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The grey zone: What to do for the “intermediate risk” patient?

The grey zone: What to do for the “intermediate risk” patient?

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The grey zone: What to do for the “intermediate risk” patient?

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  1. The grey zone: What to do for the “intermediate risk” patient?

  2. Lifestyle-Heart Hypothesis Mozaffarian et al. Circulation 2008;117;3031-3038

  3. Atherosclerosis: Traditional and novel risk factors • Interheart: Developed and developing countries (N = approx 30,000) • IHD Risk Factor Odds Ratio Population attributable risk • ApoB/ApoAI 3.25 49% • Smoking 2.87 36% • Hypertension 1.91 18% • Diabetes 2.37 10% • Abdominal obesity 1.12 – 1.62 20% • Psychosocial 2.67 33% • Diet (fruit & veg) 0.70 14% • Activity 0.86 12% • Alcohol (not binge) 0.91 7%

  4. Atheroma: Stages and timeframe

  5. Atheroma is proportional to the number and severity of classic risk factors Where is my patient?

  6. Novel risk factors and atheroma

  7. LDL-C, β-VLDL, Lp(a) AdhesionVCAM-1ICAM-1 P-selectin E-selectin Monocyte MigrationMCP-1CCR-2 oxLDL CytokinesMMPsEndothelin-1 Induction of adhesionmolecules and chemotaxis oxidation T lymphocyte Differentiation(GM-CSF) CD36SR-A CD40 IFN-gamma Foam cell Macrophage Development of an atheroma Lumen Endothelialcells Intima Internal elastic lamina Smooth muscle cells ß-VLDL = beta-very low-density lipoprotein; Lp(a) = lipoprotein (a); VCAM-1 = vascular cell adhesion molecule-1; ICAM-1 = intercellular adhesion molecule-1; MCP-1 = monocytechemoattractant protein-1; CCR-2 = specific receptor present on the surface of monocytes; oxLDL = oxidized low-density lipoprotein; MMP = matrix metalloproteinases; GM-CSF = granulocyte macrophage-colony stimulating factor; SR-A = macrophage scavenger receptor class A Adapted with permission from Fan et al, J AtherosclerThromb 2003; 10: 63

  8. Integration of risk factors: Risk calculators

  9. Limitations of CVD Risk Assessment • Underlying data (eg FRS) is historical, geographical • Suitable for non-western populations in 21st century? • Some data components are infrequently available • Left ventricular hypertrophy • No mechanism to take advantage of risk predictors • High sensitivity C-reactive protein etc • Predominant effect of age • Assigns low 10-year risk to some patients with moderate to high lifetime risk who might benefit from more aggressive management, particularly in women & younger men • Omits or fails to quantify several major risk factors • Family history, smoking, diabetes.

  10. High sensitivity C-reactive protein as a discriminator in intermediate risk? US Preventive Services Task Force (2009) “CRP is associated with CHD events....Adding CRP to risk prediction models among initially intermediate risk persons improved risk stratification. However.. evidence that reducing CRP levels prevents CHD is lacking” “ the current evidence is insufficient to assess the balance of benefits and harms of using the non-traditional risk factors studied to screen asymptomatic men and women with no history of CHD to prevent CHD events.” American Heart Assoc and CDC (2008) “the entire adult population should not be screened for hs-CRP for the purposes of CVD risk assessment.” Additional analytes, improved assays or evidence of benefits of combinations of assays may in future be found to have advantages, but further research is needed” • Canadian Cardiovascular Society (2009) • “men older than 50 years and women older than 60 years of age, of intermediate risk whose LDL-C does not already suggest treatment, hs-CRP can be used for risk stratification”

  11. Clinical risks: Microalbuminuria, renal impairment and inflammatory disorders

  12. Markers of end-organ damage BNP Hs-TnT

  13. Genetic evidence for additional risks factors

  14. Non-invasive imaging detects sub-clinical atheroma Shaw et al. Radiology 2003; 228:826-833 Raggi P et al. ArteriosclerThrombVasc Biol. 2004;24:1272-77

  15. Reclassification of intermediate risk patients

  16. Where to set the risk threshold? Benefit versus risk or benefit versus cost? “If statins cost $4/month, treatment thresholds of low-density lipoprotein cholesterol > 4 mmol/l for low-risk persons (0 to 1 risk factor), >3.3 mmol/l for moderate-risk persons (≥2 risk factors and 10-year risk <10%), and >2.6 mg/dL for moderately high-risk persons (≥2 risk factors and 10-year risk >10%) would reduce annual healthcare costs by $430 million compared with Adult Treatment Panel III guidelines”. Lazar LD. Circ 124:146-53

  17. Strategies that compete with the absolute risk approach.

  18. Establishing a risk factor • Epidemiological methods identify risk factors • The more independent risk factors for a outcome / disease, the worse each is likely to perform on its own as a predictor • What matters is the amount of the total risk attributable to the risk factor

  19. Lowestfifth Highestfifth Establishing a risk factor

  20. Rate of disease = 50 / 1000 Rate of disease = 5 / 1000 Establishing a risk factor Incidence ratio = (50/1000) / (5/1000) = 10 Odds ratio = (50/950) / (5/995)  10

  21. 60% of the population! Establishing a risk factor

  22. 1. Law MR, Watt HC, Wald NJ,.

  23. 1. Law MR, Watt HC, Wald NJ,.

  24. Threshold Threshold risk factor

  25. Continuous risk factor No threshold

  26. What happens when you treat? O.R.

  27. x? x Cholesterol

  28. Summary and transition to cases deCODE MI re class, 2 cases Complex cases 1

  29. O.R.

  30. Cholesterol reduction 1. Shepherd J, Cobbe S, et al., Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia. West of Scotland Coronary Prevention Study Group. New England Journal of Medicine, 1995. 333(20):1301.

  31. Cholesterol reduction 1. Scandinavian Simvastatin Survival Study Group, Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S).Lancet, 1994. 344(8934):1383.

  32. Cholesterol reduction

  33. 8.00 4.00 2.00 Floating Absolute Risk & 95% CI 1.00 0.50 0.25 110 120 130 140 150 160 170 Usual SBP (mmHg) Systolic blood pressure 1. Asia-Pacific Cohort Studies Collaboration, Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S).Lancet, 1994. 344(8934):1383.

  34. Coronary disease Coronary disease Odds ratio for CHD Odds ratio for CHD Stroke Diastolic blood pressure O.R. Usual diastolic blood pressure (mmHg) MacMahon S, Peto R, Cutler J, Collins R, Sorlie P, Neaton J, et al. Blood pressure, stroke and coronary heart disease. 1. Prolonged differences in blood pressure: prospective observational studies corrected for the regression dilution bias. Lancet 1990;335:765­74.

  35. Coronary disease O.R. Odds ratio for CHD Stroke Usual diastolic blood pressure (mmHg) MacMahon S, Peto R, Cutler J, Collins R, Sorlie P, Neaton J, et al. Blood pressure, stroke and coronary heart disease. 1. Prolonged differences in blood pressure: prospective observational studies corrected for the regression dilution bias. Lancet 1990;335:765­74. Diastolic blood pressure

  36. Smoking Yusuf S, Hawken S, et al. 2004: Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet, 364(9438): p. 937.

  37. Yusuf S, Hawken S, et al.2004:Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study.Lancet, 364(9438): p. 937.

  38. Attributable risk 1. Law MR, Watt HC, Wald NJ,.

  39. Framingham equation • = 0 + 1 x female + 2 x log(age) + 3 x log(age) x female + 4 x [log(age)]2 x female + 5 x log(SBP) + 6 x cigarettes + 7 x log(TC/HDL) + 8 x diabetes + 9 x diabetes x female + 10 LVH •  = exp(0 + 1 ) • u = [log(10)] - ] /  • 10 y predicted P for CHD = 1 – exp(-exp(u))

  40. Framingham equation • = 0 + 1 x female + 2 x log(age) + 3 x log(age) x female + 4 x [log(age)]2 x female + 5 x log(SBP) + 6 x cigarettes + 7 x log(TC/HDL) + 8 x diabetes + 9 x diabetes x female + 10 LVH •  = exp(0 + 1 ) • u = [log(10)] - ] /  • 10 y predicted P for CHD = 1 – exp(-exp(u))

  41. Framingham equation mismatches

  42. Framingham equation recalibration

  43. Limitations • Underestimates for extremes of risk factors • Younger people have lower risk • But more life years lost • Consider projecting risk forward in time • Normalising for age • New/novel risk factors • Continuous HbA1c • hsCRP • Lp(a) • Apo E4/E4 • Obesity • CKD

  44. Implications of global risk approach Treat anyone at high risk 1. Law MR, Watt HC, Wald NJ, The Underlying Risk of Death After Myocardial Infarction in the Absence of Treatment. Archives of Internal Medicine, 2002;162(21):2405.

  45. The major determinant of risk is existing disease Treat anyone at high risk • Untreated MI: • Death rates for first event: 36% • Before hospital 23% • During admission 16% (of those admitted) • Subsequent events: 53% • Before hospital 33% • During admission 30% 1. Law MR, Watt HC, Wald NJ, The Underlying Risk of Death After Myocardial Infarction in the Absence of Treatment. Archives of Internal Medicine, 2002;162(21):2405.

  46. The major determinant of risk is existing disease Treat anyone at high risk • Untreated MI: First event • Death rates for first year: 10.3% • Stroke & heart disease 9.6% • Annual death rate 5.3% (for life) • Stroke & heart disease 4.6% • Subsequent events: • First year 21% (19% CVD) • Annual death rate 12% (10% CVD) 1. Law MR, Watt HC, Wald NJ, The Underlying Risk of Death After Myocardial Infarction in the Absence of Treatment. Archives of Internal Medicine, 2002;162(21):2405.