Whether this is a blood test or an imaging scan or stress test, all tests have some flaws. I didn’t understand this when I started medical school. I assumed that tests were either positive or negative. There were no gray areas. I have since learned that the accuracy of tests can vary greatly, and we use sensitivity and specificity to determine that accuracy. 

The concept of sensitivity and specificity of testing is one of the most important lessons that I learned in medical school. Unfortunately, I believe it’s a concept that doctors don’t properly explain to patients. As a Wise Patient, you should understand how sensitivity and specificity can affect the way we interpret test results. 

Sensitivity is the ability of a test to detect a disease. A highly sensitive test will be really good at finding disease that would have been missed by a test with low sensitivity. For example, when looking for a brain tumor, an x-ray of your skull would be considered to have low sensitivity. This means that even if you have a brain tumor, the x-ray would not likely show it. As you can see, this means that an x-ray of your skull is rather useless when looking for a brain tumor. An MRI with contrast, however, is a highly sensitive test. This means that if you have a brain tumor the MRI with contrast is very likely to detect that disease. For more information on imaging modalities that we use to diagnose diseases, check out my article: Imaging Modalities

Specificity is the ability of a negative test to determine that you don’t have a disease. There are lots of tests that can be positive when you do not have disease. These tests have low specificity. A good example of a highly sensitive test with low specificity is the anti-nuclear antibody (ANA). The ANA is a blood test that my wife, a rheumatologist, uses all the time. The test looks for the presence of an antibody in your bloodstream that is associated with autoimmune diseases, like lupus. The problem with the ANA test is that up to 10% or more of the normal, healthy population has a positive ANA, but only a tiny percentage have autoimmune disease. You may wonder how a test like this is even useful. The answer is that the ANA has a great negative predictive value, meaning if the test is negative, then it is extremely unlikely that you have an autoimmune disease such as lupus. 

We use lots of other statistics when interpreting data, like positive predictive value, negative predictive value, likelihood ratios. Doctors get a lot of training to determine what tests are useful and give us the best information. We use sensitivity and specificity as part of that equation. Knowing the basics of sensitivity and specificity is important and can help you understand why your doctor makes the decision she/he makes based off of certain test results. If you are curious about how to interpret a test result, don’t hesitate to ask your doctor. They may not know the exact percentages, but that dialogue may help you to understand each other’s thought process a little better.