Pre-Test Probability: What Is It And Why Should I Care?

In the past colleagues would throw around terms like “pre-test” probability, and I would have a little discomfort. I had a general idea of what a pre-test probability was, but could not define it well. As I started to teach students and residents, I thought “The human mind doesn’t work like that, these statistical terms don’ t mean much to everyday clinical medicine”. I sense that many of my colleagues have the same sense that I did then.

In researching for my book, A Guide to Clinical Decision Making, I again ran into the pre-test probability. I discovered that it was both an applicable concept in clinical medicine, and that there was a better a way to explain the concept than I had been taught. 

I began teaching my students and residents that the pre-test probability was a powerful concept in making medical decisions. When explained well, a junior student can understand the concept and apply it. Although this is blog post is only meant to be a brief, easy-to-follow introduction, I think that for many students and their teachers the concept of pre-test probability will be less daunting and more concrete after reading this. 

You can define the pre-test probability simply by it’s name: the probability of disease in your mind before you know the test result. 

Taking this one step further, the post-test probability is the probability of the disease in your mind after you know the test result. 

Here’s the important concept:

A test result can change your estimate of the probability of disease.

That’s a powerful statement.

A real-life example is the current decision making guidelines for assessing a patient for a pulmonary embolism (PE). In this example, think of risk of disease before testing as the pre-test probability.

• A history and physical is sufficient to rule out a PE for the patients with the lowest risk, the lowest pre-test probability. The history and physical is a sufficient test to outweigh the chance of a PE (see my previous blog post: My History And Physical Are Tests Too!)
• A d-dimer is sufficient to rule out a PE for the patients with a slightly higher risk. We have to test a little bit more to outweigh the chance of a PE.
• An imaging study is sufficient to rule out a PE for the patients with moderate risk or higher. We have to do the most intensive testing to outweigh these higher risk patients.

Each testing modality carries a different amount of weight in the decision making process.

To rule out a disease the weight of the evidence against the disease must outweigh the risk of having the disease (the pre-test probability). 

For example, a negative d-dimer is not sufficient to rule out pulmonary embolism in a high risk patient. The negative d-dimer does not have the weight to outweigh the risk of a PE in a high risk patient. 

So generally, to rule out a disease: 

• For a low risk patient, you will need a low weight of evidence against the disease. 
• For a moderate risk patient, you will need a moderate weight of evidence against the disease.    
• For a high risk patient, you will need a high weight of evidence against the disease.

Remember, the risk of disease is your pre-test probability.

The topic of pre-test probabilities certainly goes far beyond this brief discussion, but hopefully you’ll be a bit more confident using the concept in clinical practice or teaching others to use it.

For further discussions on this topic and other topics in clinical decision making, please check out my book: A Guide to Clinical Decision Making