1. Current Challenges in CardioMetabolic Testing
Kenneth French, Director of Clinical Operations

2. Disclosers
Employee at VAP Diagnostics Laboratory

3. Outline Cardiometabolic Disease:
Current Challenges and Methodology Limitations
Advancements in Cardiovascular Risk Assessment
Clinical Evidence and Guideline Recommendations
Other markers to assess CVD risk

4. Cardiovascular Disease
CVD is an Epidemic
1 in 3 US adults has 1 or more types of CVD1
Heart disease accounts for 25% of all US mortalities2
811,940 yearly deaths from CVD
CVD kills more women each year than the next 3 causes of death combined3
Cardiovascular Disease
Diabetes affects 25.8 million people of the US population
Diabetes markedly increases the risk of MI, stroke, amputation, and death as a result of metabolic abnormalities4
At least 65% of people with diabetes die from some form of heart disease or stroke5
NCEP ATP III established diabetes as a CVD risk equivalent in mandating aggressive antiatherosclerotic therapy4,6
Metabolic Disease
NCEP ATP III=National Cholesterol Education Program Adult Treatment Panel III.
Roger VL, et al. Circulation. 2011;123(4):e18-e209.
Beckman JA, et al. JAMA. 2002;287(19).
Gutstein DE, et al. Clin Pharmacol Ther. 2012;91(1).
NDEP. Available at: Accessed August 13, 2013.
WomenHeart. Available at: resmgr/docs/women,_heart_disease,_and_di.pdf. Accessed September 4, 2013.
NCEP Adult Treatment Panel III. Circulation. 2002;106(25):

5. Why does CVD remain the number 1 Killer?
Awareness?
Medications?
Identification?

6. Lack of Quality Diagnostics
50% of all people who experienced a cardiovascular events had recently received “normal” basic cholesterol result1
Basic Cholesterol Test (1973)
Calculated LDL-C = TC – HDL – TG(fasting)/5
1. Stamper MJ, Ridker PM, Dzau VJ. Risk factors criteria. Circulation. 2004;109(25 Suppl 1):IV3-5

7. Basic Cholesterol Testing Underestimates LDL-C Up to 60% in Patients
An independent Study of 1.3 million patients conducted by Johns Hopkins Cardiology
Note: this is over 2,900 times the size of the original publication that described Friedewald LDL-C estimation
10-20% of patients with normal triglyceride levels (<150mg/dL) were reclassified as not meeting LDL-C goal
25-60% of patients with abnormal triglyceride levels (>150mg/dL) were reclassified as not meeting LDL-C goal
Martin SS, Blaha MJ, Elshazly MB, Brinton EA, Toth PP, McEvoy JW, et al. J Am Coll Cardiol. 2013;62(8):

8. Magnitude of Underestimation in Friedewald LDL-C
Discordance in Friedewald and Direct LDL-C by TG Strata
59.4%
51.9%
39.1 %
25.0%
20.3%
10.4%
n=8042
n=2678
n=11,456
n=10,544
n=13,265
n=10,838
n=24,988
n=19,677
Triglycerides
The basic lipid panel misclassifies patient goal attainment rates
Martin SS, et al. J Am Coll Cardiol *VLDL = Very Large Database of Lipids

9. LDL-C Measurements Affect Treatment1
The basic lipid panel produces significantly underestimated LDL-C measurements.2,3
Patients with elevated triglycerides frequently receive inaccurate LDL-C measurements
Lindsey CC, Graham MR, Johnston TP, Kiroff CG, Freshley A. Pharmacother. 2004;24(2):
Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. JAMA. 2001;285(19):
Martin SS, Blaha MJ, Elshazly MB, Brinton EA, Toth PP, McEvoy JW, et al. J Am Coll Cardiol. 2013;62(8):

10. Underestimation of LDL-C = Underestimation of Risk
What if an LDL-C of 100mg/dL is actually 136mg/dL?

11. Summary of Basic Cholesterol Testing Limitations
Developed by Friedewald in 19731
Basic Lipid Panel Underestimates LDL-C in 50% of Patients3
Underestimation Leads to False LDL-C
Inaccurate in nonfasting state and/or when:
Fasting 12 hours
TG 150 mg/dL2-4
LDL-C 100 mg/dL4
Impact: Underestimation of LDL-C Leads to Underestimation of Risk
Problematic patients for Friedewald include5
Frederickson class I, III, or V hyperlipoproteinemia1
Diabetes, insulin resistance, or metabolic syndrome5
Liver disease5
Nephrotic syndrome or chronic renal insufficiency5
Hormone replacement6
Hypothyroidism5
Protease Inhibitors or other medications5
Progestins, anabolic steroids and corticosteroids
Friedewald WT, et al. Clin Chem. 1972;18(6).
Scharnagl H, et al. Clin Chem Lab Med. 2001;39(5):
Lindsey CC, et al. Pharmacotherapy. 2004;24(2).
NCEP ATP III. Circulation. 2002;106(25).
Martin SS, et al. J Am Coll Cardiol
Legault C, et al. J Clin Epidemiol. 1999;52(12).

12. Technologies to Assess Lipoprotein Risk
VAP Diagnostics Laboratory – Vertical Auto Profile (VAP) Lipid Panel
LabCorp – Nuclear Magnetic Resonance (NMR) LipoProfile
Quest Diagnostics – Cardio IQ Ion Mobility
Please visit these respective labs for more information about their services.

13. Why Understand Cholesterol/Lipoprotein Physiology?
Current routine cholesterol assessment does not measure many of the known lipid parameters known to increase CVD risk
Current Guidelines discuss lipoprotein components not measured routine cholesterol testing

19. 2/3 of the story
1/3 of the story

20. Lipoprotein Physiology Directs Therapy
Triglyceride Disorders
Low Sugar Diet
Control Insulin Resistance
Diabetes control
IR or ER Niacin
Fenofibrate/Fenofibric acid
Omega 3-Fatty Acids
Cholesterol Disorders
Low Sat Fat Diet
Statins
Ezetimibe
Bile Acid Sequestrants
Positive glycemic effect
For Familial Hypercholesterolemia (FH)
Mipomersen
Lomitapide
PCSK9 inhibitors

21. Why Granularity Matters
Example of two patients:
Patient 1 Patient 2
ApoB 130mg/dL ApoB 130mg/dL
LDL-P 1800nmol/L LDL-P 1800nmol/L
TC 220mg/dL TC 220mg/dL
HDL-C 45mg/dL HDL-C 45mg/dL
Trigs 120mg/dL Trigs 120mg/dL
Therapy the same?

22. Why Granularity Matters – Treatment is Different
Patient 1 Patient 2 ApoB 130mg/dL ApoB 130mg/dL LDL-P 1800nmol/L LDL-P 1800nmol/L TC 220mg/dL TC 220mg/dL HDL-C 45mg/dL HDL-C 45mg/dL Trigs 120mg/dL Trigs 120mg/dL
Comprehensive Assessment Reveals:
Patient 1 Patient 2
Elevated LDL-C Elevated LDL-C
Elevated Remnant Lipoproteins
Elevated Lp(a)
Statin/Niacin or Statin/Fibrate Statin Only

23. Evidence-Based Guidelines Recommend Comprehensive Risk Factor Assessment
LDL-C accounts for 30% of the risk of premature CVD, while the remaining 70% represents residual risk factors1
Residual risk can be attributed to LDL-C subclasses, remnant lipoproteins, and other HDL-C components2-4
Cardiometabolic risk stratification and personalized approach to management are recommended2-4
National Guidelines2-5
Direct LDL-C measurement
Secondary targets of therapy
Non–HDL-C and metabolic syndrome
Emerging risk factors
Lp(a), HDL-C subclasses, small LDL pattern, ApoB, and remnant lipoproteins, LDL-P
Kreisberg RA, Oberman A. J Clin Endocrinol Metab. 2002;87(2).
Grundy SM, et al. Circulation. 2004;110(2).
NCEP ATP III. Circulation. 2002;106(25).
Jellinger PS, et al. Endocr Pract. 2012;18(suppl 1):
Brunzell JD, et al. Diabetes Care. 2008;31(4).

24. What to Consider When Choosing a Lab
Cost of services and reimbursement
Comprehensiveness of the test
How much information are you getting for one test verses ordering multiple tests?
External Validation
Accuracy, precision, reproducibility
Clinical significance
Publications, abstracts
Guideline support
Information discussed in various guidelines
Turn-around-time
Ease of use in clinical practice

25. Other Labs to consider for CVD Assessment
hsCRP
Chronic systemic inflammation
LpPLA2
Vascular specific inflammation
Cystatin C
Kidney disfunction from normal through stage 2
GGT
Independent marker for Met. Syn. And CVD
Homocysteine
Multiple others

26. Consideration for other labs
Outcome studies showing independent power over traditional risk factors
Treatment protocols in place for managing excess risk
Cost to healthcare/patient

27. Odd statistic…
The actual lab spend as a part of the overall healthcare expenditure (HCE) is low and accounts for ~2.3% of the total healthcare cost.
However, diagnostic testing guides approximately 66% of clinical decisions in cardiology and oncology.

28. Better Testing Leads to More Informed Treatment and Improved Outcomes
Whether primary or secondary prevention, the goal is to prevent the event.
Relying on standard labs has proven futile in the last few decades.
Everything clinicians do depends on the information they have at their finger tips…
Bad information in = Bad Outcomes
Good information in = Improved Outcomes

29. Thank you…