Post-test probability
Post-test probability (pronounced: post-test pro-ba-bi-li-ty) is a term used in medical statistics and diagnostic testing. It refers to the probability that a person has a disease or condition after the test results are known.
Etymology
The term "post-test probability" is derived from the English words "post" meaning after, "test" referring to a medical examination, and "probability" indicating the likelihood of an event occurring.
Definition
Post-test probability is the revised probability of having a disease after a diagnostic test has been performed. It is based on the pre-test probability and the result of the test. The pre-test probability is the initial assessment of the likelihood of the disease before the test is done. The post-test probability is calculated using Bayes' theorem, a fundamental theorem in probability theory and statistics that describes how to update or revise probabilities based on new data.
Related Terms
- Pre-test probability: The probability of a patient having a disease before a test is performed.
- Sensitivity (tests): The ability of a test to correctly identify those with the disease.
- Specificity (tests): The ability of a test to correctly identify those without the disease.
- Positive predictive value: The probability that subjects with a positive screening test truly have the disease.
- Negative predictive value: The probability that subjects with a negative screening test truly don't have the disease.
- Likelihood ratios in diagnostic testing: The likelihood that a given test result would be expected in a patient with the target disorder compared to the likelihood that that same result would be expected in a patient without the target disorder.
See Also
External links
- Medical encyclopedia article on Post-test probability
- Wikipedia's article - Post-test probability
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