Sensitivity
Measure of the true-positive rate
Sensitivity is a psychometric measure that quantifies the rate of true positives to total positives2. Sensitivity can apply to clinical tests that output a binary result: Normal vs Abnormal
Calculation
Sensitivity quantifies true positive rate by finding the percent of people with disease who tested positive divided by total disease population.
| Disease Present | Disease Absent | Total | |
|---|---|---|---|
| Abnormal (positive) test result | A | B (false positives) | A + B |
| Normal (negative) test result | C (false negative) | D | C + D |
| Total | A + C | B + D | A + B + C + D |
\[ \textrm{Sensitivity} = \frac{(\textrm{True Positive})}{(\textrm{True Positive} + \textrm{False Negative})} = \frac{(\textrm{True Positive})}{(\textrm{Total Positive})} \]
Clinical Relevance
One should use sensitivity (and specificity) as a way to assess the performance of a diagnostic test2. To predict whether a particular person will truly have the disease based on a positive or negative test result, one should use Positive predicitve value (PPV) and Negative predictive value (NPV)2.