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Comparing Zero Coronary Artery Calcium With Other Negative Risk

Factors for Coronary Heart Disease

A Novel Methodology: Risk-Adjusted Negative Likelihood Ratios

Multi-Ethnic Study of Atherosclerosis (MESA)

Michael J. Blaha1, Bill McEvoy1, Ron Blankstein2, Matthew J. Budoff3, Chris Sibley4, Moyses Szklo5, Richard Kronmal6, Roger S. Blumenthal1, Khurram Nasir1, 7

** Author affiliations in acknowledgements

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Negative Risk Factors

• Most novel biomarkers marginally improve risk prediction at population level, adding little for individual patient

• Theme of reporting: risk factor X adds slightly increases predicted risk more testing, more treatment needed!

• Less attention is paid to “negative” risk factors despite tremendous potential public health implications

• “Imaging Hypothesis” – due to high sensitivity, NPV >> PPV, potential value as negative risk factors

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Tools for Comparing Risk Factors

• Survival analysis - HR• ROC Analysis – c-statistic• Net reclassification

improvement (NRI)

• Do not communicate change in “risk” to the clinician decision-maker

• Do not emulate Bayesian decision making

Specific Aim: Adapt a methodology for calculating and comparing risk-adjusted LRs and apply to “negative risk factors”

Likelihood Ratios (LRs) – “Bayes Factors”Directly communicate the change in risk before and after knowledge of a new test result

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Methods: Risk-Adjusted Likelihood Ratios

logit Ppost-test = logit Ppre-test + log LR

* X = Framingham Risk Factors + race/ethnicity

(Gu and Pepe 2009)

** Y = Negative Risk Factor, i.e. CAC=0

**

*** Calculate estimated LR for each MESA participant, for negative risk factor

***METHOD

S

*

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Multi-Ethnic Study of Atherosclerosis

Negative RiskFactor

Prevalence in MESA

hsCRP <2 mg/L 52%

Homocysteine <10 umol/L

69%

BNP <100 pg/mL 71%

No MetabolicSyndrome

67%

No microalbuminuria

90%

No family history 57%

Normal ABI (1.0 – 1.3)

85%

No carotid plaque 58%

Normal cIMT (<25th percentile)

25%

Zero CAC 50%

• Multicenter study of 6,814 individuals free of known cardiovascular disease

• Follow-up for All CHD events over mean 7.1 years

**

0%5%

10%

15%

20%

Po

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ith N

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0% 5% 10% 15% 20%

Pre-Test Risk Estimate

hsCRP <2 mg/dLNo microalbuminuriaHomocysteine <10 umol/LNormal ABINo Metabolic Syndrome

BNP <100 pg/mLNo family historyNo carotid plaquecIMT <25th percentileZero CAC

Post-Test Risk vs. Pre-Test Risk

(Baseline logistic model)

(Au

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* Linear fit

Zero CAC

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Patient 1

Zero CAC

Low cIMT (<50th percentile)

No family history CHD

No carotid plaque

No metabolic syndrome

Homocysteine <10 umol/L

Normal ABI (1.0 - 1.3)

hsCRP <2

BNP <100 pg/mL

No microalbuminuria

10.80.60.40.20

Framingham-Adjusted Likelihood Ratio

Intermediate Risk White ManPre-Test Risk 10%55 years oldTotal cholesterol 200 mg/dLHDL 35 mg/dLModerate treated hypertension

Logit ppost = logit ppre + log LR

CAC=0, post-test risk ~4%**

** 10-year risk extrapolated from 7.1 year risk

00.35

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Important Covariates Influencing Likelihood Ratio for CAC=0

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.40

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.81

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Like

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40 50 60 70 80

Age in years0

0.2

0.4

0.6

0.8

1.0

Like

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AC

0% 5% 10% 15% 20% 25% 30%

Pre-Test Risk Estimate (10-year CHD Risk)

Age Pre-Test Risk

Limitations – Pre-Test risk estimate

What is the correct tool for estimating pre-test risk?• Very poor calibration of FRS in MESA

Recalibrated 10-year “MESA FRS” for All CHD Therefore LRs immediately useful for MESA

FRS, not traditional FRSRescale factor = (MESA FRS/Traditional FRS) = 0.67

All CHD vs. Hard CHDRescale factor = 0.40

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Intermediate Risk AA Woman70 years oldSmokerTotal cholesterol 240 mg/dLHDL 50 mg/dLMild treated hypertension

MESA Risk All CHD = 10% FRS Hard CHD Risk = 14%

Logit ppost = logit ppre + log LR

Post-test All CHD risk ~3%

Post-test Hard CHD risk ~1.8%

Rescaled Likelihood Ratio

FRS All CHD = 0.20 FRS Hard CHD = 0.12

EXAMPLE USING CAC=0

Likelihood Ratio if CAC=0

MESA All CHD = 0.30

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iJACC paper, Lancet paper

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Conclusions and Implications

• The risk-adjusted likelihood ratio is a powerful, clinically-usable tool for comparing incremental value of risk factors

• Imaging tests, specifically CAC=0, are strongest negative risk factors for CHD

• CAC=0, which is present in 50% of MESA, appears to have a LR consistently in “clinically helpful” range

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Acknowledgements

• We wish to thank all the volunteer research participants who made this study possible.

• This research was supported by contracts R01 HL071739, N01-HC-95159 through N01-HC-95165, and N01-HC-95169 from the National Heart, Lung, and Blood Institute. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org.

Author Affiliations:

1 Johns Hopkins Ciccarone Center for Prevention of Heart Disease, Baltimore, MD2 Brigham and Women's Hosp Non-invasive CV Imaging Program, Boston, MA3 Division of Cardiology, Harbor-UCLA Medical Center, Torrance, CA4 National Institutes of Health, Bethesda, MD5 Johns Hopkins University, School of Public Health, Baltimore, MD6 University of Washington, Seattle, WA7 Yale University School of Medicine, New Haven, CT

Prevalence of coronary calcium increases with age.

Mortality Rate (per 1000 person-years) With Increasing Coronary Artery Calcium Scores &

Traditional Risk Factors

Nasir K, Blaha MJ, et al. Circulation Outcomes. 2011