Cardiology Cardiology Journal ClubJournal Club

Sanjay Dravid, M.D.Sanjay Dravid, M.D.January 17, 2006January 17, 2006

MULTIPLE BIOMARKERS MULTIPLE BIOMARKERS FOR THE PREDICTION OF FOR THE PREDICTION OF

FIRST MAJOR FIRST MAJOR CARDIOVASCULAR CARDIOVASCULAR

EVENTS AND DEATH EVENTS AND DEATH

Wang, Thomas J., et al. Wang, Thomas J., et al. Massachusetts General Hospital. Massachusetts General Hospital. NEJM. Volume 355(25), 21 NEJM. Volume 355(25), 21

December 2006, pp 2631-2639.December 2006, pp 2631-2639.

OverviewOverview To evaluate the incremental To evaluate the incremental

usefulness of multiple biomarkers usefulness of multiple biomarkers from various pathways.from various pathways.

Established risk factors, including Established risk factors, including smoking, htn, DM, and dyslipidemia.smoking, htn, DM, and dyslipidemia.

Significant interest in new Significant interest in new biomarkers for risk stratification of biomarkers for risk stratification of ambulatory persons. ambulatory persons.

Novel ApproachNovel Approach

Many individual biomarkers have Many individual biomarkers have been studied.been studied.

““Multimarker” ApproachMultimarker” Approach Simultaneous measurement may Simultaneous measurement may

enhance risk stratification?enhance risk stratification?

Outcomes AnalysisOutcomes Analysis

1. Death from any cause1. Death from any cause 2. 12. 1stst Major cardiovascular event Major cardiovascular event

(MI, coronary insufficiency, heart (MI, coronary insufficiency, heart failure, and stroke.failure, and stroke.

Reviewed by a committee of three Reviewed by a committee of three investigators investigators

Study SampleStudy Sample Large, community based cohort studyLarge, community based cohort study Participants from the sixth examination Participants from the sixth examination

cycle (1995-1998) of the Framingham cycle (1995-1998) of the Framingham Offspring Study Offspring Study

IRB of Boston University Medical IRB of Boston University Medical Center approval Center approval

Written informed consent was obtained Written informed consent was obtained H & P, PE, and Lab AssessmentH & P, PE, and Lab Assessment

Exclusion CriteriaExclusion Criteria

Serum creatinine levels greater than Serum creatinine levels greater than 2.0 mg/dL2.0 mg/dL

Missing covariatesMissing covariates Prior event when determining Prior event when determining

outcome of major cardiovascular outcome of major cardiovascular eventevent

Triglycerides > 400Triglycerides > 400

Biomarker Selection Biomarker Selection 1. Marker of inflammation- hsCRP1. Marker of inflammation- hsCRP 2. Markers of neurohormonal activity- 2. Markers of neurohormonal activity-

BNP, aldosterone, renin, N-terminal BNP, aldosterone, renin, N-terminal pro-atrial natriuretic peptidepro-atrial natriuretic peptide

3. Marker of thrombosis and 3. Marker of thrombosis and inflammation- fibrinogeninflammation- fibrinogen

4. Marker of fibrinolytic potential and 4. Marker of fibrinolytic potential and endothelial function- plasminogen-endothelial function- plasminogen-activator activator

Biomarker cont’dBiomarker cont’d Inhibitor type 1Inhibitor type 1 5. Marker of thrombosis- D-dimer5. Marker of thrombosis- D-dimer 6. Marker of endotheial function and 6. Marker of endotheial function and

oxidant stress- homocysteineoxidant stress- homocysteine 7. Marker of glomerular endothelial 7. Marker of glomerular endothelial

function- urinary albumin-to-function- urinary albumin-to-creatinine ratio creatinine ratio

Lab ProtocolLab Protocol Fasting blood and urine samples Fasting blood and urine samples

collected in morning after patient collected in morning after patient supine for ~10 minutes. supine for ~10 minutes. Immediately centrifuged and stored Immediately centrifuged and stored at -70 degreesC. at -70 degreesC.

Standardized Assay MethodsStandardized Assay Methods

Statistical AnalysisStatistical Analysis Multivariable proportional-hazards Multivariable proportional-hazards

model (2 sets of analyses for each model (2 sets of analyses for each outcome due to urine subgroups)outcome due to urine subgroups)

Logarithmic transformation used to Logarithmic transformation used to normalize the distribution of normalize the distribution of biomarkersbiomarkers

To reduce the number of false To reduce the number of false positives from multiple testing: positives from multiple testing:

Statistics cont’dStatistics cont’d 1) Multivariable Cox regression model1) Multivariable Cox regression model 2) Backward elimination 2) Backward elimination 3) Construction of multimarker score3) Construction of multimarker score 4) Quintiles categorized 4) Quintiles categorized 5) Cumulative probability curves 5) Cumulative probability curves

constructed by the Kaplan-Meier constructed by the Kaplan-Meier method for low, intermediate and high method for low, intermediate and high mulitmarker scoresmulitmarker scores

Statistics cont’dStatistics cont’d Then calculated hazard ratios for Then calculated hazard ratios for

death and major cardiovascular events death and major cardiovascular events for the mulitmarker score groups for the mulitmarker score groups

Adjusted for age, sex, conventional Adjusted for age, sex, conventional risk factors including htn, smoking, risk factors including htn, smoking, dm, etc.dm, etc.

““C statistic”C statistic” ROC curvesROC curves

Statistics cont’dStatistics cont’d Secondary Analysis adjusting for Secondary Analysis adjusting for

medication usemedication use Repeated a Cox proportional-hazards Repeated a Cox proportional-hazards

model for major cardiovascular events model for major cardiovascular events adjusting for “nonmajor events” adjusting for “nonmajor events” angina, intermittent claudication, TIAangina, intermittent claudication, TIA

SAS software, version 8 (SAS SAS software, version 8 (SAS Institute) Institute)

C StatisticC Statistic Defined as the probability of Defined as the probability of

concordanc among persons who can concordanc among persons who can be compared.be compared.

Estimated as the sum of Estimated as the sum of concordance values divided by the concordance values divided by the number of comparable pairs.number of comparable pairs.

Better able to measure Better able to measure discrimination than relative risk. discrimination than relative risk.

ResultsResults Total of 3532 persons- 21 excluded for Total of 3532 persons- 21 excluded for

serum creatinine and 302 for missing serum creatinine and 302 for missing covariates.covariates.

10 year follow-up (median 7.4 years) 10 year follow-up (median 7.4 years) 3209 available for study.3209 available for study.

207 (6%) died, of whom 72 were women207 (6%) died, of whom 72 were women 169 (6%, excluding prevalent CV disease 169 (6%, excluding prevalent CV disease

at baseline) had a major cardiovascular at baseline) had a major cardiovascular event, of whom 68 were womenevent, of whom 68 were women

Results cont’d Results cont’d

Biomarker panel for nine: P<0.001 Biomarker panel for nine: P<0.001 for death and P=0.005 for for death and P=0.005 for cardiovascular eventscardiovascular events

Biomarker panel for ten (2750 Biomarker panel for ten (2750 persons): P<0.001 for death and persons): P<0.001 for death and P=0.04 for cardiovascular events P=0.04 for cardiovascular events

Results cont’dResults cont’d Backward elimination models: final Backward elimination models: final

statistical model included only the statistical model included only the following biomarkers:following biomarkers:

BNP, homocysteine, urinary albumin-BNP, homocysteine, urinary albumin-to-creatinine ratio and renin for to-creatinine ratio and renin for death.death.

BNP and urinary albumin-to-creatinine BNP and urinary albumin-to-creatinine ratio for major cardiovascular events.ratio for major cardiovascular events.

Utility of Multimarker Utility of Multimarker ScoresScores

Backward elimination biomarkers Backward elimination biomarkers selected as statistically significant were selected as statistically significant were incorporated into mulitmarker scores.incorporated into mulitmarker scores.

Restricted to urine sample patients: 1) Restricted to urine sample patients: 1) death from any cause, the number of death from any cause, the number of events and number at risk were 172 and events and number at risk were 172 and 2750, respectively; 2) major 2750, respectively; 2) major cardiovascular events, 133 and 2598, cardiovascular events, 133 and 2598, respectively.respectively.

Utility?Utility? Persons with high multimarker Persons with high multimarker

scores had a risk of death four times scores had a risk of death four times as great and a risk of major as great and a risk of major cariovascular events almost two cariovascular events almost two times as great as persons with low times as great as persons with low mulitmarker scores.mulitmarker scores.

(P<0.001 and P=0.02, respectively) (P<0.001 and P=0.02, respectively)

DiscussionDiscussion ~10 year study of biomarkers ~10 year study of biomarkers

indicating BNP, hsCRP, homocysteine, indicating BNP, hsCRP, homocysteine, renin, and alb/Cr ratio as most renin, and alb/Cr ratio as most informative for predicting death, while informative for predicting death, while BNP and alb/Cr ration as significant BNP and alb/Cr ration as significant for predicting cardiovascular outcome.for predicting cardiovascular outcome.

Although high multimarker scores Although high multimarker scores conferred greater risk for death and conferred greater risk for death and major cardiovascular events…major cardiovascular events…

ConclusionConclusion Mulitmarker scores (combination of Mulitmarker scores (combination of

biomarkers) add only moderately to biomarkers) add only moderately to conventional risk factors as evidenced conventional risk factors as evidenced by small changes in C statistic.by small changes in C statistic.

Single biomarkers may have Single biomarkers may have correlation with predicting outcomescorrelation with predicting outcomes

Panel likely will not be useful or cost-Panel likely will not be useful or cost-effective in ambulatory setting for effective in ambulatory setting for further risk stratification further risk stratification

LimitationsLimitations Biomarker selection: omission of Biomarker selection: omission of

lipoprotein-associated phospholipase A2lipoprotein-associated phospholipase A2 Each individual marker not Each individual marker not

independently testedindependently tested Not a true cohort study to asses for Not a true cohort study to asses for

primary prevention as “nonmajor” primary prevention as “nonmajor” cardiovascular events adjusted cardiovascular events adjusted

Adiposity or insulin resistance not taken Adiposity or insulin resistance not taken into account into account

SummarySummary Biomarkers from multiple, Biomarkers from multiple,

biologically distinct pathways are biologically distinct pathways are associated with the risks of death associated with the risks of death and major cardiovascular events. and major cardiovascular events.

However, only moderately adds to However, only moderately adds to conventional risk factors currently.conventional risk factors currently.