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Risk factors in heart disease Optimizing patient care
William Cromwell, MD, FAHA, FNLA Chief Medical Officer – LipoScience, Inc. Chief – Lipoprotein and Metabolic Disorders Institute Adjunct Associate Professor – Wake Forest University School of Medicine
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Disclosures William Cromwell, MD, FAHA, FNLA
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Current Perspectives on LDL Management
The causal link between high levels of low-density lipoprotein (LDL) and the development of CVD is well established 1 Increased numbers of circulating LDL particles accelerates development of atherosclerotic cardiovascular disease The longer the exposure to high LDL, the greater the risk of CVD events Lowering LDL is a central tenet of clinical practice 2013 ACC/AHA guidelines recommend a two step approach to managing LDL-related CVD risk 1 - Use moderate or high dose statin therapy in selected populations; - Monitor LDL levels on therapy and use clinical judgment in determining next steps in patient management. 1. Stone NJ, et al. Circulation 2014;129:S1-S45. 2. Otvos JD, et al. Am J Cardiol. 2002;90(8A):22i-29i. 3. Cromwell WC, Otvos JD. Am J Cardiol. 2006;98(12): 4. Cromwell WC, et al.. J Clin Lipidol. 2007;1(6): 5. Otvos JD, et al. J Clin Lipidol. 2011;5(2): 6. Sniderman AD, et al. Am J Cardiol. 2003;91(10): 7. Sniderman AD, et al. Am J Cardiol. 2001;87(6): , A798. 8. Sniderman AD. J Clin Lipidol. 2008;2(1):36-42.
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Two Ways To Measure LDL Quantity
LDL cholesterol (LDL-C) is the traditional measure of LDL, chosen for historical, not analytic or clinical reasons. Alternatively, LDL can be measured by particle number (LDL-P), or estimated by apolipoprotein B. Due to differences in the amount of cholesterol contained in LDL, alternate LDL measures (LDL-C vs. LDL-P) frequently disagree (discordance).1-7 LDL Particle Triglycerides Cholesterol LDL-P LDL-C LDL Particle Triglycerides Cholesterol LDL-P LDL-C 1. Otvos JD, et al. Am J Cardiol. 2002;90(8A):22i-29i. 2. Cromwell WC, Otvos JD. Am J Cardiol. 2006;98(12): 3. Cromwell WC, et al.. J Clin Lipidol. 2007;1(6): 4. Otvos JD, et al. J Clin Lipidol. 2011;5(2): 5. Sniderman AD, et al. Am J Cardiol. 2003;91(10): 6. Sniderman AD, et al. Am J Cardiol. 2001;87(6): , A798. 7. Sniderman AD. J Clin Lipidol. 2008;2(1):36-42.
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Alternate LDL Measures (LDL-C versus LDL-P)
Multi Ethnic Study of Atherosclerosis [MESA] (n=6,697) Otvos et al. J Clin Lipidol 2011;5:105-13
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LDL-C and LDL-P Different
Alternate LDL Measures (LDL-C versus LDL-P) Multi Ethnic Study of Atherosclerosis [MESA] (n=6,697) Discordant Measures LDL-C and LDL-P Different (50% Subjects) LDL-P > LDL-C Less Cholesterol per Particle Concordant Measures LDL-C and LDL-P Similar (50% Subjects) LDL-P < LDL-C More Cholesterol per Particle Otvos et al. J Clin Lipidol 2011;5:105-13
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< 70 mg/dL (< 5th Percentile)
Alternate LDL Measures (LDL-C versus LDL-P) Type II Diabetes Mellitus Subjects (n=2,355) 24% (n=364) Percent of Subjects 1% (n=19) 5th th th th percentile (nmol/L) 43% (n=631) 21% (n=307) 11% (n=163) LDL-C 70-99 mg/dL (5th – 20th Percentile) (n=1,484) (nmol/L) 43% (n=377) 30% (n=260) 9% (n=76) 2% (n=15) Percent of Subjects 16% (n=147) 40% LDL-C < 70 mg/dL (< 5th Percentile) (n=871) Cromwell WC, Otvos JD. AJC 2006;98:
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Alternate LDL Measures and Cardiovascular Disease
Cardiovascular risk tracks with LDL particle number When alternate LDL measures (LDL-C vs LDL particle number) agree (concordance) each measure is equally associated with CVD risk. When alternate measures are discordant (e.g., diabetes, metabolic syndrome, statin therapy), risk tracks with LDL-P, not LDL-C.1-5 1. Cromwell WC, et al.. J Clin Lipidol. 2007;1(6): 2. Otvos JD, et al. J Clin Lipidol. 2011;5(2): 3. Sniderman AD, et al. Am J Cardiol. 2003;91(10): 4. Sniderman AD, et al. Circ Cardio quality and outcomes. 2011;4(3): 5. Sniderman AD, et al. Atherosclerosis. Dec 2012;225(2):
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Associations of Alternate LDL Measures with CHD Framingham Offspring Study (n=3,066)
Years of Follow-up Event-Free Survival Concordant Discordant Better Survival Lower Risk Worse Survival Higher Risk 1.00 0.98 0.96 0.94 0.92 0.90 0.88 0.86 0.84 0.82 0.80 0.78 0.76 0.74 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Low LDL-C High LDL-P (n=282) High LDL-C Low LDL-P (n=284) Low LDL-C Low LDL-P (n=1,249) High LDL-C High LDL-P (n=1,251) Better survival Lower risk Worse survival Higher risk Cromwell WC et al. J Clin Lipidol 2007;1(6):
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Low LDL Despite High LDL-C
LDL-P and LDL-C Discordance in MESA Relations with Incident CVD Events Follow-up (years) Cumulative Percent Incidence 2 4 6 LDL-P < LDL-C Concordant LDL-P > LDL-C LDL-C 104 117 130 mg/dL LDL-P 1372 1249 1117 nmol/L 16% 33% 54% MetSyn High LDL Despite Low LDL-C LDL-C underestimates LDL-attributable risk Low LDL Despite High LDL-C LDL-C overestimates LDL-attributable risk Otvos et al. J Clin Lipidol 2011;5:105-13
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Cumulative Percent Incidence
LDL-P and LDL-C Discordance in MESA CVD Event Rates in Subgroups with Low LDL-C Concordant 2 4 6 Cumulative Percent Incidence Discordant High LDL-P Otvos et al. J Clin Lipidol 2011;5:105-13
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LDL-P and LDL-C Discordance in MESA
CVD Event Rates in Subgroups with Low LDL-P 1 Discordant High LDL-P Concordant 6 ACC/AHA Threshold for Considering Statin Therapy (7.5% risk over 10 years) 2 4 Cumulative Percent Incidence 2 1. Otvos et al. J Clin Lipidol 2011;5:105-13 2. Adapted from Stone et al. Circulation. 2013
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Circulation. Cardiovascular quality and outcomes. 2011;4(3):337-345.
A Meta-Analysis of Low-Density Lipoprotein Cholesterol, Non-High-Density Lipoprotein Cholesterol, and Apolipoprotein B as Markers of Cardiovascular Risk Allan D. Sniderman, MD; Ken Williams, MSc; John H. Contois, PhD; Howard M. Monroe, PhD; Matthew J. McQueen, MBChB, PhD; Jacqueline de Graaf, MD, PhD; Curt D. Furberg, MD, PhD Circulation. Cardiovascular quality and outcomes. 2011;4(3):
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Meta-Analysis of LDL-C, Non-HDL-C, and ApoB as Markers of Cardiovascular Risk
Study Design: Meta-analysis of all published epidemiologic studies with estimates of relative risks of fatal or nonfatal ischemic cardiovascular events and measures of non-HDL-C and apoB. 12 independent reports, including 233,455 subjects and 22,950 events, were analyzed. Major Findings: Whether analyzed individually or in head-to-head comparisons, apoB was the most potent marker of cardiovascular risk. Sniderman AD, Williams K, et al. Circulation. Cardiovascular quality and outcomes. 2011;4(3):
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Meta-Analysis of LDL-C, Non-HDL-C, and ApoB as Markers of Cardiovascular Risk
Conclusions: “The present analysis indicates that non-HDL-C is superior to LDL-C as a marker of cardiovascular risk.” “The conventional explanation would be that the gain in predictive power is due to the cholesterol in VLDL.” “The superiority of non-HDL-C over LDL-C is due to the fact that non- HDL-C is a better marker of LDL-P than LDL-C.” “When apoB and non-HDL-C are concordant, they will predict risk equally, whereas when they are discordant, apoB will be superior.” Sniderman AD, Williams K, et al. Circulation. Cardiovascular quality and outcomes. 2011;4(3):
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LDL Subclasses: 2011 National Lipid Association Recommendations
“Many studies document links between small dense LDL particles and atherosclerotic CVD.” “However, these statistical associations between small, dense LDL and CV outcomes are either significantly attenuated or abolished when the analyses are adjusted for the overall number of circulating LDL particles (LDL-P) either by adjustment for Apo B levels or by adjustment for nuclear magnetic resonance-derived LDL-P.” Adapted from Davidson, et al. J Clin Lipidol 2011;5:
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LDL Subclasses: 2011 National Lipid Association Recommendations
“To date, there is no evidence that the shift in LDL subfractions directly translates into change in disease progression or improved outcome.” “The NLA Biomarkers Expert Panel was unable to identify any patient subgroups in which LDL subfractionation is recommended.” Adapted from Davidson, et al. J Clin Lipidol 2011;5:
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Impact on Clinical Decision Making Evidence Needed to Support Use
Expectations for Novel Risk Tests versus An Alternate Measure of an Established Target Intended Application Type of Biomarker Clinical Use Impact on Clinical Decision Making Evidence Needed to Support Use Risk Assessment Novel Biomarker (lipoprotein particle size / subclasses, Inflammatory measures) Biomarker is used to enhance risk assessment Allocate patient to different risk category Significant improvement in risk stratification with the addition of new biomarker (net reclassification) 1 Risk Management (LDL particle size, Inflammatory measures) Biomarker serves as a treatment goal Modify therapy (different agents, dosage, or combinations) as indicated to achieve new therapeutic goal Outcome improvement established independent of other risk factors Newer Measure of an Established Target (e.g., LDL particle number) 1. Newer measure consistently outperforms the old measure in the setting of discordance.2 2. Improved outcomes are noted when subjects are treated to equivalent levels of the new versus old measure. 1, Ge Y, Wang TJ. J Intern Med. 2012;272(5): 2. Glasziou P, et al. Ann Intern Med. 2008;149(11):
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Recommendations for Using LDL Particle Number Measures as Targets of Therapy
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Recommendations for Using LDL Particle Number Measures as Targets of Therapy
Step 1: Stratify ASCVD risk and initiate therapy (Statin therapy if triglyceride levels < 500 mg/dL) Step 2: Assess adequacy (laboratory testing) and tolerance of therapy Step 3: If not at desired level intensify therapeutic lifestyle, consider additional therapy Intensify statin therapy; Consider combination statin &/or ezetimibe &/or colesevelam &/or niacin Step 4: Assess adequacy / tolerance of therapy with and consider additional therapeutic adjustment. Risk Level Moderate Risk High Risk DM but no other major risk and/or age < 40 DM + major CVD risk(s) (HTN, Family History, Low HDL-C, smoking) or CVD Desirable Level LDL-P (nmol/L) < 1200 < 1000 apoB (mg/dL) < 90 < 80 Adapted from Garber AJ, et al. Endocr Pract 2013;19 (Suppl 2):1-48.
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Recommendations for Using LDL Particle Number Measures as Targets of Therapy
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“These data indicate that both Apo B and LDL-P were generally in agreement in their association with diverse clinical outcomes (58.8%), but with a substantial amount of discordance (21.2%) in which one biomarker was statistically significant whereas the other was not.” “In these cases, LDL-P showed a significant association with a clinical outcome more often than apo B alone, and the level of statistical significance, as indicated by the P value, and the strength of association, as indicated by the OR, RR, and HR, was more often higher for LDL-P than it was for apo B.” Cole TG, et al. Clinical Chemistry February 2013;59(5):
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2013 ACC / AHA Cholesterol Guidelines
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2013 ACC / AHA Cholesterol Guidelines Overview
Objective: Produce treatment recommendations, based on randomized controlled trial (RCT) data, to reduce atherosclerotic cardiovascular disease (ASCVD) risk. Based on RCT data significant emphasis was placed on identifying populations most likely to benefit from statin therapy. “Because the overwhelming body of evidence came from statin RCTs, the Expert Panel appropriately focused on these statin RCTs to develop evidence-based guidelines for the reduction of ASCVD risk.” 1 1. Stone et al. Circulation. 2013
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ASCVD Statin Benefit Groups
No Stone et al. Circulation. 2013
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2013 ACC / AHA Cholesterol Guidelines Role of LDL Testing
While acknowledging the causal role of LDL in ASCVD, due to exclusive reliance on RCT data no recommendation was made for LDL treatment goals. “The panel makes no recommendations for or against specific LDL-C or non- HDL-C targets for the primary or secondary prevention of ASCVD.” 1 Although no goal is endorsed, LDL testing is advocated to aid clinical management ATP III Recommendation: LDL testing was used to achieve risk-based LDL goal 2013 ACC/AHA Recommendation: LDL testing is used to monitor therapeutic response and adherence Modifying individual treatment requires clinical judgment. “The ultimate decision about care of a particular patient must be made by the healthcare provider and patient in light of the circumstances presented by that patient.” 1 1. Stone et al. Circulation. 2013
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Statin Therapy: Monitoring Therapeutic Response and Adherence
Stone et al. Circulation. 2013
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Integrating Population Based and Individual Optimization Strategies in Practice
The 2013 ACC/AHA Guideline is a starting point for population management, but is not an end point for individual care. This highlights two different opportunities to improve patient care: - Population strategy (A) – treat population with generalized therapy to achieve relative risk reduction among the group - Individual optimization strategy (B) – monitor individual response with a reliable LDL measure and adjust care as indicated. 2013 Guidelines advise clinicians to integrate these options: - Use of A and B (start with population care, followed by individual optimization based on clinical judgment) is recommended; - Use of A only (population strategy, “Fire and Forget”) is not advised. Exclusive use of a population strategy is incapable of judging individual response to statin therapy or optimizing individual management.
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Cardiovascular Events In Treat to New Target “TNT”
Heterogeneous Response to High Intensity Statin Therapy Cardiovascular Events In Treat to New Target “TNT” 1 2 3 4 5 6 8 10 12 14 16 18 # MetSyn Components Patients with major CVD events (%) Atorva 10 mg Atorva 80 mg 56% Benefited From High Intensity Statin Therapy WHY? Atorvastatin 10 mg Atorvastatin 80 mg (LDL-C on-trial 77 mg/dL) (LDL-C on-trial 101 mg/dL) No Benefit From Aggressive Treatment (44 %) 22% Reduction in Major cardiovascular events (p=0.0002) Deedwania P, et al. The Lancet. 2006;368:
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Potential Answer to TNT is Supplied by Framingham
180 170 160 150 140 130 120 110 MetSyn (-) MetSyn (+) 2.3x risk LDL-C (mg/dL) LDL-P (nmol/L) 1100 1200 1300 1400 1500 1600 1700 1800 1 2 3 4 5 N=30 N=113 N=233 N=355 N=407 N=286 LDL-C LDL-P With Higher LDL-P, Greater Benefit Is Expected From More Intensive LDL-P Lowering. Kathiresan S, et al. Circulation 2006;113:20-27
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Journal of American Heart Association 2014;3
Relations of Change in Plasma Levels of LDL-C, Non-HDL-C and apoB With Risk Reduction From Statin Therapy: A Meta-Analysis of Randomized Trials George Thanassoulis, Ken Williams, Keying Ye, Robert Brook, Patrick Couture, Patrick R. Lawler, Jecqueline de Graaf, Curt D. Furgerg and Allan Sniderman Journal of American Heart Association 2014;3
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Meta-Analysis of LDL Measures and Risk Reduction from Statin Therapy
Objective: To evaluate the relationship between the reduction in alternate LDL measures (LDL-C, non-HDL-C, apoB) and observed cardiovascular benefit produced by statin therapy in randomized, placebo controlled trials. “The marker whose reduction relates most directly to benefit should also be the marker that is best to identify those whose outcome might be improved by further lipid lowering.” Meta-analysis was performed using both frequentist and Bayesian methods. Thanassoulis G, et al. J Am Heart Assoc. 2014;3:e000759
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Meta-Analysis of LDL Measures and Risk Reduction from Statin Therapy
Studies Selected: Analyzed all published, placebo-controlled studies, which have reported baseline and on-treatment levels of LDL- C, non-HDL-C, and apoB. Thanassoulis G, et al. J Am Heart Assoc. 2014;3:e000759
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Meta-Analysis of LDL Measures and Risk Reduction from Statin Therapy
Findings: Relative risk reduction from statin therapy in the 7 major placebo-controlled statin trials demonstrated: Risk reduction was more closely related to reductions in apoB than to reductions in either non-HDL-C or LDL-C. Changes in non-HDL-C and LDL-C appeared to be statistically indistinguishable with respect to risk reduction of statin therapy. Within trial “head-to-head” comparisons of cardiovascular risk relationship with individual LDL markers : LDL-C was 2.4% (- 3.6%, 8.4%) > non-HDL-C (P=0.445) apoB was 21.6% (12.0%, 31.2%) > LDL-C (P<0.001) apoB was 24.3% (22.4%, 26.2%) > non-HDL-C (P<0.001). Thanassoulis G, et al. J Am Heart Assoc. 2014;3:e000759
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Atherosclerosis 2014;235(2):585-591
Cardiovascular Risk in Patients Achieving Low-Density Lipoprotein Cholesterol and Particle Targets Peter P. Toth , MD, PhD Michael Grabner , PhD Rajeshwari S. Punekar , PhD Ralph A. Quimbo , MA Mark J. Cziraky , PharmD Terry A. Jacobson , MD Atherosclerosis 2014;235(2):
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Study Design Claims data between 2006 and 2012 were used to identify eligible patients achieving LDL-P <1000 nmol/L (LDL-P cohort) and patients achieving LDL-C<100 mg/dL (LDL-C cohort) without LDL-P measurements. Demographic and comorbidity differences between the two cohorts were balanced using propensity score matching however, treatment patterns were left intact. Adapted from Toth PP, et al. Atherosclerosis 2014;235(2):
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Baseline Characteristics for Patients with ≥ 12 Months of Follow-Up
Adapted from Toth PP, et al. Atherosclerosis 2014;235(2):
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Baseline Characteristics for Patients with ≥ 12 Months of Follow-Up
Adapted from Toth PP, et al. Atherosclerosis 2014;235(2):
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Study Results At every follow-up interval the LDL-P cohort demonstrated: Significant risk reduction (Hazard Ratio): 24% at 12 months 22% at 24 months 25% at 36 months Significant event reduction (Number of patients with CHD/stroke events) 1.8% (8.12% %) at 12 months 2.9% (13.9% %) at 24 months 4.4% (19.0% %) at 36 months Adapted from Toth PP, et al. Atherosclerosis 2014;235(2):
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Study Results Another metric of event reduction is the “Number Needed to Treat” (NNT). NNT = 1 / Event Reduction Represents the number of subjects needed to treat to prevent 1 event. (i.e., number of subjects needed to attain LDL- P <1000 vs LDL-C <100 to prevent 1 CHD/stroke event). 2.9 Adapted from Toth PP, et al. Atherosclerosis 2014;235(2):
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Number Needed to Treat 2014;235(2):
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Approach to the Use of LDL in Clinical Practice
Step 1: Stratify ASCVD risk (does not require LDL-P) Step 2: Institute appropriate course of treatment. Step 3: Use a reliable, FDA cleared, outcome proven LDL measure to monitor adherence and response among those treated. Step 4: Use clinical judgment in considering the need to modify individual therapy. Step 5: After modifying therapy, use a reliable, FDA cleared, outcome proven LDL measure to assess patient response. Use clinical judgment to consider modifications of treatment as indicated to optimize care.
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Reduce LDL Particle Production Improve LDL Particle Clearance
Selected Strategies to Reduce Particle Number LDL-P Target Reduce LDL Particle Production (make less) Improve LDL Particle Clearance (remove more) Diet Exercise Weight Loss Glycemic Control Co-Morbidity Management (up to 30-50% 6 LDL-P) Marine Omega-3 DHA + EPA (no 6 LDL-P) EPA Only (4-15 % 6 LDL-P) Statins (35-55% 6 LDL-P) Gut agents Ezetimibe (15-30% 6 LDL-P) Resins / Bile Acid Sequestrates Statin + Gut (50-70% 6 LDL-P) Statin + Gut + Niacin (> 60% 6 LDL-P) Adapted from Cromwell W, Dayspring T. Lipid and lipoprotein disorders: Current clinical solutions. Baltimore: International Guideline Center; 2012.
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Conclusions Guidelines recommend a two step approach to managing LDL-related CVD risk: 1 Use moderate or high dose statin therapy in selected populations; Monitor LDL levels on therapy and use clinical judgment in determining next steps in patient management. Because CVD risk tracks with apoB and NMR LDL-P 2-6, and because frequent discordance exists between LDL-C and measures of LDL-P 2-4,7-10, many expert panels advocate use of LDL particle number to adjudicate response and optimize individual therapy.11-13 Clinical utilization data confirms a significant reduction of CVD risk and events among high risk patients attaining low NMR LDL-P (mean nmol/L) versus statin treated subjects with low LDL-C (mean 79 mg/dL).14 1. Stone NJ, et al. Circulation 2014;129:S1-S45. 2. Cromwell WC, et al.. J Clin Lipidol. 2007;1(6): 3. Otvos JD, et al. J Clin Lipidol. 2011;5(2): 4. Sniderman AD, et al. Am J Cardiol. 2003;91(10): 5. Sniderman AD, et al. Circ Cardio quality and outcomes. 2011;4(3): 6. Sniderman AD, et al. Atherosclerosis. Dec 2012;225(2): 7. Otvos JD, et al. Am J Cardiol. 2002;90(8A):22i-29i. 8. Sniderman AD, et al. Am J Cardiol. 2001;87(6): , A798. 9. Cromwell WC, Otvos JD. Am J Cardiol. 2006;98(12): 10. Sniderman AD. J Clin Lipidol. 2008;2(1):36-42. 11. Contois JH et al. Clin Chem. 2009;55: 12. Davidson MH et al. J Clin Lipidol. 2011;5: 13. Garber AJ, et al. Endocr Pract 2013;19(Suppl 2):1-48. 14. Toth PP, et al. Atherosclerosis 2014;235(2):
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