2. 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
9. Logistic Model
General Form
Logit P(X) = α + Β1X1+ Β2X2+… ΒjXj
To find the probability of the outcome
given the risks present:
P(X)= 1 / 1 + e-(α+ΣΒiXi)
10. 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
11.
12. Copyright restrictions may apply.
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
13. “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
14.
15. Determining an individual’s risk
P(X) = 1 / 1 + e –(α+Β1X1+Β2X2+…ΒjXj)
α =the estimate of the baseline (no exposures) risk
in the population
B1,B2 … Bjare the estimates of the independent
effects of each exposure in the model
16.
17. 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
18. 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.
20. 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)
