1. Measuring cholesterol by L-B The Liebermann-Burchard method is used by the CDC to establish reference materials Cholesterol esters are hydrolyzed and extracted into hexane prior to the L-B reaction

2. Enzymatic cholesterol methods Enzymatic methods are most commonly adapted to automated chemistry analyzers The reaction is not entirely specific for cholesterol, but interferences in serum are minimal Cholesterol esters Cholesterol Cholesteryl ester hydroxylase Choles-4-en-3-one + H 2 O 2 Cholesterol oxidase Quinoneimine dye ( max  500 nm) Phenol 4-aminoantipyrine Peroxidase

3. Measuring HDL cholesterol Ultracentrifugation is the most accurate method –HDL has density 1.063 – 1.21 g/mL Routine methods precipitate Apo-B-100 lipoprotein with a polyanion/divalent cation –Includes VLDL, IDL, Lp(a), LDL, and chylomicrons HDL, IDL, LDL, VLDL HDL + (IDL, LDL, VLDL)  Dextran sulfate Mg ++ Newer automated methods use a modified form of cholesterol esterase, which selectively reacts with HDL cholesterol

4. HDL-C Determined using an anti human-β-lipoprotein antibody that binds to non-HDL lipoproteins and allows the quantification of HDL-C by the presence of a cholesterol esterase and cholesterol oxidase/peroxidase (CHE and CHO/POD) enzyme chromogen system Need for saline dilution when the triglycerides >1000 mg/dL (11.3 mmol/L)

5. HDL-C Audit - 0/18 specimens with triglycerides >1000 mg/dL were diluted So, we decided to dilute when triglycerides >1000 mg/dL Re-audit - 0/17 specimens with triglycerides >1000 mg/dL (11.3 mmol/L) were diluted

6. HDL-C So, we decided to investigate the use of an automated alert for the technical staff via the LIS Re-audit showed that of 21/25 specimens with triglycerides >1000 mg/dL were diluted

7. HDL-C Can we improve on this? Middleware may automatically result in: –dilution –re-analysis –phoning of results

8. Measuring triglycerides LDL is often estimated based on triglyceride concentration, using the Friedewald Equation: [LDL chol] = [Total chol] – [HDL chol] – [Triglyceride]/2.19 Triglycerides Glycerol + FFAs Lipase Glycerophosphate + ADP Glycerokinase ATP Dihydroxyacetone + H 2 O 2 Glycerophasphate oxidase Peroxidase Quinoneimine dye ( max  500 nm)

9. IS IT NOT EASIER TO PUT STATINS IN TAP WATER? Pat Twomey Royal Infirmary Edinburgh

10. How low should we go?

11. INTRODUCTION Atherosclerosis-related disease is the principal cause of mortality in the Western world Atherosclerosis-related disease is destined to become the principal cause of worldwide morbidity by 2020

12. INTRODUCTION How do we identify which patients would benefit from cardiovascular risk factor intervention as universal pharmacological treatment is not – practically possible, – economically feasible nor – psychologically desirable

13. INTRODUCTION Do we treat individual risk factors? –Raised Cholesterol –Low HDL-C –Raised BP What threshold?

14. Serum Cholesterol Levels in Men* Framingham Heart Study % Population 0 10 20 30 40 *During first 16 years of study: Entry ages 30–40 years Adapted from Castelli WP Can J Cardiol 1988;4(suppl A):5A-10A. MI No MI 150200250300350400450 Serum cholesterol 3.9 (mg/dl) (mmol/L) 5.26.57.89.110.311.6

15. INTRODUCTION

16. Cardiovascular disease risk profiles Am Heart J 1991; 121:293-8. FRAMINGHAM EQUATIONS Several sets of data – 1967 –1973 –1976 – 1991 – 1998

17. Cardiovascular disease risk profiles Am Heart J 1991; 121:293-8. FRAMINGHAM EQUATIONS Within each set, there are different disease types –a CHD risk –bStoke risk (inc TIA) –cTotal cardiovascular disease risk –dMI –eDeath from CHD –fDeath from cardiovascular disease

18. Cardiovascular disease risk profiles Am Heart J 1991; 121:293-8. FRAMINGHAM EQUATIONS  = 15.5305 + (28.4441*sex) + (-1.4792*ln(age)) + (-14.4588*ln(age)*sex) + (1.8515*(ln(age) 2 )*sex) + (-0.9119*ln(sysBP)) + (-0.2767*smoker) + (-0.7181*ln(t-cho/HDL-cho)) + (-0.1759*diabetes) + (-0.1999*diabetes*sex) + (-0.5868*LVH)  = e (0.9145 + (-0.2784*  ) p(CHD – 10-yr) = 1-e (-e (ln(10)-  /  ) ) Sex: Male = 0; female = 1 DM, smoke, LVH: 0 = No; 1 = Yes

19. FRAMINGHAM EQUATIONS

20. Joint British Recommendations Dec 1998 FRAMINGHAM EQUATIONS

21. Joint British Recommendations Dec 1998 FRAMINGHAM EQUATIONS

22. Cardiovascular disease risk profiles Am Heart J 1991; 121:293-8. FRAMINGHAM EQUATIONS The Framingham equations are derived by parametric regression model of epidemiological data The results produced are valid for populations Each population coefficient in the risk equation is subject to a confidence interval

23. FRAMINGHAM EQUATIONS Extrapolation to individuals is assumed by many In addition, it is assumed that precise results can be obtained from one determination of risk factor status and thus neglect the role of variation.

24. What we think we’re doing

25. One Target: One Bullet

26. What we think we’re doing Take Aim

27. What we think we’re doing

28. Getting closer

29. What we think we’re doing Identify the different individual from the crowd

30. What we think we’re doing (1) Too Many Targets Some scoring systems miss

31. What we think we’re doing (2) Bad Marksmanship

32. BIOLOGICAL VARIATION Average population CV – Total Cholesterol6.5% – HDL-C7.5% – SBP7%

33. ANALYTICAL VARIATION CV – Total Cholesterol2.5% – HDL-C3.4% – SBP5%

34. TOTAL VARIATION CV total = [CV biological 2 + CV analytical 2 ] 1/2 – Total Cholesterol6.9% – HDL-C8.2% – SBP8.6%

35. TOTAL VARIATION Average population 95% CI – TC5.0 +/- 0.7 mmole/L – HDL-C1.0 +/- 0.16 mmole/L – SBP140 +/- 24 mm Hg

36. CV

37. TOTAL VARIATION CV total = [CV Chol 2 + CV HDL-C 2 + CV SBP 2 ] 1/2 CV total = [6.9 2 + 8.2 2 + 8.6 2 ] 1/2 CV total = 13.7%

38. POPULATION SIMULATION 1.Population of 5,000 males and 5,000 females Add intra-individual and laboratory variation (100 simulants for each individual) and calculated CHD risk

39. POPULATION SIMULATION Different Cholesterol & HDL-C data used for male & female Lipids based on the Health Survey for England 1998 Correlation between Cholesterol & HDL-C achieved by Polar-Marsaglia-Bray Cholesky decomposition matrix method

40. POPULATION SIMULATION Smokers - random 25% Assumed no diabetics SBP as per the Health Survey for England 1998 Age range 30 - 70

41. POPULATION SIMULATION LVH defined randomly but with a different frequency for hypertensive & normotensive groups LVH assigned according to known population frequencies - 29.4 cases /1000 hypertensive simulants (defined as systolic BP >= 160mmHg) and 6.4 cases / 1000 normotensive simulants (defined as systolic BP < 160mmHg)

42. POPULATION SIMULATION

43. CUMULATIVE FREQUENCY DISTRIBUTION

44. > 15% 10 year CHD risk15.0% > 20% 10 year CHD risk7.65% > 30% 10 year CHD risk1.54%

45. CONFIDENCE INTERVALS

46. SINGLE MEASUREMENTS

47. DUPLICATE MEASUREMENTS

48. TRIPLICATE MEASUREMENTS

49. SINGLE v TRIPLICATE For every 100 whose mean risk >= 30% threshold – 20 v 15 false positives – 30 v 11 false negatives – 50 v 26 incorrectly assigned

50. SINGLE v TRIPLICATE For every 100 whose mean risk >= 20% threshold – 18 v 10 false positives – 16 v 11 false negatives – 34 v 21 incorrectly assigned

51. SINGLE v TRIPLICATE For every 100 whose mean risk >= 15% threshold – 15 v 9 false positives – 13 v 8 false negatives – 28 v 17 incorrectly assigned

52. SUMMARY There is a significant variation in the Framingham risk equations due to biological and analytical variation Biological variation is the major contributor

53. SUMMARY Future risk thresholds will be lower for statin therapy Risk assessment imprecision increases with a decreasing risk threshold The absolute number of incorrect assignments will increase

54. It Takes all the Skill out of it!

55. THANK YOU