Pre-test probability

Pre-test probability is a concept in medical diagnostic testing that refers to the probability of a patient having a certain disease or condition before a diagnostic test is conducted. It is an essential part of the Bayesian inference in medical decision making.

Overview

The pre-test probability of a disease is the likelihood that a patient has the disease before the diagnostic test results are known. It is based on the patient's medical history, physical examination, and the prevalence of the disease in the relevant population. The pre-test probability helps in interpreting the results of diagnostic tests and in deciding whether to order a test.

Calculation

The pre-test probability is usually expressed as a percentage. It can be calculated using various methods, including clinical prediction rules, which are based on the patient's history and physical examination findings, and the prevalence of the disease in the relevant population.

Importance

The pre-test probability is important because it affects the interpretation of diagnostic test results. A test with a high sensitivity and specificity may still have a low positive predictive value if the pre-test probability is low. Conversely, a test with low sensitivity and specificity may have a high positive predictive value if the pre-test probability is high.

See also

• Post-test probability
• Likelihood ratios in diagnostic testing
• Bayesian inference
• Evidence-based medicine

References

Pre-test probability Resources
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