Cardiology Journal Club

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Cardiology Journal Club

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

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MULTIPLE BIOMARKERS FOR THE PREDICTION OF FIRST
MAJOR CARDIOVASCULAR EVENTS AND DEATH

• Wang, Thomas J., et al.
• Massachusetts General Hospital.
• NEJM. Volume 355(25), 21 December 2006, pp
  2631-2639.

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Overview

• To evaluate the incremental usefulness of
  multiple biomarkers from various pathways.
• Established risk factors, including smoking, htn,
  DM, and dyslipidemia.
• Significant interest in new biomarkers for risk
  stratification of ambulatory persons.

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Novel Approach

• Many individual biomarkers have been studied.
• Multimarker Approach
• Simultaneous measurement may enhance risk
  stratification?

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Outcomes Analysis

• 1. Death from any cause
• 2. 1st Major cardiovascular event (MI, coronary
  insufficiency, heart failure, and stroke.
• Reviewed by a committee of three investigators

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Study Sample

• Large, community based cohort study
• Participants from the sixth examination cycle
  (1995-1998) of the Framingham Offspring Study
• IRB of Boston University Medical Center approval
• Written informed consent was obtained
• H P, PE, and Lab Assessment

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Exclusion Criteria

• Serum creatinine levels greater than 2.0 mg/dL
• Missing covariates
• Prior event when determining outcome of major
  cardiovascular event
• Triglycerides gt 400

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Biomarker Selection

• 1. Marker of inflammation- hsCRP
• 2. Markers of neurohormonal activity- BNP,
  aldosterone, renin, N-terminal pro-atrial
  natriuretic peptide
• 3. Marker of thrombosis and inflammation-
  fibrinogen
• 4. Marker of fibrinolytic potential and
  endothelial function- plasminogen-activator

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Biomarker contd

• Inhibitor type 1
• 5. Marker of thrombosis- D-dimer
• 6. Marker of endotheial function and oxidant
  stress- homocysteine
• 7. Marker of glomerular endothelial function-
  urinary albumin-to-creatinine ratio

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Lab Protocol

• Fasting blood and urine samples collected in
  morning after patient supine for 10 minutes.
  Immediately centrifuged and stored at -70
  degreesC.
• Standardized Assay Methods

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Statistical Analysis

• Multivariable proportional-hazards model (2 sets
  of analyses for each outcome due to urine
  subgroups)
• Logarithmic transformation used to normalize the
  distribution of biomarkers
• To reduce the number of false positives from
  multiple testing

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Statistics contd

• 1) Multivariable Cox regression model
• 2) Backward elimination
• 3) Construction of multimarker score
• 4) Quintiles categorized
• 5) Cumulative probability curves constructed by
  the Kaplan-Meier method for low, intermediate and
  high mulitmarker scores

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Statistics contd

• Then calculated hazard ratios for death and major
  cardiovascular events for the mulitmarker score
  groups
• Adjusted for age, sex, conventional risk factors
  including htn, smoking, dm, etc.
• C statistic
• ROC curves

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Statistics contd

• Secondary Analysis adjusting for medication use
• Repeated a Cox proportional-hazards model for
  major cardiovascular events adjusting for
  nonmajor events ? angina, intermittent
  claudication, TIA
• SAS software, version 8 (SAS Institute)

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C Statistic

• Defined as the probability of concordanc among
  persons who can be compared.
• Estimated as the sum of concordance values
  divided by the number of comparable pairs.
• Better able to measure discrimination than
  relative risk.

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Results

• Total of 3532 persons- 21 excluded for serum
  creatinine and 302 for missing covariates.
• 10 year follow-up (median 7.4 years) 3209
  available for study.
• 207 (6) died, of whom 72 were women
• 169 (6, excluding prevalent CV disease at
  baseline) had a major cardiovascular event, of
  whom 68 were women

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Results contd

• Biomarker panel for nine Plt0.001 for death and
  P0.005 for cardiovascular events
• Biomarker panel for ten (2750 persons) Plt0.001
  for death and P0.04 for cardiovascular events

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Results contd

• Backward elimination models final statistical
  model included only the following biomarkers
• BNP, homocysteine, urinary albumin-to-creatinine
  ratio and renin for death.
• BNP and urinary albumin-to-creatinine ratio for
  major cardiovascular events.

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Utility of Multimarker Scores

• Backward elimination biomarkers selected as
  statistically significant were incorporated into
  mulitmarker scores.
• Restricted to urine sample patients 1) death
  from any cause, the number of events and number
  at risk were 172 and 2750, respectively 2)
  major cardiovascular events, 133 and 2598,
  respectively.

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Utility?

• Persons with high multimarker scores had a risk
  of death four times as great and a risk of major
  cariovascular events almost two times as great as
  persons with low mulitmarker scores.
• (Plt0.001 and P0.02, respectively)

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Discussion

• 10 year study of biomarkers indicating BNP,
  hsCRP, homocysteine, renin, and alb/Cr ratio as
  most informative for predicting death, while BNP
  and alb/Cr ration as significant for predicting
  cardiovascular outcome.
• Although high multimarker scores conferred
  greater risk for death and major cardiovascular
  events

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Conclusion

• Mulitmarker scores (combination of biomarkers)
  add only moderately to conventional risk factors
  as evidenced by small changes in C statistic.
• Single biomarkers may have correlation with
  predicting outcomes
• Panel likely will not be useful or cost-effective
  in ambulatory setting for further risk
  stratification

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Limitations

• Biomarker selection omission of
  lipoprotein-associated phospholipase A2
• Each individual marker not independently tested
• Not a true cohort study to asses for primary
  prevention as nonmajor cardiovascular events
  adjusted
• Adiposity or insulin resistance not taken into
  account

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Summary

• Biomarkers from multiple, biologically distinct
  pathways are associated with the risks of death
  and major cardiovascular events.
• However, only moderately adds to conventional
  risk factors currently.