Diagnostic Test Sensitivity

Diagnostic sensitivity measures how well a test identifies people who truly have an infection. It is the proportion of infected individuals, as determined by an appropriate reference standard, who obtain a positive test result. Thus, sensitivity represents the test's true-positive rate.

Calculation and interpretation

Sensitivity is calculated as true positives divided by true positives plus false negatives, or TP/(TP + FN). A sensitivity of 90% means that the test correctly detects 90 out of every 100 infected persons under the conditions evaluated.

• The complement of sensitivity is the false-negative rate, calculated as 1 minus sensitivity.
• Higher sensitivity means fewer infected individuals are missed by the test.

Distinction from related measures

Sensitivity concerns test results among people who are actually infected. It differs from specificity, which measures the proportion of uninfected people correctly testing negative, and from positive predictive value, which asks how many positive results represent true infection.

• A negative result from a highly sensitive test can help exclude infection, but it must be interpreted with clinical findings and disease probability.
• Diagnostic sensitivity should not be confused with analytical sensitivity, which concerns the smallest quantity of an analyte that a laboratory method can detect.

Public-health importance

Sensitivity is especially important when missed infections could delay treatment or permit transmission. However, increasing sensitivity may sometimes reduce specificity, so test thresholds must reflect the purpose of testing, such as screening or confirmation.