measuring cholesterol by l-b the liebermann-burchard method is used by the cdc to establish...

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

HO

H2SO4/HOAc

HOO2S

Cholesterol Cholestahexaene sulfonic acid

max = 620 nm

L-B reagent

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

Cholesterylester

hydroxylase

Choles-4-en-3-one + H2O2

Cholesteroloxidase

Quinoneimine dye (max500 nm)

Phenol4-aminoantipyrinePeroxidase

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

• Newer automated methods use a modified form of cholesterol esterase, which selectively reacts with HDL cholesterol

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)

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

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

HDL-C

• Can we improve on this?

• Middleware may automatically result in:

–dilution

–re-analysis

–phoning of results

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 + FFAsLipase

Glycerophosphate + ADPGlycerokinase

ATP

Dihydroxyacetone + H2O2

Glycerophasphateoxidase

PeroxidaseQuinoneimine dye (max 500 nm)

IS IT NOT EASIER TO PUT STATINS IN TAP WATER?

Pat Twomey

Royal Infirmary Edinburgh

How low should we go?

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

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

INTRODUCTION

• Do we treat individual risk factors?

–Raised Cholesterol

–Low HDL-C

–Raised BP

• What threshold?

Serum Cholesterol Levels in Men*Framingham Heart Study

% P

op

ula

tio

n

0

10

20

30

40

*During first 16 years of study: Entry ages 30–40 yearsAdapted from Castelli WP Can J Cardiol 1988;4(suppl A):5A-10A.

MINo MI

150 200 250 300 350 400 450

Serum cholesterol

3.9(mg/dl)

(mmol/L)5.2 6.5 7.8 9.1 10.3 11.6

INTRODUCTION

Cardiovascular disease risk profiles Am Heart J 1991; 121:293-8.

FRAMINGHAM EQUATIONS

• Several sets of data

– 1967

–1973

–1976

– 1991

– 1998

Cardiovascular disease risk profiles Am Heart J 1991; 121:293-8.

FRAMINGHAM EQUATIONS

• Within each set, there are different disease types

–a CHD risk

–b Stoke risk (inc TIA)

–c Total cardiovascular disease risk

–d MI

–e Death from CHD

–f Death from cardiovascular disease

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 = 1DM, smoke, LVH: 0 = No; 1 = Yes

FRAMINGHAM EQUATIONS

Joint British Recommendations Dec 1998

FRAMINGHAM EQUATIONS

Female?(yes=1,no=0) 0Age(years) 64SBP (mmHg) 150DBP (mmHg) 85Smokes?(yes=1,no=0) 0Total - C (mmol/ l) 5.5HDL - C (mmol/ l) 0.7Diabetes(yes=1,no=0) 0

Known to haveECG-LVH? (yes=1,no=0) 0

Period of predicted risk 10(years)

Joint British Recommendations Dec 1998

FRAMINGHAM EQUATIONS

CHD risk % Stroke risk %over 10 years over 10 years

SBP 29.8 4.9

DBP 27.7 3.6

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

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.

What we think we’re doing

What we think we’re doing

One Target: One Bullet

What we think we’re doing

Take Aim

What we think we’re doing

What we think we’re doing

Getting closer

What we think we’re doing

Identify the different individual from the crowd

What we think we’re doing (1)

Too Many Targets

Some scoring systems miss

What we think we’re doing (2)

Bad Marksmanship

BIOLOGICAL VARIATION

•Average population CV

– Total Cholesterol 6.5%

– HDL-C 7.5%

– SBP 7%

ANALYTICAL VARIATION

•CV

– Total Cholesterol 2.5%

– HDL-C 3.4%

– SBP 5%

TOTAL VARIATION

• CVtotal = [CVbiological2 + CVanalytical

2]1/2

– Total Cholesterol 6.9%

– HDL-C 8.2%

– SBP 8.6%

TOTAL VARIATION

• Average population 95% CI

– TC 5.0 +/- 0.7 mmole/L

– HDL-C 1.0 +/- 0.16 mmole/L

– SBP 140 +/- 24 mm Hg

CV

Biological Analytical Total

Cholesterol 6.5% 2.5% 6.9%

HDL-C 7.5% 3.4% 8.2%

SBP 7% 5% 8.6%

TOTAL VARIATION

• CVtotal = [CVChol2 + CVHDL-C

2 + CVSBP2]1/2

• CVtotal = [6.92 + 8.22 + 8.62]1/2

• CVtotal = 13.7%

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

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

POPULATION SIMULATION

• Smokers - random 25%

• Assumed no diabetics

• SBP as per the Health Survey for

England 1998

• Age range 30 - 70

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)

POPULATION SIMULATIONMale mean Female mean

Cholesterol 5.8 mmol/l 5.6 mmol/l

HDL-C 1.3 mmol/l 1.6 mmol/l

TC:HDLcorrelation

r = 0.1 r = 0.07

SBP 136.8 mm Hg 132.5 mm Hg

CUMULATIVE FREQUENCY DISTRIBUTION

0%

20%

40%

60%

80%

100%

0% 10% 20% 30% 40%

'True' 10-year CHD Risk

Fre

qu

en

cy

CUMULATIVE FREQUENCY DISTRIBUTION

• > 15% 10 year CHD risk 15.0%

• > 20% 10 year CHD risk 7.65%

• > 30% 10 year CHD risk1.54%

CONFIDENCE INTERVALS

0%

5%

10%

15%

20%

25%

30%

35%

40%

0% 10% 20% 30% 40%

'True' Risk (%)

Es

tim

ate

d R

isk

(%

)

SINGLE MEASUREMENTS

95% CI CV%

15% +/- 5.1% 16.7%

20% +/- 6.0% 14.9%

30% +/- 6.9% 12.0%

DUPLICATE MEASUREMENTS

95% CI CV%

15% +/- 3.6% 12.0%

20% +/- 4.2% 10.5%

30% +/- 4.9% 8.2%

TRIPLICATE MEASUREMENTS

95% CI CV%

15% +/- 2.8% 9.3%

20% +/- 3.3% 8.3%

30% +/- 3.9% 6.5%

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

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

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

SUMMARY

• There is a significant variation in the Framingham risk equations due to biological and analytical variation

• Biological variation is the major contributor

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

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