Coronary artery disease
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Multivariable Risk and Risk Prediction
Transcript of Coronary artery disease
Multivariable Risk and Risk Prediction
Coronary Artery Disease (CAD)Impact
• Heart disease has remained the leading cause of death in the United States for nearly 100 years.
• At approximately 710,000 deaths a year, heart disease accounts for nearly 30% of all deaths in the U.S.
• In 2000, the U.S. mortality rate for heart disease was 258/100,000.
• Second leading cause of disability in older men and women
medlib.med.utah.edu/WebPath/jpeg5/CV004.jpg
www.medicalengineer.co.uk/atherosclerosis.jpgwww.smbs.buffalo.edu/
Cholesterol hypothesis
Framingham: A seminal cohort study of CHD
Circulation. 1967;35:734
Logistic Model
General Form
Logit P(X) = + 1X1+ 2X2+… jXj
To find the probability of the outcome given the risks present:
P(X)= 1 / 1 + e-( + iXi)
Table 1. Framingham Functions (Cox Regression Coefficients) for Hard CHD Events (Coronary Death or MI)*
JAMA. 2001;286:180-187
OR = exp(0.83) = 2.29
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LaRosa, J. C. et al. JAMA 1999;282:2340-2346.
Relative Odds of Major Coronary Events Associated With Statin Treatment From Individual Trials and Overall by Sex and Age
“Classic” Risk Factors• Age (85% of CHD mortality in people over 65)• Male Gender• Race
– African Americans have higher risk than whites until advanced age– Asian Americans have half the risk of whites
• Cigarette Smoking• Family History• Low SES• Obesity• Low Physical Activity• Hypertension• Diabetes• Serum Cholesterol
– Low High-Density Lipoprotein Concentrations– High Low-Density Lipoprotein Concentrations
Determining an individual’s risk
P(X) = 1 / 1 + e –( + 1X1+ 2X2+… jXj)
= the estimate of the baseline (no exposures) risk in the population
B1, B2 … Bj are the estimates of the independent effects of each exposure in the model
Evaluating Predictive Models
Accuracy• Discrimination-the correct
ordering of individuals in terms of risk relative to one another
• Calibration-the accuracy of the numeric probabilities generated by the model
Generalizability• Reproducibility-the ability
of the model to predict accurately within the underlying population from which the study subjects were drawn
• Transportability-the ability of the model to predict accurately outside of the conditions under which it was created
Accuracy-Discrimination
• Discrimination is measured using the area under the Receiver Operating Characteristic (ROC) Curve. The ROC curve plots sensitivity on the y-axis verses (1-specificity) on the x axis.
• A perfectly discriminating model will have an ROC area of 1.0 while a completely non-discriminating model will have an area of 0.5.
Example of ROC Curve
Generalizability• Reproducibility-the degree to which the model can replicate its accuracy
in people outside of the subjects included in the development of the model but from within the same population from which those subjects came.
• Transportability-the ability of the model to predict accurately:– In a different population– In a different era of calendar time (historic transportability)– In a different place (geographic transportability)– Over a different follow-up period (follow-up transportability)– Across different researchers and subtle variations in methodology
(methodologic transportability)– Across varying exposure prevalences (spectrum transportability)
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Circulation. 2004;110:227-239.
Third Report of the Expert Panelon Detection, Evaluation, and Treatment of High Blood
Cholesterol in Adults (Adult Treatment Panel III)
www.smj.org.uk/0803/CHD%20figure_1.htm .
Trends in coronary heart disease mortality among men aged 35-64 in selected countries/areas
