StATS: Incorporating risk factors into diagnostic test calculations (November 9, 2006).

A contributor to the Evidence-Based Health email discussion group (PK) raised an interesting question about how to incorporate information about risk factors when applying the results of a diagnostic test.

When you are estimating a pre-test probability for a diagnostic test, you need to take three steps:

1. find an estimate of the prevalence of the disease in the general population,
2. modify this estimate based on characteristics of your particular practice, and
3. further modify this estimate based on characteristics of the individual patient that is currently sitting in front of you.

Risk factors should be incorporated in the third step. If your patient has diabetes, you should increase the pre-test probability estimates of arteriosclerosis, retinopathy, and renal disease. If your patient has a long history of cocaine abuse, you should increase the pre-test probability of various sinus and nasal diseases. If your patient has a sister who was diagnosed with breast cancer at the age of 45, you should increase the pre-test probability of breast cancer for this patient.

How much you adjust the pre-test probability is tricky, but it should certainly be done. This is classic illustration of how we can apply David Sackett's admonition to individualize the practice of EBM.

You could indeed think of the risk factors as diagnostic tests in their own right. Some of these ideas are covered in the JAMA Rational Clinical Examination series. Still this seems to me to be bit much. So if you are testing for heart disease and the patient is a smoker, just double the prevalence estimate.

Don't forget about the Step-2 adjustments also. Where you practice medicine can make a big difference in your pre-test probability. If you work in a tertiary care center, your prevalence rates are probably higher than it would be for a primary care physician. The funneling of patients and the screening/filtering that goes on will tend to concentrate the proportion of difficult cases.

There's an amusing story about screening for alcohol abuse. It turns out (not surprisingly) that alcohol abuse is very much dependent on the age and gender of the patient which is important for your Step-3 adjustment, but another interesting fact is that the rate of abuse in an outpatient setting is about twice that of the rate in the general population. For an inpatient setting, the rate is four times higher. These are Step-2 adjustments.

%22Why is it that patients in an outpatient or inpatient setting have a much greater probability of alcohol abuse?" I will typically ask my students. "Does being around doctors so much drive people to drink?" The answer, of course, is actually quite logical. People who abuse alcohol tend to have more health problems than the general population and tend to be overrepresented in outpatient and inpatient settings.