Medical Examples
In medical diagnostics, test sensitivity is the ability of a test to correctly identify those with the disease (true positive rate), whereas test specificity is the ability of the test to correctly identify those without the disease (true negative rate).
If 100 patients known to have a disease were tested, and 43 test positive, then the test has 43% sensitivity. If 100 with no disease are tested and 96 return a negative result, then the test has 96% specificity. Sensitivity and specificity are prevalence-independent test characteristics, as their values are intrinsic to the test and do not depend on the disease prevalence in the population of interest.
A highly specific test is unlikely to give a false positive result: a positive result should thus be regarded as a true positive. A sign or symptom with very high specificity is often termed pathognomonic. An example of such a test is the inspection for erythema chronicum migrans to diagnose lyme disease. In contrast, a sensitive test rarely misses a condition, so a negative result should be reassuring (the disease tested for is absent). A sign or symptom with very high sensitivity is often termed sine qua non. An example of such test is a genetic test to find an underlying mutation in certain types of hereditary colon cancer.
SPIN and SNOUT are commonly used mnemonics which says: A highly SPecific test, when Positive, rules IN disease (SP-P-IN), and a highly 'SeNsitive' test, when Negative rules OUT disease (SN-N-OUT).
Read more about this topic: Sensitivity And Specificity
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