What does pretest probability describe?

• A. The likelihood of disease before testing based on history, exam, and risk factors.
• B. The probability after testing.
• C. The cost of testing.
• D. The probability of adverse drug reactions.

Answer: (A)

Pretest probability is the clinician’s estimate of how likely it is that a patient has a disease before any diagnostic test, and that estimate is guided by the history, the physical exam, and known risk factors. This starting point matters because it shapes both what tests you choose and how you interpret their results. Tests don’t speak in a vacuum—their results are weighed against what you already suspected1. For instance, if a patient has symptoms and risk factors that make a disease likely, the pretest probability is high, so a positive test strengthens the diagnosis more, while a negative test might still leave some doubt depending on the test’s accuracy. If the likelihood is low from the outset, a positive result may be more likely a false positive, and a negative result can effectively rule out disease given a good test. In short, the pretest probability is the initial likelihood of disease before testing, distinct from the post-test probability you get after the test results. The other options describe probabilities after testing or relate to costs or adverse effects, not the probability before testing.