - age: 45-84 vs 45-75 years - 6 vs 3 cities - 4 vs 1 ethnic groups - no CVD at entry - follow-up: 3.5 vs 5 years CAC+FRS AuROC=.83 CAC alone AuROC=.78 (p=.6 vs. CAC+FRS) FRS alone AuROC=.79 (p=.1 vs. CAC+FRS) HNR.749** HNR.741* HNR.681 Comparison of MESA and HNR not randomly vs randomly selected CAC burden known versus unknown results!! ΔAuROC.51 vs.68 * p=.46, ** p=.3 Detrano et al NEJM 28 Erbel et al JACC 56:1397-46, 21
Improvement of Risk Prediction for Coronary Events using Signs of Subclinical Atherosclerosis by CT Combined End-points Hard Events HNR.749** calcium score better than percentile cut-off values like 75th percentile Budoff M et al J Am Coll Cardiol 53:345-52, 29 Brown ER et al Radiology 247:669-75, 28 Erbel et al JACC 56:1397-46, 21
Improvement of Risk Prediction for Coronary Events using Signs of Subclinical Atherosclerosis and Biomarkers Helmut Drexler died 6 months later with 58 years Philip Alexander Poole-Wilson death with 66 years March 4, 29 Two weeks after last Update in Cardiology In Davos
Methods II: for detection of Subclinical atherosclerosis - Framingham Risk Score - electron beam CT (GE-Imatron, San Francisco), - for coronary artery calcification scoring (Agatston score) - carotid ultrasound for measuring intimal media thickness and plaques - blood pressure at ankle and arm for ankle-arm index (ABI) measurement Stang A et al Am J Epidemiol 164:85-94, 26 Erbel R et al Atherosclerosis 197:662-72, 28 Schmermund A et Atherosclerosis 185:177-82, 26 Greenland P et al Circulation 115:42-26, 27
Erbel et al., (eingereicht) RR für CAC und hscrp
Endotheliale Dysfunktion Herrmann J, Lerman A Herz 27 in press
Atherosklerose Pathogenese Herrmann J, Lerman A Herz 27 in press 39
Atherosklerose: Gefaesswand als Target Herrmann J, Lerman A Herz 27 in press
Atherosklerose Pathogenese Herrmann J, Lerman A Herz 27 in press
HeartScore Classification
Risikofaktoren der Atherosklerose (Hypertonie, Dyslipidämia, Diabetes. Rauchen, Adipositas, Alter, Geschlecht Mentaler Stress, chronischeentzündung) Endotheliale Dysfunktion EPCs (Zahlreduktion, Funktionsstörung) 1. Gestörte Regulation des vaskulären Tonus und Struktur 2. Gesteigerte vaskuläre Inflammation Entwicklung und Progression der Atherosklerose 3.Prothrombotische Phänotyp Änderung des Endothels 4. Gestörte endogene endotheliale Reparation Giannotti/Landmesser Herz 32:568-72, 27
% Participants Non-Invasive Imaging of Subclinical Coronary Atherosclerosis using Computed Tomography 7 6 5 4 3 2 1 Männer Male Frauen Female Prevalence of CAC 82 % Men 55 % Women -9 1-99 1-399 4-999 >= 1 Schmermund et al Atherosclerosis 26
Agatston CAC Score Agatston CAC Score Non-Invasive Imaging of Subclinical Coronary Atherosclerosis using Computed Tomography 5th CAC-Percentile 9th CAC-Percentile 4 3 3 MESA HNR 25 2 MESA HNR 2 15 1 1 5 5 55 6 65 7 75 8 5 55 6 65 7 75 8 Age/years Age/years MESA multiethnic study of atherosclerosis McClelland et al. Circulation 26 Schmermund et al Atherosclerosis 26
CAC Agatston Score Unit Non-Invasive Imaging of Subclinical Coronary Atherosclerosis using Computed Tomography smoking and coronary artery calcification no smoking 3 cigaretts/die, stop 2 years ago 3 cigaretts/die Current Smoking Former smoking nosmoking Age/years Jöckel et al Atherosclerosis 28 46
Veränderung des Kalkscore [%] Change of CAC/ % Non-Invasive Imaging of Subclinical Coronary Atherosclerosis using Computed Tomography 3 25 pollution and coronary artery calcification adjusted analysis 2 15 1 5-5 -1 Distanz >2; PM<=22 (141) Distanz >2; PM>25 (84) Rest (3339) Distanz <=1; PM<=22 (33) Distanz <=1; PM>25 (38) adjusted for age, sex, education, smoking, hypertension, D.m., cholesterol, living area B Hoffmann et al Circulation116:489-496, 27
Coronary artery calcification Agatston Score Unit Coronary artery calcification Agatston Score Unit Non-Invasive Imaging of Subclinical Coronary Atherosclerosis using Computed Tomography socio-economics and coronary artery calcification Men Women Income quartiles Income quartiles N Dragano et al Eur J Cardiovasc Prev Rehabil 14:568-74 27
Net Reclassification Improvement by CAC in Comparison to the Framingham Risk Score Comparison to the FRS 6-2% instead of 1-2% Classification according to FRS 1-year event rate with events Reclassification accounting for CAC scores low intermed. high Total - low - intermediate - high Total 7 27 34 12 12 18 29 47 7 57 29 93 without events - low - intermediate - high Total 933 187 283 479 479 246 58 754 933 2595 58 436 NRI = 3.6% (p<.1) Note: Folie 49 more correct Titel down- than up classification in those with events