Mult ltidisciplinaire Ric ichtlijn CVRM NVIVG symposium September 7, 2018 Frank L.J. Visseren
Disclosures • Research ZonMw, Wellerdieck-de Goede fonds, Leatare foundation, Vrienden UMC Utrecht, Dutch Heart Foundation • Honoraria None • Stocks None • Other … Fase II/III clinical research in the field of lipid-lowering (Sanofi, Medicines Company, Amgen, Pfizer, Eli Lilly, Merck, ISIS) Guideline committees: CV Risk Management, CV Risk Management in elderly, (Genetic) lipid disorders
De nieuwe CVRM richtlijn Concept richtlijn maart 2018 (basis = ESC richtlijn 2016) Commentaarronde Definitieve versie richtlijn September 2018 Accordering verenigingen (NIV, NVVC, NHG, Hart-Vaat groep, NVN, Hartstichting, NVHVV) Publicatie December 2018 / Januari 2019
De nieuwe SCORE-NL tabel Concept richtlijn april 2018:
De nieuwe CVRM richtlijn Concept richtlijn april 2018: • Risico schatten: SCORE-NL, bij patienten met DM2, vaatziekten en ouderen • Healthy lifestyle ……… • Lipiden: patienten met vaatziekte LDL-c <1,8 mmol/l, patienten met (heel) hoog CV risico LDL-c <2,6 mmol/l Nog lager is prima als dat makkelijk mogelijk is • Bloeddruk: <140 mmHg, bij comorbiditeit <130 mmHg
De nieuwe CVRM richtlijn
De nieuwe CVRM richtlijn Concept richtlijn april 2018: • Risico schatten bij: • Gezonde mensen (SCORE-NL) • Patienten met DM2 (ADVANCE) • Patienten met vaatziekten (SMART) • Ouderen >70 jaar (Elderly riskscore)
10-year risk for recurrent CVD events in CVD patients: SMART risk score www.escardio.org Piepoli ea, EHJ 2016;37, 2315 – 2381 Dorresteijn ea, Heart. 2013 Jun;99(12):866-72 Kaasenbrood ea, Circulation. 2016;134:1419 – 1429
individual Risk Reduction iARR: large variation iRRR: no variation
Optimal risk reduction according to guidelines and remaining 10-year CV risk N=6904 Kaasenbrood, et al Circulation 2016;134:1419-1429
Challenges in CVD risk prediction in apparently healthy people. Specific risk score for elderly problem OK problem Lifetime CVD risk score
CVD risk prediction in elderly (>70 yrs) Lipid-lowering 10-year CV risk (adjusted for competing risks) Not all elderly at high risk BP lowering Clin Res in Cardiol. 2017 Jan;106(1):58-68 De Vries et al, ESC congress 2018, abstract 114
‘Vaatrisico’ App
Tot hier de (concept) CVRM richtlijn
Challenges in CVD risk prediction in apparently healthy people. Specific risk score for elderly problem OK problem Lifetime CVD risk score
Wouldn’t it be great to have lifetime predictions? Baseline risk Therapy effectiveness Lifetime treatment Costs and Therapy harms Competing risks benefit Level of modifiable risk factors
Progress – Model Development Dorresteijn ea, BMJ. 2016 Mar 30;352:i1548
Additional CV-free life from PCSK9-i Initiation age ≥ 40-<50 Initiation age ≥50-<60 Initiation age ≥60-<70 Initiation age ≥70 Lifetime 20 years 10 years Lifetime 20 years 10 years 20 years 10 years 10 years Risk <10% LDL<1.8 8 3 1 5 3 1 2 1 0 LDL 1.8-2.6 10 4 1 7 4 1 3 1 1 LDL ≥ 2.6 14 6 2 9 6 2 4 2 1 Risk 10-20% LDL<1.8 10 4 1 7 5 1 3 1 1 LDL 1.8-2.6 15 6 2 10 6 2 4 2 1 LDL ≥ 2.6 22 9 2 14 9 3 5 3 2 Risk 20-30% LDL<1.8 15 6 2 10 8 2 5 2 2 LDL 1.8-2.6 22 10 3 15 10 3 7 3 2 LDL ≥ 2.6 34 13 4 19 14 4 9 5 4 Risk >30% LDL<1.8 21 11 4 12 10 4 7 3 2 LDL 1.8-2.6 23 11 4 16 13 5 9 5 3 LDL ≥ 2.6 NA NA NA 32 22 8 16 7 5 Kaasenbrood et al, Heart. 2018 Apr 5. pii: heartjnl-2017-312510 with this combination of characteristics to derive a reliable median. Importantly, expected benefit is also determined by a patient’s risk of other
Lifetime predictions with Age as Time-Scale 10-year risk Lifetime risk Geskus, Biometrics 2011;67:39-49 Dorresteijn ea, BMJ. 2016 Mar 30;352:i1548
CVD risk prediction in apparently healthy people LIFE-CVD model N Jaspers, ESC congress 2018, Young Investigators Award, abstract 1149.
Lifetime prediction of CV events in vascular patients: SMART-REACH model C-statistic 0.67 (95% CI 0.66-0.68) C-statistic 0.68 (95% CI 0.67-0.70) Kaasenbrood ea, JAHA 2018 epub Dorresteijn, ESC congress 2018, abstract 3141
Great challenge for a clinician: translating the results of large clinical trials to individual patients
Much to consider, much to choose: what for whom and when? CV prevention starts with healthy lifestyle. Risk factor Drugs Dose / combi Treatment goal Lipids Statin Dose? LDL-c <2.5 mmol/l Ezetimibe Combination? LDL-c <1.8 mmol/l PCSK9-mab Even lower Blood pressure ACEi/ARB, Diuretics Dose? SBP <140 mmHg CCB, Betablocker, Combination? SBP <130 mmHg Spironolactone Elderly goal Antithrombotics Antiplatelet (COX, Dose? P2Y12, cAMP) Combination? DOAC Diabetes Metformin, SU,DPP- HbA1c <53, <58, <64 4 insulin, GLP-1, mmol/mol SGLT-2 Inflammation Triglycerides, Lp(a)
Externally validated scores for Lifetime CVD risk and Lifetime therapy benefit Lifetime CVD risk score in primary prevention • Apparently healthy people: LIFE-CVD model 1 - Derived and externally validated in cohorts: ARIC, MESA, EPIC, Heinz Nixdorf Recall (total n=69,523) • Lifetime CVD risk prediction for CVD patients Patients with CV disease: SMART-REACH model 2 - Derived and externally validated in cohorts: SMART, REACH (total n=40,388) Lifetime CVD risk prediction in patients with Diabetes • Patients with DM2: DIAL model 3 - Derived and externally validated in cohorts: Swedish NDR, Scottish Diab Reg, ADVANCE, ACCORD, ASCOT, ALLHAT, SMART (total n=587,151) CV risk prediction in elderly • Elderly patients: Elderly model 4,5 - Derived and externally validated in cohorts: PROSPER, SMART, ASCOT, HYVET (total n=11,090) 1 Jaspers, ESC congress 2018, abstract 1149 4 Stam-Slob et al, Clin Res in Cardiol. 2017 Jan;106(1):58-68 2 Kaasenbrood et al, JAHA 2018 5 De Vries et al, ESC congress 2018, abstract 114 3 Berkelmans et al, in revision
Individual lifetime treatment effects: gain in CVD-free life Lifetime risk Treatment effects CVD-free life Much to consider, much to choose: what for who Externally validated scores for Lifetime CV risk and and when? Lifetime therapy benefit CV prevention starts with healthy lifestyle. Lifetime CVD risk score in primary prevention • Apparently healthy people: LIFE-CVD model 1 Riskfactor Drugs Dose / combi Treatment goal - Derived and externally validated in cohorts: ARIC, MESA, EPIC, Heinz Nixdorf Recall (total n=69,523) Lipids Statin Dose? LDL-c <2.5 mmol/l Ezetimibe Combination? LDL-c <1.8 mmol/l = + • PCSK9-mab Lower better? Patients with CV disease: SMART-REACH model 2 Lifetime CVD risk prediction for CVD patients Blood pressure ACEi/ARB, Diuretics Dose? SBP <140 mmHg - Derived and externally validated in cohorts: SMART, REACH (total n = 40,388) CCB, Betablocker, Combination? SBP <130 mmHg Lifetime CVD risk prediction in patients with Diabetes • Spironolactone Elderly? Patients with DM2: DIAL model 3 Antithrombotics Antiplatelet (COX, Dose? - Derived and externally validated in cohorts: Swedish NDR, Scottish diab reg, ADVANCE, ACCORD, P2Y12) Combination? ASCOT, ALLHAT, SMART (total n = 587,151) DOAC CV risk prediction in elderly • Elderly patients: Elderly model 4,5 Diabetes SGLT-2 HbA1c <53, <58, <64 - Derived and externally validated in cohorts: PROSPER, SMART, ASCOT, HYVET (total n=11,090) GLP-1 mmol/mol 1 Jaspers, ESC congress 2018, abstract 1149 New treatments Inflammation 2 Kaasenbrood et al, JAHA 2018 4 Clin Res in Cardiol. 2017 Jan;106(1):58-68 Triglycerides, Lp(a) 5 DeVries et al, ESC congress 2018, abstract 114 3 Berkelmans et al, in revision
Interactive calculator www.U-Prevent.com
Conclusie CVRM richtlijn • 1 CVRM richtlijn voor 1e en 2e lijn • Iets lagere treatment targets voor sommige patienten met HVZ (lipiden) en voor patienten met hoge bloeddruk en comorbiditeit • Risicoschatten voor iedereen!
Conclusion risk prediction • 10-year CVD Risk prediction in CVD patients, patients with DM2, Elderly • Lifetime CVD risk prediction for: • Apparently healthy people • Patients with vascular disease • Patients with Diabetes Mellitus • Estimating gain in CVD-free life from (combination of) smoking cessation, lipid- lowering, blood pressure-lowering, antithrombotic treatment
Some final thoughts Treating based on level of risk factors Treating based on risk Treating based on level of risk factors Treating based on individual treatment benefit Benefit-based Medicine!
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