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LowDensityLipoproteinSubfractions:SystematicReviewofMeasurement

MethodsandAssociationwith CardiovascularOutcomes

June16,2008

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LowDensityLipoproteinSubfractions:Systematic ReviewofMeasurementMethodsandAssociation

withCardiovascularOutcomes

TechnologyAssessmentReport

ProjectID:LIPS0707

June16, 2008

TuftsEvidencebasedPracticeCenter

EthanBalk,MDMPH

StanleyIp,MD

MeiChung,MPH

JosephLau,MD

AliceH.Lichtenstein,DSc

This reportis basedon research conductedby theTufts EvidencebasedPractice Center(EPC)undercontract totheAgency for HealthcareResearch andQuality (AHRQ), Rockville, MD(ContractNo. 290020022). Thefindings andconclusions in this document arethoseof theauthors whoareresponsiblefor its contents. Thefindings andconclusions do notnecessarilyrepresent theviews of AHRQ. Therefore,no statement in this reportshouldbeconstruedas anofficial position of theAgency for HealthcareResearch andQuality or of theU.S. Department of Health andHuman Services.

Theinformation in this report is intendedto helphealth caredecisionmakers patients andclinicians, health system leaders, andpolicymakers, make wellinformeddecisions andtherebyimprovethequality of health careservices. This reportis notintendedtobeasubstitutefor theapplication of clinical judgment. Decisions concerningtheprovision of clinical careshouldconsiderthis reportin thesameway as any medical reference andin conjunction with all otherpertinent information, ie,in thecontext of availableresources andcircumstances presentedbyindividual patients.

This reportmay beused, in wholeor in part, as the basis for development of clinical practice guidelines andotherquality enhancement tools, or as abasis for reimbursement andcoveragepolicies. AHRQor U.S.Department of Health andHuman Services endorsement of suchderivativeproducts may not bestatedor implied.

Noneof theinvestigators has any affiliations or financial involvement relatedtothematerialpresentedin this report.

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Tableofcontents Abbreviations......................................................................................................................................................... 5

CHAPTER 1. INTRODUCTION........................................................................................................................... 7

Key questions to be addressed.......................................................................................................................... 8

CHapter 2. methods ............................................................................................................................................. 10

Search strategy .............................................................................................................................................. 10

Classification of LDL Subfraction Methods (Tests) ........................................................................................ 10

Study Selection.............................................................................................................................................. 11

Data Extraction.............................................................................................................................................. 13

Quality Assessment ....................................................................................................................................... 14

Applicability assessment................................................................................................................................ 14

Summary Tables............................................................................................................................................ 15

CHapter 3. Results............................................................................................................................................... 17

Literature Search ........................................................................................................................................... 17

Question 1.................................................................................................................................................... 17

Question 2.................................................................................................................................................... 21

Question 3.................................................................................................................................................... 25

Question 3.1 ........................................................................................................................................... 25

Question 3.2 ........................................................................................................................................... 25

Question 4.................................................................................................................................................... 32

Question 4.1 ........................................................................................................................................... 32

Question 4.2 ........................................................................................................................................... 63

Question 4.3 ........................................................................................................................................... 63

Question 4.4 ........................................................................................................................................... 73

CHapter 4. discussion .......................................................................................................................................... 80 LDL subfractionmethodology ................................................................................................................ 80

AssociationbetweenLDL subfractions and CVD.................................................................................... 81

Limitations ............................................................................................................................................. 83

Future research ....................................................................................................................................... 84

Summary................................................................................................................................................ 86

References ........................................................................................................................................................... 87

AppendixA. Search strategy................................................................................................................................ 94

AppendixB. Rejectedarticles.............................................................................................................................. 95

AppendixC. Potential treatment studies ............................................................................................................ 104

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TablesandFigures

Table 1. Comparisonof different methods for measuringLDL subfractions ......................................................... 23

Table 2. Test Variability (or Imprecision) ........................................................................................................... 30

Table 3a. Characteristics of the nestedcasecontrol studies of incident CVD andNMRmeasuredLDL

subfractions .............................................................................................................................. 36

Table 3b. Nestedcasecontrol studies of incident CVD and NMRmeasuredLDL subfractions ............................ 37

Table 4. Longitudinal study of NMRmeasuredLDL subfractions and progression of CVD ................................. 39

Table 5a. Characteristics of patients in the crosssectional studies of prevalent CVD andNMRmeasuredLDL

subfractions .............................................................................................................................. 40

Table 5b. Crosssectional studies of NMRmeasuredLDL subfractions andprevalent CVD outcomes 41

Table 6a. Characteristics of casecontrol studies of prevalent CVD andLipoPrint GEmeasuredLDL subfractions 42

Table 6b. Casecontrol studies ofLipoPrint GEmeasured LDL subfractions and prevalent CVD .......................... 42

Table 7a. Characteristicsof patientsin the crosssectional studies of prevalent CVD andLipoPrint GEmeasured LDL

subfractions ............................................................................................................................... 43

Table 7b. Crosssectional studies ofLipoPrint GEmeasured LDL subfractions and prevalent CVD ...................... 44

Table 8. Longitudinal study of timeaveraged Berkeley HeartLab GEmeasured LDL subfractions and progression

of CVD..................................................................................................................................... 45

Table 9. Associationbetween LDL Subfraction and incident CVD events (not full extraction).............................. 49

Table 10. Associationbetween LDL Subfraction and progression of coronary artery disease (not full extraction).. 51

Table 11. Associationbetween LDL Subfraction and prevalent coronary artery disease (not full extraction).......... 53

Table 12. Summary: Associationbetween LDL Subfraction andCVD outcomes (not full extraction).................... 57

Table 13. Associationbetween LDL Subfraction and cerebrovascularoutcomes (not full extraction) .................... 59

Table 14. Overall summary of unadjustedanalyses of LDL subfractions and cardiovascular outcomes ................. 60

Table 15. Overall summary of lipidadjustedanalyses of LDL subfractions and cardiovascular outcomes ............ 61

Table 16. Overall summary of studies that reported both unadjustedand lipidadjustedanalyses of LDL subfractions

andcardiovascular outcomes .................................................................................................... 62

Table 17. LipoPrint: Prevalent Disease: Univariable ............................................................................................ 65

Table 18. NMR: Prevalent Disease: Univariable .................................................................................................. 66

Table 19. LipoPrint: Prevalent Disease: Multivariable ......................................................................................... 67

Table 20. NMR: Prevalent Disease: Multivariable ............................................................................................... 68

Table 21. LipoPrint: Incident Disease: Univariable and Multivariable .................................................................. 69

Table 22. NMR: Incident Disease: Univariable ................................................................................................... 70

Table 23. NMR: Incident Disease: Multivariable ................................................................................................. 72

Table 24. Associationbetween baseline LDL subfraction andCVD outcome, stratifiedby treatment vs control ... 77

Table 25. Associationbetween ontreatment LDL subfractionandCVD outcome, stratifiedby treatment vs

control ..................................................................................................................................... 78

Table 26. Associationbetween change in LDL subfraction, on intervention (control), and CVD outcome ............ 79

Figure 1. Analytic frameworkfor association between interventions, LDL subfractions, and CVD events ............ 73

Figure 2. Analyses to demonstrate clinical effect of treatment of abnormal LDL subfractions .............................. 74

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Abbreviations Abbreviation Definition Adj adjustedfor cardiovascularriskfactors, includinglipids and/or triglycerides AHRQ Agency for HealthcareResearch andQualityApoB apoprotein B Assns associations ATPIII Adult Treatment Panel III (3rd reportof theNational Cholesterol Education

Program Expert Panel) AUC areaunderthecurveBMI body mass indexCABG coronary artery bypass graftCAC coronary artery calcificationCAD coronary artery diseaseCC casecontrol studies CDC Centers for DiseaseControl andPreventionCerebroVD cerebrovasculardiseaseCHD coronary heart diseaseCI confidence intervalCITP capillary isotachophoreticmethodCK creatinekinaseCLIA Clinical Laboratory Improvement ActCMS Centers for MedicareandMedicaidServices hsCRP high sensitivity C reactiveproteinCV coefficient of variationCVD cardiovascularheart diseaseDBP diastolicbloodpressureDGUC density gradient ultracentrifugationDM diabetes mellitus ECG electrocardiogramEPC EvidencebasedPractice CenterESRD endstage renal diseaseFH familial (hereditary) hypercholesterolemia(homozygous or heterozygous) FHx family historyFPG fastingplasmaglucoseFram Sc Framingham scoreGE gel electrophoresis HDL high density lipoproteinHDLc HDL cholesterolHPLC high performance gel filtration (liquid) chromatographyHTN hypertensionIMT intimamediathickness Inter intermediateJNC 7 The7th Reportof theJoint National Committee on Prevention, Detection,

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Abbreviation Definition Evaluation, andTreatment of High BloodPressure

LDL lowdensity lipoproteinLDLc LDL cholesterolLDLSF score LDL subfraction scoreLOA BlandandAltman limits of agreementMI myocardial infarctionMLD minimum lumen diameter(coronary arteries) MRI magneticresonanceimagingN samplesize nCC nestedcasecontrol studies nd no dataNMR nuclear magneticresonance No. numberOR odds ratioPbtw Pvaluefor difference between treatment andcontrolPCohort prospectivecohort(crosssectional) studies PLong prospectivelongitudinal studies PTCA percutaneous transluminal coronary angioplastypy packyear r correlation coefficientRCT randomizedcontrolledtrialRef Std reference standardRf ratio of distance movedby bandrelativetomarkerRR relativeriskSBP systolicbloodpressureSD standarddeviationsdLDL small denseLDL TC total cholesterolTg triglycerides TIA transient ischemicattacks UC ultracentrifugationUI MedlineuniqueidentifierUnadj unadjustedfor lipids and/or triglycerides VAP Vertical Auto ProfileWHO WorldHealth OrganizationXS crosssectional

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Chapter1. Introduction Cardiovasculardisease(CVD)is theleadingcause of disability anddeath in theUS.1

Identifyingindividuals at high riskfor CVDandaggressively treatingthem is acriticalcomponent tolower thepopulationwidediseaseburden. TheAdult Treatment Panel III (ATPIII) of theExpert Panel of theNational Cholesterol Education Program has identifiedagroup of riskfactors associatedwith CVD. Riskfactor assessment is usedtoestimateindividual riskandinform decisions on courseof treatmentandtarget goals for theefficacy of treatment once it has been initiated.Cardiovascularriskfactors addressedby ATPIII (in addition toelevatedLDL cholesterol) includecigarettesmoking, hypertension (bloodpressure>140/90mm Hgor onantihypertensivemedication), lowconcentration of high density lipoprotein (HDL) cholesterol (55years men >45years).2 For individuals with two or moreriskfactors, ATPIII recommends estimatinga10year CHDriskscore(FraminghamScore) andmakingtreatmentrecommendations andsettingLDL cholesterol goals on thebasis of this score.3

Recently, questions havebeen raisedas tohowwell thestandardATPIII criteriafor estimatingCVDriskidentifies highriskindividuals andwhetheradditional diagnosticcriteriaareneededto adequately estimateCVDrisk.47 For themost part, this controversy has centeredon theincremental valueof additional riskfactors tothosecurrently used. Someadditionalcandidateriskfactors includehigh sensitivity Creactiveprotein, lipoproteinassociatedphospholipaseA2, Nterminal proatrial natriuretic peptide,aldosterone,renin, fibrinogen, Ddimer, plasminogenactivator inhibitor type1, homocysteine,urinary albumintocreatinineratio, hemoglobin A1c,lipoprotein (a)[Lp(a)], apoprotein (apo) AI, apo B andLDL particlesize.

Ithas been suggestedthatdeterminingLDL particlesize distribution provides additionalpredictivepower toLDL cholesterol measurement alonetoestimatean individuals CVDrisk.2 On thebasis of particledensity, small denseLDL particles arethought toconferahigherlevel of riskthan largerless denseLDL particles.8,9 In vitro, small denseLDL particles aretaken upmoreavidly by macrophages than largerless denseLDL particles.10 This may berelatedto small denseLDL beingmoresusceptibletooxidativemodification or havingagreaterbindingpotential toarterial wall proteoglycans than thelargerless denseLDL particles. Higherplasmaconcentrations of small denseLDL tendto beassociatedwith higherconcentrations of triglycerideandapo B100, andlowerconcentrations of HDL cholesterol andapo AI, each of which has independently been associatedwith increasedCVDrisk.11

TheAmerican Diabetes Association, togetherwith theAmerican College of CardiologyFoundation, convenedapanel of experts to developaconsensus position for patients withcardiometabolicrisk.12 In their opinion, LDL particlenumber, as measuredby nuclear magneticresonance(NMR) may beabetter discriminator of riskthan LDL cholesterol andthatboth LDL particleconcentration andLDL size areimportant predictors of CVDthoughseveral limitations, includingavailability andaccuracy of themethod, werenoted. Despitethis consensus piece,it has yet tobedeterminedwhetherCVDriskassessment andtreatmentdecisions wouldbeimprovedif LDL subfraction measurements wereavailabletoclinicians andwerefactoredintothedecision makingprocess. Furthermore,therearenumerous disparatesystems currently availabletoestimateLDL subfractions, though most arelaborintensiveand/or requirelongassay turnaroundtimes, makingthem impractical for routineuseby clinicallaboratories. WereLDL subfractions associatedwith alteredCVDrisk, it is unclear whetherthe

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http:particles.10

different characteristics of theLDL subfractions assessedby thedifferent methods wouldresultin similarpredictivequalities for estimatingCVDrisk. Itis also unclear whethermeasuringLDL subfractions wouldbeof incremental benefit overmeasurement andtreatment of traditionalcardiovascularriskfactors.

Multipleterms areusedin theliteraturetodescribe LDL subfractions andrelatedfeatures of LDL, includingLDL subclasses, particles, particleconcentration, particlenumbers,andpatterns. Theseterms describeseparate, but sometimes overlappingfeatures of LDL. For simplicity, this report uses what webelieveis themost genericterm, subfractions, except wherespecificmeasurements arebeingdescribed.Weacknowledge that this term does not completelydescribeall measuredfeatures of LDL, bewedeterminedit was areasonablecompromisetoreducetheburden of repeatedly listingterms. LDL subfraction clearly has deficiencies as agenericterm, andour useof theterm is notmeant as arecommendation that this term beadoptedby theresearch community. Wealso donot mean tosuggest thatthat thedisparatemethods for analyzingLDL can befully subsumedin asingleconcept.

In December2006theFood andDrugAdministration (FDA) heldapublichearingonlipoprotein subfractions (www.fda.gov/OHRMS/DOCKETS/ac/06/transcripts/20064263t101t.pdf, accessedFeb 19, 2008). Several questions wereformulatedfrom this meetingregardingtheuse of LDL (andHDL) subfractions for clinical decision making. Basedon this hearing, theCenters for Medicare& MedicaidServices (CMS) requestedareviewof theliteratureon LDL subfractions andtheriskof CVD. Afteran early overviewof thepotentially relevant literaturebytheTufts EvidencebasedPracticeCenter(Tufts EPC), thequestions of interest for this reportwererestrictedtoadescription of themeasurement methods that potentially couldberoutinelyusedby clinical laboratories, comparisons of thedifferent measurement methods, areviewof theevidenceregardingtheassociation between LDL subfractions andCVD, andareviewof studies thatevaluatedan intervention that may improve LDL subfraction profiles andalso evaluatedcardiovascularoutcomes. Theprimary population of interest for this reviewis theoverage 65Medicarepopulation however, data from all adults arealso of interestto CMS.

Key questionstobeaddressed 1. What arethemethods thathave been proposedtobeusedroutinely tomeasureLDL

subfractions? Is thereamethodthat is consideredthereferencestandard?

2. Howdodifferent methods of measuringLDL subfractions comparein terms of testperformance?

3.1 Howmuch variability is therein measures of LDL subfractions from day to day?

3.2 Howmuch variability is therein measures of LDL subfractions within thesameindividual (measuretomeasure)?

4.1 What is therelationshipbetween LDL subfractions andoutcomemeasures relatedtoCVD?

4.2 If thesetests areusedin combination with othercardiovascularriskassessmenttechnologies, what is theincremental increaseof diagnosticperformance?

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www.fda.gov/OHRMS/DOCKETS/ac/06/transcripts/20064263t1

4.3 If thereis arelationshipbetween LDL subfractions andCVD, howstrongis it relativetootherriskfactors?

4.4 What dostudies reportregardingthelinkbetween therapies toalterLDL subfractions andCVDoutcomes?

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Chapter2. Methods This reporton thelowdensity lipoprotein (LDL) subfractions andassociations with CVD

is basedon asystematicreviewof theliterature,selectedreviewarticles, andFoodandDrugAdministration (FDA) documents.

SearchStrategy A comprehensivesearch of thescientificliteraturewas conductedto identify relevant

studies addressingthekey questions. Ourfinal search was conductedon August 22 2007. WesearchedMEDLINE (from 1950to present), CAB Abstracts (1973 to present), theCochraneClinical Trial Registry (3rd quarter 2007), andtheCochrane Databaseof SystematicReviews (3rd quarter 2007) to identify articles relevant toeach key question. In electronicsearches, weusedvarious terms for LDL, particlesize/subfractions, andtestmethodologies, limitedtohumans andEnglish language (see Appendix A for completesearch strategy). Thesameliteraturedatasetwas usedfor all key questions. We didnot systematically search for unpublisheddatawith theexception of FDA documents, as describedbelow.

Classificationof LDL SubfractionMethods(Tests) For thepurposes of our analyses, wedividedtheresearchedmethods into different

categories: NuclearMagneticResonance(NMR). This methoduses NMR techniques tomeasure

amplitudes of spectral signals emittedby lipoprotein subfractions of different sizes. This methodis availablefor clinical useviaasmall numberof medical laboratories.

LipoPrint. This is ameasurement techniqueclinically availablethat uses astandardizedmethodfor usinglinear polyacrylamidegel electrophoresis to separateLDL particles onthebasis of size andtoalesserextent charge. Thekit andinstrument for this methodaremarketedby Quantimetrix.

Berkeley HeartLabgradient gel electrophoresis. This is astandardizedsystem usingaspecificgradient GE to provideLDL subfraction patterns. Thestandardizedversion of this system is performedonly at theBerkeley HeartLab, but is clinically available.

Gel electrophoresis (GE) (Bench). This covers awiderangeof methods usingGE. Thesemethods areeithernotstandardizedor, if standardized, arenotroutinely usedby clinicallaboratories. In general, researchers preparetheir own gels andusetheir own methods for runningtheanalyses. Different compounds areusedto createthegels, thoughpolyacrylamideis most common, anddifferent distributions of gel densities areused. Thesemethods aretimeandresourceintensive.

Ultracentrifugation. This covers awiderangeof methods thatseparatelipoproteinparticles on thebasis of density, eithersequentiallyandcontinuously, prior to lipidor apoprotein analysis. Thesemethods aretimeandresourceintensive.

Othermethods that were consideredincludehigh pressureliquidchromatography(HPLC), capillary isotachophoresis (CITP), Lipophor(anotherGE methoddevelopedby Quantimetrix), andothertechniques. In addition, otherclinically availablemethods for

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measuringLDL subfractions includean ultracentrifugation techniqueperformedat theUniversity of Washingtons Northwest LipidResearch Laboratory andtheVertical AutoProfile. However, as describedin theresults section for Question 4, no studies eligiblefor theclinical associations portions of this reviewusedtheselattertwomethods.

Study Selection Weassessedtitles and/or abstracts of citations identifiedfrom literaturesearches for

inclusion, usingthecriteriadescribedbelow. For studies thatpotentially met thecriteria, thefull textarticles wereretrievedandasecondreviewwas conductedtodetermineinclusion by reapplyingtheeligibility criteria.A lowthresholdwas usedto retrievearticles for full rescreening.

Eligibility criteriafor key question1(routinely usedmeasurement methodsandreferencestandards)

Generalapproach: Discussion regardingmethods (tests) thatareavailablefor routineuseor thatmay beusedas areference standard. Theterm routine was operationalizedto mean that themethodcouldbesuitablefor useby acommercial or institutional clinical laboratory for measuringLDL subfractions, as orderedby clinicians.

Studydesign: Narrativeor systematicreview,editorial or letter with references. Englishlanguage. Publishedsince 2001.

Intervention: Methods (tests) for themeasurement of LDL subfraction distribution.

In addition, toidentify methods submittedtotheFood andDrugAdministration (FDA) for clearance toproceedtomarket, theFDA Clinical Laboratory Improvement Act (CLIA) databasewas searchedfor all listedanalytenames with lipoprotein fractionsandfor nuclear magneticresonance/NMRtest systems or specific manufacturers. All documents andinternetlinks associatedwith theFDA CLIA records were examinedfor therelevanceto themethods of measuringor separatingLDL subfractions.

Eligibility criteriafor key questions2and 3(test performance)

Population:Human serum samples. If information is providedon theindividuals, then they mustbeat least 18years old.

Intervention:Any methodtomeasureLDL subfraction distribution.

Comparators:For question 2, studies must havecomparedmethods from twoor moredifferentcategories of methods (as describedabove). Excludestudies that evaluatedonly incremental or technical changes to themethods. For question 3.1, studies must havedrawn serum samples fromthesamevolunteers on multipledays withinashortperiodof time(wedidnotsetastrict upperlimit on thetimeframe). For question 3.2, studies must havemeasuredthesameserum samples usingthesamemethods atleast twice.

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Outcomes:We allowedany methodof comparingtest accuracy, validity, or consistency, includingsensitivity/specificity, BlandAltman plots, correlation (r), or measures of variability.

Design:Articles must reportoriginal data reviewarticles wereexcluded. Articles must havebeen peer reviewed letters andabstracts were excluded. Thedataset must includeserum samples from at least 10individuals for each method.

Eligibility criteriafor key questions4.14.3(associationwithCVD)

Population:Adult humans (18years old). Excludedhighly atypical populations on acasebycasebasis (eg,astudy of peoplewith hypopituitary growth hormonedeficiency was excluded).

Predictors:LDL subfraction information, includingsize, concentration, or subclass pattern, usingany method(test). Serum (or plasma)samples must bedrawn prior to outcomes (for incidencestudies) or at least 1month afteracardiovascularevent (for prevalence studies) toallowtimefor stabilization of lipoproteins aftertheevent. Studies wereexcludedif they usedameasurement methodthat was determinedto beoutdatedtotheextent that thereis littlecomparability to modern methods. For question 4.2, studies must reporttheincremental changein diagnosticperformance overothercardiovascularriskassessment tools. For question 4.3, studies must reportcompleteresults of multivariableanalyses that includedboth LDL subfractions andothercardiovascularriskfactors (though not exclusively otherlipoproteinsubfractions). For all questions wedidnotevaluatedifferences in constituents of LDL, such as percent total protein, apoB, cholesteryl esters, or triglycerides.

Outcomes:Clinical or selectedsurrogate cardiovascularoutcomes, includingcardiovascularevents, clinical CVDstatus (eg,diagnosis or prevalence of CVD, stage or severity of CVD), intimamediathickness (IMT, Dopplerultrasonography measurement of degreeof arterialatherosclerosis), or electron beam computerizedtomography (EBCT, ameasurement of calciumdeposits in thecoronary vessels).

Design:Prospectiveor retrospective,crosssectional (for prevalence) or longitudinal (for incidence). Singleor parallel cohortstudies, casecontrol or nestedcasecontrol studies. Datasetmust includeat least 10subjects perstudy group. Studies must reportsufficient data or analyses toassess theassociation between LDL subfractions andcardiovascularoutcomes. No minimumduration for longitudinal studies.

Eligibility criteriafor key question4.4(therapy,LDLsubfraction,&CVD)

Population:Adult humans (18years old). Excludedhighly atypical populations on acasebycasebasis.

Interventions: Pharmaceutical or otherintervention hypothesizedtobeneficially affect LDL subfractions.

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Comparators: Otherinterventions that may affect LDL subfractions, or placebo, usual care, or no treatment.

Outcomes:Clinical or selectedsurrogate cardiovascularoutcomes, includingcardiovascularevents, clinical CVDstatus (eg,diagnosis or prevalence of CVD, stage or severity of CVD), IMT (Dopplerultrasonography measurement of degreeof arterial atherosclerosis), or electron beamcomputerizedtomography (EBCT, ameasurement of calcium deposits in thecoronary vessels).

Analyses: At aminimum, thestudies must havereported howthebaselineor ontrial LDL subfractions wereassociatedwith CVDoutcomes, stratifiedby intervention (i.e., theassociations in both theintervention andthecontrol arms), or they must havereported howthechangeinLDL subfractions from baselineto ontrial was associatedwith CVDoutcomes. Studies wereexcluded(for this question) if they reported associations between baselineor ontrial LDL subfractions andCVDoutcomes if they pooledinterventions, even if they adjustedfor intervention in amultivariablemodel.

Design: Randomizedcontrolledtrials (RCTs) or nestedcasecontrol studies within an RCT. Datasetmust includeat least 10subjects perarm (or original arm of theRCT). No minimumduration.

DataExtraction Separatedata extraction forms weredesignedfor questions 2& 3andfor question 4. For

studies that met criteriafor questions 4.14.4, full dataextraction was completedonly for studies thatusedspecificmethods or kits that are currentlyavailablefor clinical useor hadthesamples analyzedby laboratories that also perform LDL subfraction analyses for clinical use(usingthesamemethods that arecurrently usedfor clinical samples). Weusedthebest informationavailabletous from CMS, FDA, domain experts, thereviewedstudies, internet searches, invitedreviewers, andconversations with several laboratories todeterminewhich methods areavailablefor clinical use.Wealso usedthebest availableinformation todeterminewhetherthespecificmethods usedby investigators aresimilarto themethods usedby clinical laboratories however, we didnot contactinvestigators. Becausethemethods usedin otherstudies arenot clinicallyavailablein theUS, datafrom studies that usedtheseothermethods weresummarizedonlybriefly (see belowfor moredetails). For eligiblestudies weextracted data on study year, country, setting, fundingsource, study design, timingof endpoints (if applicable), eligibility criteria,measurement method, comparator (if applicable), definitions of outcomes, subject characteristics (if applicable), andbaseline,final, or correlation results for outcomes of interest (as applicable).

For question 4.14we focusedon twotypes of analyses:adjustedanalyses (multivariableanalyses wheretheassociation between LDL subfraction andCVDoutcomes wereadjustedfor LDL cholesterol, HDL cholesterol, nonHDL cholesterol, and/or triglycerides) andunadjustedanalyses (whethercompletely unadjustedor, if thesedataare not reported, adjustedonly for variables notincludedin theadjustedlist, such as otherlipoprotein subfractions, clinical history, demographics, or bloodpressure).

For questions 4.14.4 studies of othermethods, datawere extracteddirectly intosummary tables.

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Quality Assessment Weassessedthemethodological quality of each fully extractedstudy (andall question

4.4studies) basedon predefinedcriteria.Weuseda3category gradingsystem (A, B, C) todenotethemethodological quality of each study. This gradingsystem has been usedin most of theprevious evidence reports from theTufts EPCas well as in evidencebasedclinical practiceguidelines. This system defines agenericgradingsystem that is applicableto varyingstudydesigns includingrandomizedandnonrandomizedcomparativetrials, cohort, andcasecontrolstudies. Studies werenot rejectedduetopoor quality.

A(good) Goodquality studies arelikely to havetheleast bias andresults areconsideredvalid. They includestudies that adheremost closely to thecommonly heldconcepts of highquality includingthefollowing:aformal randomizedcontrolledstudy clear descriptionof thepopulation, setting, interventions, andcomparison groups appropriatemeasurement of outcomes appropriatestatistical andanalyticmethods andreporting noreportingerrors clear reportingof dropouts andnoobvious bias. For studies evaluatingassociations between LDL subfractions andCVDoutcomes, only thosethatevaluatedincidenceor progression of diseasein longitudinal studies wereeligibleto beagrade Astudy. Theassociation between LDL subfractions andprevalent CVDwas not deemedtobeaclinically high quality analysis.

B (fair) Fair quality studies aresusceptibletosomebias, butnot sufficient toinvalidatetheresults. They do not meet all thecriteriain category A becausethey havesomedeficiencies, but nonelikely tocausemajor bias. Thestudy may bemissinginformation, makingit difficult to assess limitations andpotential problems.

C(poor) Poor quality studies havesubstantial bias that may invalidatetheresults. Thesestudies haveserious problems in design, analysis, or reporting havelargeamounts of missinginformation, largedropoutrates, discrepancies in reporting, lackof proper adjustments for relevant variables, or othermajor sources of bias.

Applicability Assessment Applicability addresses therelevance of agiven study to apopulation of interest. Every

study applies certain eligibility criteriawhen selectingstudy subjects. Most of thesecriteriaareexplicitly stated (eg, diseasestatus, age, comorbidities). Somemay beimplicit or duetounintentional biases, such as thoserelatedto location (eg, multicentervs. singlecenter, intensivecarevs. all inpatients), year of procedure, andotherissues. Theapplicability of astudy is dictatedby thekey questions, thepopulations, andtheinterventions that areof interest tothis review, as opposedto thoseof interestto theoriginal investigators.

Wecategorizedstudies within atargetpopulation into1of 3levels of applicability thataredefinedas follows:

High Sampleis representativeof Medicarepopulation in relevant settings. Patients age (olderadult), gender, spectrum of diseaseseverity andtype, etc. are

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representativeof population of interest. Nosubstantial exclusion criteriathatwouldmake thesampleatypical of Medicarepatients for whom LDL subfraction testingmight beconsidered.

ModerateSampleis an important subgroup of population of interest. Possibly limitedbyanarrowor youngage range,typeof disease,gender, restrictiveeligibilitycriteria, etc.

Low Samplerepresents only anarrow, atypical subgroupof population of interest.

Summary Tables For each question we summarizeddatain summary tables which includedataon study

design characteristics, subject characteristics, test method, numberof subjects (or samples) analyzed, results data, andfor most questions, quality, andapplicability.

Mosttables includedetails of theoutcomedataas reportedby thestudy authors. However, becauseof thelargenumberof studies that usedmethods thatarenotavailablefor clinical useandbecauseof thelimitedapplicability of thesestudies to clinical practice (given thelackof standardization of LDL subfraction measurement or reporting), wereportonly qualitativeresults for each of thesestudies that addressedquestions 4.14.3. Symbols wereusedtodenotestatistically significant positiveor negativeassociations between LDL subfractions andCVDoutcomes, lackof association, or in afewcases what theauthors reportedas substantialassociations but wherestatistical analysis was not reported. SeeTables 9andfollowingfor thesymbols andtheir definitions. Analyses that wereadjustedor unadjustedfor lipoproteins arepresentedin separatecolumns, with differently shadedsymbols. For thesetables, wedistinguishedbetween measurements of size (diameterin angstroms) andmeasurements of pattern.Pattern coveredall thedifferent measurements of specificsubfraction concentrations (or otherlevels), proportions (comparedto overall or othersubfractions), andothermeasurements describingthedistribution of subfractions.

For question 4.1, grandsummary tables (Tables 1416) were also created, presentingclinically availablemethods andothermethods together. Thesedescribethenumberandtypeof studies that foundpositive,negativeor no associations with CVDoutcomes in both unadjustedandadjustedanalyses. Thefinal table(Table16) also summarizes thosestudies that reportedboth unadjustedandadjustedanalyses, to evaluatetheeffect of adjustingfor lipoproteins.

For questions 4.2and4.3, separatesummary tables werecreatedfor incident andprevalent CVD,each clinically availablemethod, andunivariableandmultivariableanalyses. Univariableandmultivariablesets of datathatdo notincludeLDL subfraction arenot included. Each tableincludes thesamelist of potential cardiovascularriskfactors. This list was derivedfrom theevaluatedstudies. Itincludes, in order, theLDL subfraction measures, thelipoproteincholesterol andtriglycerideconcentrations, theriskfactors usedby ATPIII2 andJNC 7,13 andotherpotential riskfactors. Theotherlipoprotein subfractions areomittedfrom analysis. Theprimary purposeof theevaluation of themultivariableanalyses for this report is todeterminewhetherany measures of LDL subfractions arepredictors of outcomes independent of otherknown or commonly measuredpredictors of or riskfactors for CVDusedin clinical practice. Theapproach used,andthis report in general, is notmeant toevaluateetiology of any

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associations. Thetables aredesignedtodescribetherelativestrengths of theassociations between theriskfactors andtheCVDoutcomes, notto describeeach model createdbyindividual studies or thevalue,perse,of each riskfactor. Therefore, tomaintain simplicity andreadability, themeasurement units for each riskfactor arenotincludedin thetables (except for percent of subjects. Othertables providethemoredetaileddatafor theLDL subfractions. Theoriginal papers shouldbereadfor otherdetaileddata. Unadjustedriskfactors wererankedbasedon thestatistical significance of their association with theoutcome. From adjusted, multivariablemodels, theriskfactors with thestrongest associations with theCVDoutcomes (eg, largest OR) aretabulated.

For question 4.4, tables werecreatedbasedon thedifferent potential analyses describedunder Eligibilitycriteriakeyquestion4.4, above. Separatetables werecreatedfor dataon theassociation between changes in LDL subfraction andCVDoutcomes, between baselineLDL subfraction andoutcomes stratifiedby intervention, andbetween ontrial LDL subfraction andoutcomes stratifiedby intervention. Results aregiven for analyses both unadjustedandadjustedfor lipoprotein concentrations.

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Chapter3. Results

LiteratureSearch Theliteraturesearch yielded6373uniquecitations from Medline(n=5996), CAB

Abstracts (n=326), theCochraneclinical trial registry (n=47), andtheCochranedatabaseof systematicreviews (n=4). Of these,457full text articles wereretrieved. As describedfurtherbelow, 9articles providedinformation for Question 1, 9studies wereeligiblefor Question 2, 5studies wereeligiblefor Question 3(two of which werealso eligiblefor Question 2), and65studies wereeligiblefor Question 4(oneof which was also eligiblefor Question 2).

Amongthe374rejectedarticles, 270evaluatedpossibletreatments for abnormal LDL subfractions but didnot evaluateCVDoutcomes (see Appendix C). Amongtheremainingrejectedarticles 54hadno relevant information, 12didnotevaluateLDL subfractions, 9didnotevaluateaclinical CVDoutcome(for Question 4), 7wereduplicatepublications, and22wererejectedfor otherreasons (see Appendix B).

Question 1

Whatarethemethodsthathavebeenproposedto beusedroutinelytomeasureLDLsubfractions?Isthereamethodthatisconsidered thereferencestandard?

Amongthestudies evaluatedbelowfor Question 4, four general methods for separatingandmeasuringLDL subfractions wereidentified:gel electrophoresis (GE), nuclear magneticresonance(NMR), ultracentrifugation, andhigh pressureliquidchromatography (HPLC). Themost common methods reported for measuringLDL subfractions involveeitherGE or ultracentrifugation methods.

Gel electrophoresis Thelargemajority of studies thathaveimplementedGE usedspecificmethods thatwere

particulartotheresearch laboratories. Theresearcherscreatedtheir own gels andusedtechniques that may havebeen basedon previous researchers work, butwerenotstandardized. They also tendedtousedefinitions of LDL subfractions that wereuniqueto their laboratories or wereotherwisenot standardized. LDL subfractions quantifiedby GE arefrequently classifiedinto eitherpattern A, pattern B, or an intermediatepattern. Investigators may also usedifferentalgorithms for theclassifications of LDL patterns. GE can also determinetheLDL subfractionsizes by comparisons with calibrators that included particles and/or LDL lyophilizedstandardswith known sizes. A drawbackof thesemethods is thelengthy labor intensivenatureof theexperimental procedures someof which requiremore than aday for sampleanalysis. Thereis also apractical restriction to thenumberof samples thatcan beanalyzedat any onetime, whichmay limitapplications of thesemethods for routine clinical use.14 Anotherlimitation of theseGE methods was duetolimits in thickness of thegradient gels as relatedto ensuringreproducibilityof thegradient gels, which in turn may affect comparability of LDL particleseparation from

17

laboratory tolaboratory. Moreover, thevisualization of theprotein bands requires theremoval of thegel from its casing, incubation with astainingsolution followedby destainingandscanning, again, alabor intensiveprocess that can introduce variability.

LipoPrint (Quantimetrix Corp.) is aGE system that is availableto clinical laboratories for testingof LDL subfractions in patients. Thesystem includes specificequipment andreagents andastandardmethodfor definingLDL subfractions. Ituses aloadinggel that is polymerizedwith fluorescent light. This methodpermits separation of LDL intoseven subfractions within 60minutes. Multiplesamples can berun simultaneously. Becausethegels arepreparedby thecompany, it is technically simpler, less expensive,andmoreconducivetoroutinelaboratorytestingthan traditional GE.15 LDL particles areseparatedby size andtoalesserextent charge, andmigration distance is quantifiedby densitometricscanning. Accordingto LipoPrintproductinsert describingthemanufacturers instruction for theanalyticprocedureandproducingquantitativeresults (http://www.4qc.com/products/lipoprint/index.html), atypical Lipoprintprofileconsists of 1VLDL band, 3midbands (comprisingprimarily IDL), upto 7 LDL bands, and1HDL band. Aftertheelectrophoresis is completed, thevarious stainedlipoprotein fractions (bands) present in thesampleareidentifiedby their mobility (Rf) usingVLDL as thestartingreference point (VLDL=0)andHDL as theleading reference point (HDL=1). Therelativeareafor each lipoprotein bandis determinedandmultipliedby thetotal cholesterol concentration of thesampletoyieldtheamount of cholesterol for each bandin mg/dL. Thelipoproteinsubfraction profiles can also beclassifiedinto TypeA (normal) andTypeB (abnormal) basedontheaverageparticlesizeof theLDL particles describedin apaper by Austin andassociates.16 Useof theLipoprint todetermineparticlesizes or LDL scores or any otherform of classification is notrecommendedby themanufacturerof thekit. However, as will benotedbelow, research laboratories usingLipoprint frequently havenot usedtherecommendedLDL subfraction definitions.

Berkeley HeartLabuses LDL Segmented GradientGel Electrophoresis (LDLS3GGETM).17 This techniqueseparates LDL particles into7LDL subfractions (LDL I, IIa,IIb, IIIa, IIIb, IVa, andIVb) basedon particlesize andshape. LDLS3GGETM gel kitprovides amethod(acomputeralgorithm) for calculatingthenumberof particles in an LDL subfraction.18 TheLDL particlenumberis determinedby assumingaphysiological 1:1ratio between apo B andLDL particles. In publishedliterature, investigators usetheS3GGETM gel kitfor classifyingLDL subfractions as pattern A, AB, or B basedon LDL size cutoffs.17

Ultracentrifugation SimilartoGE, thestudies that haveimplementedultracentrifugation usedavariety of

instruments, specificmethods, anddefinitions of LDL subfractions in their laboratories. Ultracentrifugation is likewiselabor intensive,particularly sequential flotation, which mayrequiremorethan aday for sampleanalysis. An arbitrary selection of density ranges is oftenused. LDL subfractions quantifiedby ultracentrifugation arefrequently classifiedintoeitherpattern A, pattern B, or an intermediatepattern. Investigators also useddifferent algorithms for theclassifications of LDL subfractions.

As best we coulddetermine,theUniversity of Washingtons Northwest LipidResearchLab (http://depts.washington.edu/nwlrl/) uses an ultracentrifugation methodandis availabletorun clinical samples.

18

http://depts.washington.edu/nwlrl/http:cutoffs.17http:subfraction.18http:associates.16http://www.4qc.com/products/lipoprint/index.html

Nuclear magneticresonance TheNMR methodmeasures thesignal from theaggregatenumberof terminal methyl

groups in thelipidwithin theparticle.Thenumberof methyl groups is reflectedin theamplitudeof themethyl NMR signal. Theamplitudeof each lipoprotein particlesignal serves as ameasureof theconcentration of that lipoprotein. Usingstandardassumptions concerninglipoproteindiameterandlipidcontent, theNMR datacan betransformed(through calculations) intosubfraction concentrations. Otherquantitativesubfraction information, such as LDL size andpatterns, can alsobederivedthrough additional calculations.19 NMR is availabletopatients andclinicians by sendingsamples to a small numberof clinical laboratories that havetheequipment.

Theconcept of usingproton NMR spectroscopy tomeasureplasmalipoprotein particleconcentrations was introducedin theearly 1990s andwas commercializedfor clinical research in1997.19 NMR can quantify thenumbers of lipoprotein subclass particles basedon twophenomena. First VLDL, LDL, andHDL subclasses of different sizes in plasmasimultaneouslyemit distinctiveNMR signals whoseindividual amplitudes can beaccurately andreproduciblymeasured. Second, themeasuredsubclass signal amplitudes aredirectly proportional tothenumbers of subclass particles emittingthesignal, irrespectiveof variation in particlelipidcomposition. Therefore,NMR spectroscopy can providesimultaneous measurements of LDL particlenumberandsize (through calculations), as well as measurement of high density andverylowdensity lipoprotein (HDL andVLDL) subfractions. Thereare, however, several assumptions for NMR measurements of lipoprotein subfractions. TheNMR methodis calibratedby its libraryof over30signal envelopes from sizecharacterizedpurifiedfractions. Itis assumedthat everysampleanalyzedandtheNMR spectradeconvolutedby theNMR methodsoftwarehas components encompassedclosely enough by this calibration library, andall NMR spectralcomponents of agiven sampleareuniquetolipoproteins (ie, no spectral interferences). Therearemany layers of assumptions withintheNMR software, which is proprietary. Someof theunknown assumptions, calibration andvalidation issues havebeen addressed19 but someremaintobefully evaluated.

High performanceliquidchromatography(HPLC) Theoriginal HPLC methodfor measuringLDL sizemonitors thecolumn effluent at280

nm of theisolatedLDL subfraction by ultracentrifugation. Theretention timeof theLDL peakis then usedtocalculatetheLDL diameter.20 A drawbackof this methodis thenecessity of LDL isolation by ultracentrifugation prior to chromatography. A modifiedHPLC methodthat is basedon selectivedetection of lipoproteins by postcolumn labelingwith parinaricacid(afluorescentlipidprobe)permits direct measurement of LDL sizein wholeplasmaor serum.21 Notably, though, despiteapositivereportof themethods comparability toGE, as describedbelow, themethodhas only rarely been usedoverthepast decade by researchersof LDL subfractions andCVDrisk.

Methodssubmittedto the Food& DrugAdministration(FDA) TheCLIA databasecontains themarketedin vitro test systems categorizedby theFDA

since January 31, 2000andtests categorizedby the Centersfor DiseaseControl andPrevention(CDC) prior to thatdate. A search on theCLIA databasefor all listedanalytenames withlipoprotein fractionsreturnedatotal 31records meetingthis search criterion. All documents andinternet links associatedwith these31records wereexaminedfor therelevance tothemethods of measuringor separatingLDL subfractions. Seven devices wereidentified:HelenaLaboratories REPHDL/LDL30Electrophoresis System, HelenaLaboratories REPUltraHDL,

19

http:serum.21http:diameter.20http:calculations.19

VLDL/LDL Cholesterol System, Isolab LDLDirect, Isolab LDLDirect Plus, LipoPrint, LFSLipogel System(Zaxis, Inc.), andHydragel K20System with HYDRASYS(Sebia, Inc). Thesedevices arealso categorizedunderthedeviceclassification nameof electrophoreticseparation, lipoproteins.Thefirst four devices (by HelenaLaboratories andIsolab) didnothaveany otherassociateddocuments postedon theCLIA databaseexcept for thestandardreportfromthedatabasesearch. Therearesummaries/statements of the510(k) notification in concordance of theSafeMedical Devices Act (SMDA) postedfor thelatterthree devices (LipoPrint, LFSLipogel System, andHydragel K20System).

From evaluation of thesummaries/statements of the510(k) notification, weconcludedthat, all of thesedevices that havebeen usedto measureLDL subfractions or sizes in theliteraturewereclearedby FDA for theuse of separatingor measuringLDL fraction (ie, separatingLDL cholesterol from othercholesterolcontaininglipoprotein particles), not for theuseof measuringLDL subfractions or sizes. Accordingto thesummary/statement of the510(k) notification, Quantimetrix LipoPrintSystem classifies LDL subfractions as MidC, MidB, MidA, andLDL1through 7. Thesum of all subfractions constitutes total LDL cholesterol. Theintendeduseof Quantimetrix LipoPrintSystem declaredin thesummary/statement of the510(k) notification of FDA was tomeasurelipoprotein cholesterol (for lipoprotein fractions andsubfractions from VLDL to HDL) in fastingserumor plasmawith atotal cholesterolconcentration 100mg/dL.Theperformance characteristics comparingQuantimetrixLipoPrintSystem to direct HDL or LDL cholesterol methods werealso provided. Thesedataconfirmedthat theLipoPrintLDL Test System performs comparably to thedirect HDL or LDL cholesterol methods in aclinical setting. Thedevicewas thereforefoundtobesubstantiallyequivalent tolegally marketeddevices by FDA, andwas permittedtoproceedtothemarket.

Thesearch of theFDA CLIA databasefor nuclear magneticresonance/NMRtestsystems or LipoScience/LipoMedmanufacturerresultedin no records found. Accordingto theinformation providedby LipoScience, Inc., all tests areperformedusingFDA clearedreagents andmethods. ThecurrentFDA clearedLDL cholesterol measurement system of NMR LipoProfile is Beckman Synchron CX4system (reagents andmethods) measuringLDL cholesterol in human serum or plasma.A search of theFDA CLIA databasefor BeckmanSynchron CX4resultedin eight records with effectivedates from 1995to2000.

Wedidnot identify any federal documents by FDA or othergovernment agencies thatdiscuss possiblereference standards for measuring LDL subfractions.

Narrativereviews Toprovidegreater insight intowhat methods may beusedroutinely tomeasureLDL

subfractions andwhetherany methodis consideredareference standard, wesystematicallysearchedfor review articles andeditorials that discussedpotential routineuseof any methodor suggestedareference standard. An important caveat is that someof thosereviews werewrittenby authors who were actively involvedin bench research of LDL subfractions andhadeitheraprofessional or financial stake in theuse of agivenmethodology.

Ultracentrifugation has been describedas theoriginal goldstandardtowhichsubsequent methods havebeen calibratedandvalidated.11 James Otvos andElias Jeyarajah, whowith others developedNMR analysis of LDL subfractions, also describedthat theNMR measures werecalibratedagainst ultracentrifugationderivedreference dataon isolatedlipidsubfractions.22 However, ultracentrifugation is timeconsumingandavailableonly at someresearch laboratories.11

20

http:laboratories.11http:subfractions.22http:validated.11

As describedby several reviewarticles, andalso as evidencedby thestudies eligiblefor Question 4below, GE is themost commonly usedprocedure in research laboratories.23,24 Researchers usemany different specificmeasurements or methods of analyzingthedata fromGE however, amongthemoreconsistent measurements is theassignment of phenotypes intolargermorebuoyant LDL phenotypeA andsmaller denseLDL phenotypeB (andA/Bor intermediatephenotypes). However, as wealso foundin our reviewfor Question 4, thereis notcompleteconsistency inthedefinition of theparticlediameterthresholdto distinguishphenotypes A andB, or howtoanalyzethosewith intermediatephenotypes. Quantimetrix has commercializedtheLipoPrintGE methodfor LDL subfractionation. Howeveras wedescribebelow(Questions 2and4) andas commentators havenoted,25 theredoes not appeartobeharmonization by researchers of themeasurements derivedfrom thetestor clearvalidation of themethodagainst othermethods.

NMR measurement of LDL subfractions has been commercializedandhas beendescribedas themostrapidandconvenient methodfor determiningLDL size andsubfractionconcentration, though questions remain about its calibration andvalidation.11 Despiteits commercial availability, it has been describedas notbeingapopularmeasurement methodduetotherequirement for expensivespecializedlaboratory equipment which is too difficult to useindaily clinical practice.23 Nevertheless, an advantage ascribedtoNMR (by DrsJeyarajah andOtvos) is that it has theuniqueability toquantify lipoprotein particlenumbers, even in thefaceof significant variation in thecholesterol composition of subfraction particles amongindividuals.19

Summary Thereis currently no generally acceptedreference standardfor measuringLDL

subfractions. Themost common methods for measuringLDL subfractions involveeitherGE or ultracentrifugation methods. Howeverthelengthy experimental procedures andheterogeneity inthealgorithms toclassify LDL patterns or sizes limit their application for routineclinicalpractice. Furthermore,all current gel electrophoresis devices in theFDA databasehavebeenusedto measureLDL subfractions or sizes in theliteraturewerebasedon substantial equivalencetolegally marketeddevices for measuringLDL cholesterol, not LDL subfractions. LipoPrint is theonly FDAcleareddevices that declaredits intent to measureLDL subfractions as theprimaryuse. NMR measurement of LDL subfractions has been commercializedandhas been describedas themostrapidandconvenient methodfor determiningLDL sizeandsubfractionconcentration, though questions remain about its calibration andvalidation. HPLC has rarelybeen reportedin research studies overthepast decade.

Question 2

HowdodifferentmethodsofmeasuringLDL subfractionscomparein termsof test performance?

In this section, we review primary studies that compareddifferentmethods of measuringLDL subfractions. Themethods examinedincludeNMR, LipoPrintGE, otherGE methods (bench methods), ultracentrifugation, andothers. Studies hadto useadult serum samples from atleast 10individuals for each method. Weexcluded studies that evaluatedonly incremental or

21

http:validation.11

technical changes to themethods (eg,comparison of LDL particlesize determination by GE usingtwodifferent approaches comparison of LDL particlesize by HPLC with ultraviolet lightdetection toamodifiedmethodbasedon selectivedetection of lipoproteins by postcolumnlabelingwith afluorescent lipidprobe).

Weallowedany methodof comparingtestperformance, includingsensitivity/specificity, BlandAltman plot (or bias andlimit of agreement), correlation (r), or measures of concordance or agreement between tests. Wereviewedall statistical approaches acknowledgingthat differentmethods of comparingtestperformance makedifferent statistical assumptions andhavedifferentinterpretations of theresults:

Sensitivity andspecificity measuretheclinical diagnostictest performance. Their calculations requireagoldor reference standardthatis presumedtohave nomeasurement errors. Sensitivity is theproportion of peoplewith thedisease(or apositivereference standard) who areidentifiedby thetest. Specificity is theproportion of peoplewith anegativereference standardwho also havea negativetestresult.

Correlation coefficient (r) measures thecorrelationof onediagnostictestto another, butdoes not provideany information abouttheclinicalutility of thetest. Correlation coefficientis inadequatefor comparinganewmethodof measuringLDL subfractions with anestablishedonefor several reasons:First, r measures thestrength of arelation between twovariables, not theagreement between them. Twovariables arein perfect agreement notonlyif thepoints from thescatterplot liealongthelineof equality (thediagonal lineof ascatterplot), but also if thepoints liealongany straight line. Second, r depends on therangeof values in thesample.If therangeis wide,thecorrelation is likely to begreater than if it is narrow. Third, correlation ignores bias (or thesystematicdifference between methods) anditmeasures relativeratherthan absoluteagreement.26 Thus, interpretations of test accuracyusingcorrelation coefficients may bemisleading. A high correlation does not necessarilyimply that thereis good agreement between thetwomethods.

BlandAltman bias andlimits of agreement measuretheabsoluteagreement between twotests, assumingtherearemeasurement errors in both tests (ie, neithertest is agoldstandard).26 BlandAltman bias andlimits of agreement donot provideany informationabout theclinical utility of thediagnostictest. A BlandAltman plotplots themean of theresults from thecomparedtests (xaxis) against thedifference between thetwo tests (yaxis). Theaccuracy is assessedby evaluatinghowclosethedatapoints aretozero on theyaxis (difference between tests thelimits of agreement) andwhetherthereis atrendas thevalueon thexaxis (mean value)increases (or bias). Zerobias andnarrowlimits of agreementindicateagoodagreement between thetwo methods. In addition, ideal tests wouldhaveconsistent limits of agreement across widerangeof testingpopulations.

Kappa is ameasureof agreement between two tests takinginto account agreementthatcouldoccur by chance. Kappa does not provideany information about theclinical utility of thediagnostictest. A kappa valueof oneindicates thetwotests haveperfect agreement, andakappavalueof zero indicates thetwotests haveno agreement.

Ninearticles provideddataon thecomparison of different methods.15,17,20,2731 Four articles reportedfivecomparisons of NMR andGE, three articles comparedLipoPrintandotherGE, four articles reported fivecomparisons of ultracentrifugation andGE, andonearticlecomparedHPLC andGE (Table1). Only onestudy (Witte2004) usedarandom sampleof the

22

http:standard).26http:agreement.26

study populations andblindingof theinvestigators for thealternatetestresults.31 Therefore, this was theonly goodquality study. All otherstudies usedconvenience samples half reportedthatthetestresults wereassessedin blindedfashion in relation to alternatetestresults. Seven studies wereof fair quality. Theonepoor quality study gavean inadequatedescription of thetests compared.28

Nuclear magneticresonance (NMR) vs. gel electrophoresis (GE) Four articles reportedfivecomparisons of NMR andGE involving436subjects (Table1,

NMR vs. GE).17,27,30,31 Witte2004 randomly selectedpatients with type1diabetes andpeoplewithoutdiabetes from thegeneral population. Ensign 2006andBlake 2002enrolledaconvenience sampleof healthy people.Hoefner2001didnotdescribehowthestudy populationwas selected.Thelipidprofiles of all 436subjects across studies wereheterogeneous.

Although therewas agood correlation between NMRassessedandGEassessedLDL particlesizes in 21apparently healthy men (r=0.89, P0.40, intermediateLDL:Rf=0.380.40, largeLDL:Rf

Intermediateor pattern AB:5.58.5 atherogenicor pattern B:>8.5) Theconcordance rates between LipoPrintassessedandGEassessedLDL patterns variedaccordingtotheLDL phenotypes.

Hirany 2003reportedagood agreement between LipoPrintandan alternateGE methodafterevaluatingthedatausingkappa statistics (weightedkappa =0.78 95% CI, 0.680.87). LipoPrinthadan agreement of 92percent concordancefor classification of thesmall LDL subfraction comparedwith GE. For largeLDL subfraction, LipoPrinthadan agreement of 77percent concordance comparedwith GE.

Hoefner2001reported84, 64, and24percent agreement for classification of thesmall, intermediate,andlargeLDL subfraction, respectively, for LipoPrintandGE. Ensign 2006showedonly 40percent agreement in theclassification of LDL patterns between LipoPrintandGE.

Ultracentrifugation vs. GE Four articles reportedfivecomparisons of ultracentrifugation andGE methods involving

atotal of 152subjects (Table1, Ultracentrifugation vs. GE).17,28,29,32 Dormans 2001, Ensign2006, andDavies 2003enrolledaconvenience sampleof healthy people. ONeal 1998enrolledaconvenience sampleof patients with type2diabetes (26percent) or from thegeneral population. Thelipidprofiles of these152subjects across studies variedgreatly although thedatawereincompletely reportedin most studies.

Therewas no uniform ultracentrifugation or GE methodology across studies. Therefore, theresults from thesefivecomparisons areevaluatedindividually.

Dormans 2001showedthat migration distanceof thepredominant LDL subfraction fromGE correlatedstrongly with thedensity of thepredominant LDL bandfrom ultracentrifugation(r=0.85, P1.028kg/L) was shown togive100percent specificity andsensitivity in differentiatingapredominance of small denseLDL III (pattern B). This was reportedtobemarginally betteras apredictor of small denseLDL III than thecutoff density of 1.028kg/L alone(94percent sensitivity92percent specificity).

High performancegel filtrationchromatography(HPLC)vs. GE OnearticlecomparedHPLC with GE involved60patients with type2diabetes (Table1,

HPLC vs. GE).20 Thetotal cholesterol andtriglycerideconcentrations rangedfrom 135to315mg/dL and45to509mg/dL, respectively.

LDL size as measuredby HPLC andGE was highly correlated(r=0.88, P

HPLC andon GE was 2.5 (with HPLC beinglarger). The95percent limits of agreement were6and+10, indicatingthat 95 percent of thedifferences between thetwomethods can beexpected to fall within this range.

Summary A widerangeof agreement (describedas fair to good agreement) was reported for the

comparison of NMRassessedwith GEassessedLDL patterns andfor Lipoprintassessedversus otherGEassessedLDL patterns. Thedifferences between themethods, though, variedacross different prespecifiedpopulations. Onestudy foundthat NMR measurements of LDL sizeareon averageabout54 smallerthan measurements basedon GE, with widelimits of agreement, implyingthat size measurements madewith thedifferent methods arenotinterchangeable.Themeasuredsize difference was larger for patients with type1diabetes, women, andthosewith lowertriglycerideconcentrations, suggestinginconsistent limits of agreements between NMR andGE across testingpopulations. Thestudies comparingultracentrifugation andGE methods useddifferent techniques andmeasurements thereforetheagreements between ultracentrifugation andGE methods for assessingLDL patterns areeachuniqueto theindividual study. Onestudy comparedHPLC andGE it foundgood agreementbetween HPLCassessedandGEassessedLDL sizes but, on average,HPLC measurement ofLDL sizes are2.5 largerthan measurements basedon GE, implyingthat size measurements made with thedifferent methods arenotinterchangeable.

Question 3

Question3.1 Howmuch variability is thereinmeasuresof LDLsubfractionsfrom day to day?

Toanswer this question, studies must havedrawn serum samples from thesamevolunteers on multipledays withinashort periodof time(wedidnot set a strict upperlimit onthetimeframe). No study addressedthis question.

Question3.2 Howmuch variability is thereinmeasuresof LDLsubfractionswithin thesameindividual(measuretomeasure)?

For Question 3.2, studies must havemeasuredthesameserum samples usingthesamemethodatleast twice. Fivestudies reported dataon theintraassay variability (or thereproducibility) and/or theinterassay variability (or theimprecision of testby analyzingstoredsamples on different days) usingrepeatedmeasures by thesametest(Table2).1921,30,33 Nostudydescribedhowthesubsamplewas selectedfrom thestudy population andnonewas primarilydesignedto address this question.

Hoefner2001took two plasmasamples from thestudy population andmeasuredtheir LDL subfraction scores usingLipoPrintGE. Theintraassay coefficients of variations for patientsamples analyzed10times in duplicatewere4.6and4.3percent at LDL subfraction scores of 3.4and13.3, respectively. Interassay precision was determinedusingplasmafrom 19subjects with

25

LDL scores rangingfrom 2.9to16.5 assayedon 3days overa1weekperiod. Themeaninterassay coefficient of variation (CV)was 13percent, although howthebloodsamples werestoredduringthe1weekperiodwas not reported.

Scheffer1997tooka subset of thestudy population andmeasuredtheir LDL size usingGE andHPLC methods. Betweenrun reproducibility for particlediameterwas determinedbyrepeatedly analyzingan isolatedLDL samplestoredin aliquots at70 C. GE andHPLC reproducibility, expressedas coefficients of variation (CV)determinedoveran 8weekperiod, were0.6percent (n=14)and0.2percent(n=12), respectively. Withinrun reproducibility for LDL size measurements was assessedonly for theHPLC method. For thesampleof 10patients with type2diabetes, theCVfor twodifferent LDL samples was less than 0.1percent. In asubsequent study, Schefferet al. modifiedtheHPLC methodandcomparedthetestperformanceof themodifiedmethodto theoriginal HPLC method for measuringLDL sizes. UsingisolatedLDL andwholeplasmasamples from 10subjects, Scheffer1998reported that thewithinrun CVof themodifiedHPLC methodwere0.14 and0.22percent, respectively. UsingisolatedLDL samples stored in aliquots at86 C they reportedthatbetweenrun CVs calculatedfrommeasurements performedon different days was 0.21percent.

Adler2000comparedLDL particlesize determination by GE with two additionalmethods for LDL fractionation:ultracentrifugationusingadensity rangeof 1.019and1.063g/mL, andprecipitation of apo Bcontaininglipoproteins from plasma. This study was gradedpoor quality dueto inadequatereportingof thestudy population andstatistical analyses for thetest variability. Peakparticlediameterwas reproduciblewith aCVof 1.2percentfor LDL samples separatedby ultracentrifugation and1.4percent for LDL samples separatedby apo B precipitation in six separategels. Itwas also reportedthattheintraassay variation (within asinglegel) was 0.2percent,although it was unclearhowmany samples andwhich separationmethodwereusedfor this calculation.

In areview articleby Jeyarajah 2006,19 dataon theintraassay andinterassay precision of NMR lipoprotein measurements werereported. This study was gradedpoor quality duetoinadequatereportingof thestudy population andmethods for samplehandling(although theauthors statedthatall procedures werefollowingstandardprotocol). Twoplasmapools wereused, onewith nominally high triglycerides andlowHDLandtheotherwith lowtriglycerides andhigh HDL.For theplasmapool with high triglycerides andlowHDL, theintraassay andtheinterassay precision for total LDL particleconcentration were2.4percentCVand2.1percentCV, respectively. For thesameplasmapool, theintraassay andtheinterassay precision for LDL size were0.4percentCVand0.5percent CV, respectively. For theotherplasmapool withlowtriglycerides andhigh HDL,theintraassay andtheinterassay precision for total LDL particleconcentration were4.0percent CVand4.3 percentCV, respectively. For thesameplasmapool, theintraassay andtheinterassay precision for LDL size were0.5percent CVand0.6percentCV, respectively.

Summary Thetestvariability is substantially greaterwhen analyzingLDL patterns (ie, pattern A,

intermediate,orpattern B) than when analyzingLDL sizes. Theintraassay variability was relatively small (rangingfrom

Table 1. Comparisonof different methods formeasuringLDLsubfractions Author, YearCountryUI

N Mean (range), mg/dL

Population Tests Concordance or Agreement

QualityLDLc TC Tg Test1(Metric) Test2orRefStd(Metric)

r(P Value)

LOA(95%CI) orOther Results

NMR vs. GE

Witte, 200431Netherlands14993238

324 nd nd 545

Case: diabetes(type 1)

Control: general

NMR (size, nm)

GE (size, nm) nd

All (n=324): 5.38(6.79, 3.97)

Type 1DM (n=152): 5.49(7.31, 3.68)

NoDM (n=172): 5.27(6.96, 3.60)

Men(n=156): 5.20(6.86, 3.53)

Women(n=168): 5.55(7.41, 3.68)

Tg118(n=107): 4.99(6.61, 3.37)

A

Hoefner, 200130US 11159775

51 120 213 217 nd

NMR (patternA, intermediate,

pattern B basedonabsolute sizecutoffs) A

LipoPrint(patternA, intermediate,

pattern B basedonLDLSF score) B

0.67(

Table 1. Continued

Author, YearCountryUI

N Mean (range), mg/dL

Population Tests Concordance or Agreement

QualityLDLc TC Tg Test1(Metric) Test2orRef

Std(Metric)

r(P Value)

LOA(95%CI) orOther Results

LipoPrint vs. other GE

Hirany, 200315US 12669713

102 125 (42452)

219 (113563)

270 (61617)

nd

LipoPrint GE (small,

intermediate large basedon Rf cutoff values) E

GE (small,

intermediate large basedonabsolute sizecutoffs) F

Weightedkappa= 0.78(0.680.87) Concordance:

Small=92%Intermediate=33%

Large=77%

B

Hoefner, 200130US 11159775

51 120 213 217 nd

LipoPrint GE (patternA, intermediate,

pattern B basedonLDLSFscore) B

GEZaxis(patternA & B per BerkleyHeartLab

cutpoints)

Concordance: Pattern A=88%

Intermediate=64%Pattern B=24%

B

Ensign, 200617US 16740651

35 (58820) nd(37479) General

LipoPrint GE (patternA, AB, or

B) D

GE (patternA, AB, or

B) CAgreement = 40%(14/35) B

Ultracentrifugation vs. GE Dormans, 200129Netherlands2049850

41 nd 213 143 General DGUC

(LDL1, LDL2orLDL3, g/mL)

GE (migration

distance, mm)

0.85(1.028 kg/L)

Sensitivity =94%Specificity =92%

continued

28

C

Table 1. Continued Author, YearCountryUI

N Mean (range), mg/dL

Population Tests Concordance or Agreement

QualityLDLc TC Tg Test1(Metric)

Test2orRef Std(Metric)

r(P Value)

LOA(95%CI) orOther Results

HPLC vs. GE Scheffer, 199720Netherlands9342011

60 nd 231 (135315) 209 (45509) Diabetes(type 2)HPLC

(size, nm) GE

(size, nm) 0.88 (0.40, Intermediate LDL: Rf=0.380.40, Large LDL: Rf

Table 2. Test Variability (or Imprecision)

Author, YearCountryUI

N Population TestsN repeated

measurements perpatient (N selected

samples)

TestVariability

Quality How much variability isthere inmeasures ofLDLsubfractions from

day today?

How much variability is thereinmeasures of LDL

subfractions within thesameindividual (measureto

measure)?

Hoefner, 200130US 11159775

51 nd

LipoPrint(patternA, intermediate,

pattern B basedonLDLSFscore) B

nd(19)A MeanCV =13%

B 10C(2)

Intraassay CVsof 4.6% and 4.3%at LDLSFscoresof 3.4

and 13.3, respectively

Scheffer, 199720Netherlands9342011

60 Diabetes(type2)

GE n/a(14)D ndBetweenrunCV (or

reproducibility), over an 8weekperiod= 0.6%

B HPLC

(size, nm)

n/a(12)D

nd

BetweenrunCV (or reproducibility), over an 8week

period= 0.2%2

(10) Withinrun CV

Table 2. Continued

Author, YearCountryUI

N Population TestsN repeated

measurements perpatient (N selected

samples)

TestVariability

Quality How much variabilityisthereinmeasures of LDLsubfractions from

day today?

How much variability isthere inmeasures of LDLsubfractions within the

same individual (measuretomeasure)?

PlasmapoolNMR aliquotedandfrozensamples(LDL nd

Plasma pool A total LDLparticles(nmol/L):

IntraassayCV =2.4%InterassayCV =2.1%

C

Jeyarajah, 200619US 17110242

nd

A:high TgandlowHDLPlasmapoolB: low Tg and highHDL(pool B)

concentrations, nmol/L)

Interassayprecision: 20consecutive days across

6different NMR analyzers

Intraassayprecision: thawingandanalyzing 20replicateson 1 NMR

analyzer

Plasma pool B total LDLparticles(nmol/L):

IntraassayCV =4.0%InterassayCV =4.3%

NMR aliquotedandfrozensamples(LDL

sizes, nm) nd

Plasma pool A LDL size(nm):

IntraassayCV =0.5%InterassayCV =0.4%Plasma pool B LDL size

(nm): IntraassayCV =0.5%InterassayCV =0.6%

19 subjects with LDL scores ranged from2.9 to 16.5, assayed on 3 days over a 1weekperiod B Pattern A: LDLSF score 8.5 C Samples were analyzed in duplication of 10 D Betweenrun reproducibility forparticle diameterwas determined byrepeatedlyanalyzing an isolated LDL sample stored in aliquots at 70 C

overan 8weekperiod E Betweenrun CVs calculated frommeasurements performed on different days (not defined but all samples were analyzed within 4 days), using

isolated LDL sample stored in aliquots at 86C F Unclearhow manysamples and which separation method were used forthe intraassayvariation G The studies onlyincluded forthe questions on test variability, not for the comparison of different methods formeasuring LDL subfractions

A

31

Question 4

Question4.1 Whatistherelationship betweenLDLsubfractionsand outcomemeasuresrelatedtoCVD?

Weevaluatedall studies that analyzedtheassociation between LDL subfractions andcardiovascularoutcomes. Weperformeddetailedanalysis of thestudies that usedthemethods availablefor clinical usefor measuringLDL subfractions. For this section, wesearchedfor and, whereavailable,includedeligiblestudies that usedNMR aspecifickit for GE thatis availablefor clinical use(LipoPrint) aspecificgradient GE methodusedattheBerkeley HeartLab thecurrent methodusedattheNorthwest LipidResearch Lab andtheVertical AutoProfilemethodusedby Atherotech.

Ten studies examinedtherelationships between NMR measuredLDL subfractions andcardiovascularoutcomes.27,3442 All NMR studies hadtheir samples run by asingleset of researchers at LipoScienceor its precursors. (Wedonot repeatedly namethis company, as is necessary todistinguish theproprietary GE tests, since NMRis sufficiently descriptive.)

Eight studies examinedtherelationships between LipoPrintGE measuredLDL subfractions andcardiovascularoutcomes.4350

Onestudy hadtheir samples analyzedby theBerkeley HeartLabusingwhat we concludedwerethesamemethods that are availableclinically.51

No study that met eligibility criteriausedtheVertical AutoProfile. Weconcludedthatnoneof thestudies hadtheir samples performedat theUniversity of Washingtons NorthwestLipidResearch Laboratory usingthecurrently clinically availablemethods.

NMRmeasuredLDL subfractions Fivenestedcasecontrol studies,27,35,37,40,42 four crosssectional studies,34,36,38,39 andone

prospectivelongitudinal study41 reported on theassociation between NMR measuredLDL subfractions andcardiovascularoutcomes. Four studies wereof good methodological quality andsix wereof fair methodological quality. Thenumberof subjects in thesestudies rangedfrom 118to5538. Many of thestudies haveslightly differentdefinitions of theLDL size subfractions (eg,onestudy definedsmall LDL as 18.3to 19.7nm,27 whileanotherstudy definedsmall LDL as 18.0to21.2 nm40). Somestudies enrolledonly women (eg,Womens Health Study27) andsomestudies enrolledonly men (eg,VA HDL Intervention Trial40). Somestudies enrolledhealthysubjects atbaselineandsomestudies enrolledonlypatients with diabetes or lowHDLcholesterol concentrations. Half of thestudies enrolled40percent or morepatients olderthan 65years.

Incidence or progressionofCVD Fivestudies evaluatedtheassociation between NMRmeasuredLDL subfractions and

incident CVDor progression of CVD(Tables 3a& 3b).27,35,37,40,42

Fatal or nonfatal CVDevents Both good quality nestedcasecontrol studies foundthat LDL particlenumberwas

associatedwith theriskof incident fatal or nonfatal coronary artery disease, or stroke(Blake

32

http:clinically.51

2002:adjustedOR4th quartilecomparedto 1stquartile=2.90(1.167.30), P=0.03 El Harchaoui2007:adjustedOR4th quartilecomparedto 1stquartile=1.37(1.041.83), P=0.02). WhiletheLDL particlesize showedunadjustedsignificant differences between cases andcontrol in thesestudies, therelativeriskcomparingdifferent quartiles of particlesize failedtodemonstratestatistical significance afteradjustment for baselinelipidvariables. Onefair quality study foundstatistically significant differences between cases (incident myocardial infarction or angina)andcontrol in LDL particleconcentration andsize in women, but not in men.37 Afterabivariateanalysis includingLDLcholesterol in thecalculation, LDL particleconcentration (OR 1.11per100nmol/L, 1.031.09) remainedsignificantly different between caseandcontrol. Theotherfair quality study foundsimilarrelationships between LDL particlenumberandtheriskof incidentmyocardial infarction or deaths from coronary artery disease(OR 1.20(95% CI 1.051.37) per 1SDincrement of LDL particlenumber) in men. Theauthors reported that adjustment for baselinelipidvariables didnot appreciably changetheserelationsbut theactual datawerenot shown.40

Diagnosis of CVDOnefair quality study reportedunadjustedsignificant differences between cases (incident

coronary artery disease)andcontrols in LDL particlesize, medium andsmall LDL. Small andmedium size LDL failedto predict incident coronary artery diseasein multivariateanalysis.42

Changein minimum lumen diameterOnefair quality prospectivestudy reportedan association between LDL particlesize and

small LDL with worseningin minimum lumen diameter(Table4).41 Thestudy reported adjustedORs of 0.2(95% CI 0.1 0.9) for particlesize (abovevs. belowmedian size) and9.1(95% CI 2.139) for small LDL (abovevs. belowmedian concentration).41

PrevalentCVD Four studies evaluatedtheassociation between NMRmeasuredLDL subfractions and

prevalence of CVD(Tables 5a& 5b).34,36,38,39

Diagnosis of CVDOnepoor quality study foundastatistically significant difference between healthy subjects andsubjects with CVDin theproportion of largeLDL particle(66.5% vs. 43.3%, P=0.001) andparticlesize (21.4nm vs. 20.8nm, P=0.001).34 This study didnot reportadjustment for differences in baselinelipidmeasurements.

Intermediatemarkersof CVDThree fair quality crosssectional studies analyzedtherelationships between LDL

subfractions andintermediatemarkersof prevalentCVD. Thefirst study foundthat largeandsmall LDL particles wereassociatedwith carotidIMT (Changein IMT inmicrons peroneSD=30.3for large, and34.8for small, both P=0.001).39 Thesecondstudy foundthat therewas noassociation between small LDL with reduction in lumen diameter.36 Thethirdstudy foundthatLDL particlenumber, size, andsmall LDL wereassociatedwith coronary calcification (adjustedOR 1.44(95% CI 1.041.99) 0.55(95% CI 0.31 0.99) 1.36(95% CI 1.041.77) respectively, per1SD increasein lipoprotein subclass).38

Summary Results from thegood andfair quality casecontrol studies suggest that LDL particle

concentration andparticlenumber(as measuredbyNMR spectroscopy) areassociatedwithincident cardiovascularoutcomes. But theassociation between LDL particlesize andincident

33

http:subclass).38http:diameter.36http:0.001).39http:P=0.001).34http:concentration).41http:analysis.42http:shown.40http:1.051.37http:1.031.09http:1.041.83http:1.167.30

cardiovascularoutcomes is inconsistent two good andonefair quality casecontrol studies didnotfindassociations whileonefair quality study reported an association in women, but notmen.

Twofair quality crosssectional studies with atotal of 5696patients suggest that smallLDL particles areassociatedwith intermediatemarkersof prevalent CVDwhileonefair qualitystudy that analyzed158patients didnot findthis association. Onefair quality longitudinal studydidfindan association between small LDL andchanges in minimum lumen diameter.

LipoPrint GEmeasuredLDL subfractions Itis important tonotethattheintendeduse for theLipoprint test as statedin the

manufacturers productinsert is tomeasuretheamountof cholesterol in each of thelargebuoyant andsmall denseLDL subfractions. Useof theLipoprintkit todetermineparticlesizes or LDL scores or any otherform of classification is notrecommendedby themanufacturerof thekit. Despitethis disclaimerfrom themanufacturer, thestudies citedin thereportusedtheLipoprint test todetermineCVA riskby measuringlipoprotein subfraction by particlesize or complicatedLDL scores.

Incidence or progressionofCVD No studies evaluatedtheassociation between LipoPrintGEmeasuredLDL subfractions

andincident CVDor progression of CVD.

PrevalentCVD Twocasecontrol studies43,50 (Tables 6a& 6b) and six crosssectional studies4449 (Tables

7a& 7b) reported on theassociation between LipoPrintGEmeasuredLDL subfractions andprevalent CVD.Six studies wereof fair methodological quality andtwowereof poor methodological quality. Thenumberof subjects in thesestudies rangedfrom 27to 792. Many of thestudies havedifferent definitions of small LDL subfractions (eg, onestudy definedpattern Bas LDL

artery branches) in amultiplelogisticregression that includedlowandhigh HDLcholesterol.45 Thethirdstudy foundthat LDL score was significantly different between patients who hadprevalent carotidatherosclerosis andthosewho didnot in an unadjustedanalysis (1.56vs. 1.26, P=0.04), but a stepwiselogisticregression that includedotherlipidvariables renderedtheassociation nonsignificant (adjustedOR2.20 (95% CI 0.915.29) theodds of higherLDL scorein patients with carotidatherosclerosis theexact units of theOR werenotreported).46 Thelaststudy foundthat in patients with type2diabetes, thosewith ahistory of coronary artery disease(myocardial infarction and/or nitrates, revascularization, or EKGchanges) hadstatisticallysignificantly different small LDL profile(LDL 3andabove)than thepatients who didnot(overall sum of LDL3to 5: 16.7 vs. 11.1, P

Table 3a. Characteristicsof the nested casecontrol studiesof incident CVD and NMRmeasuredLDLsubfractionsAuthor, YearCountryUI

Population Mean Age, Ayears

>65, A,B%

Male, A%

DM, A%

Smoke, A%

Mean LDLc, Amg/dL

Blake, 200227US 12370215

WomensHealth Study: RCTof aspirin vs. vitaminE vs. placebo.Subjects had baseline blood sample withsubsequent cardiovascular

event 60 ~30 0 11 59 129

El Harchaoui, 200735UK 17276177

EuropeanProspective Investigation into Cancer and Nutrition (EPIC), age between45and 79 years 65 ~50 64 6 16 164

Kuller, 200237US 12117734

Cardiovascular Health Study, Age65years, noninstitutionalized, 95%White 73 100 56 nd nd 129

Otvos, 200640US 16534013

VeteransAffairs HDLIntervention Trial (VAHIT) (gemfibrozil vs. placebo), age

Table 3b. Nested casecontrol studiesof incident CVD and NMRmeasuredLDL subfractionsAuthor YearCountryUI

Population Definitions Cases Control P Other results Quality

Blake 200227US 12370215

WomensHealthStudy

Case=deathdue to CAD, nonfatal MI, or stroke n=130 n=130

Risks of event (adjustedfor TgandTC/HDLc)

4thquartile comparedto 1stquartile:

ALarge: 213227 886 A (nmol/L) 1001 0.50

Medium: 198212 201 126 .008 Small: 183197 0 0 .80

LDLparticle concentration 1597 1404

Table 3b. Continued

A median

Author YearCountryUI

Population Definitions Cases Control P Other results Quality

Otvos, 200640US 16534013

VA patient withCHD

LDLc140 mg/dL

HDLc40mg/dL

Tg300 mg/dL

Case=New nonfatal MI or CHD death n=364 n=697

Risks of event, adjustedfor treatment group, age, HTN, smoking, BMI and DM

Adjustment for LDLc, HDLc, and Tg didnot appreciablychange these relations [nd]).

per 1SD increase in parameter

BLarge: 212230 nd OR=1.08(0.951.23) NS

Small: 180212 nd OR=1.11(0.981.27) NS LDLparticleconcentration nd OR=1.20(1.051.37) P

Table 4. Longitudinal study ofNMRmeasured LDLsubfractions and progressionof CVD AuthorYearCountryUI

Population Mean Age, Ayears >65, A,B

%Male, A

%DM, A%

Smoke, A%

Mean LDLc, Amg/dL

Rosenson 200241US 12106834

Pravastatin Limitationof Atherosclerosis inthe Coronary Arteries(PLACI) trial, completed3yearsin the RCT, frozenplasmaand coronary angiogram at baseline

Patientswith CAD in RCTof pravastatin(n=130) vs. placebo(n=111)

58 ~20 76 nd nd 163

Outcome Definitions Results Quality

Change in minimum lumendiameter (MLD) over 3 yearsn=241

Spearman correlations, adjustedforLDLc, HDLc, Tg and other factors

B

Large: 213230 0.03 (NS)

Medium: 198212 nd

Small: 183197 0.17(P0.07 mm/y, over 3yearsn=111 (placeboarm only)

Risk of progression, adjustedforLDLc, HDLc, Tg and other factors

Large: 213230 84mg/dL vs.

Table 5a. Characteristicsof patientsin the crosssectional studies of prevalent CVD and NMRmeasured LDLsubfractionsAuthorYearCountryUI

Population Mean Age, Ayears

>65, A,B%

Male, A%

DM, A%

Smoke, A%

Mean LDLc, Amg/dL

Mora200739US 16765964

MultiEthnic Studyof Atherosclerosis (MESA), age 4584 years, noselfreportedCHD, from 6centers 61 ~40 47 12 14 120

Freedman199836US 9672064

Menadmittedfor coronary angiogram (severe orunstable angina, myocardial ischemia after MI, recurrent chest painof unknownorigin), did

notuse cholesterollowering medications, Tg

Table 5b. Crosssectional studiesof NMRmeasured LDL subfractionsandprevalent CVD outcomesAuthor YearCountryUI

Population Outcome Definitions Results Quality

Mora200739US 16765964

NoselfreportedCVD n=5538 Carotid IMT

Association, adjustedfor LDL subfractions, age, sex, race, HTN, smoking, LDLc, HDLc, and Tg

IMTper one SD of parameter B

Large: 212230 +30.3 (11.9, 48.7) P

Table 6a. Characteristicsof casecontrol studiesof prevalent CVD andLipoPrint GEmeasured LDL subfractionsAuthorYearCountryUI

Population Mean Age A, years

>65, A,B%

Male, A%

DM, A%

Smoke, A%

Mean LDLcA(mg/dL)

Yoon 200550S. Korea15899660

Consecutive patients whounderwent coronary angiogram, age

Table 7a. Characteristicsof patientsin the crosssectional studies of prevalent CVD and LipoPrint GEmeasured LDLsubfractions AuthorYearCountryU