Thanks for the question, Raj -
For those not familiar with factor analysis it takes a bunch of variables (that are often correlated with one another) and creates (I think generally linear) combinations of them in a way that these new "factors" are now no longer correlated with one another.
The advantage is that you can reduce the number of variables to a smaller number without losing much information.
The disadvantage (which to me more than outweighs the advantage) is that the new variables now generally no longer have an intuitive meaning or interpretation. So your clinical prediction rule may now include a variable equal to 0.0243 times the LDL cholesterol level in mg/dL + .0442 times the blood pressure in mm Hg - 0.2217 times the HDl cholesterol - 1.2 if you are a woman, and that variable will have a certain coefficient, so you'll be able to say a 1 SD change in this variable is associated with a 40% increase in heart disease, but it's a lot more satisfying to know the effect of each of these variable separately.
Tom