Sensitivity is used to determine the proportion of actual positives which are correctly identified under a given set of assumptions.
Sensitivity is also called the true positive rate. It determines how different values of an independent variable will impact a particular dependent variable. Sensitivity is used to find out positive results out of the total results.
The sensitivity of a test can be written as:
Sensitivity = (Number of True Positives ) / Number of True positives + Number of False Positives
Sensitivity is prevalence-independent test characteristic, as its values are intrinsic to the test.
Sensitivity is used in Medical Treatment where it helps in identifying the diseases.
The understanding of the following terms is very important to determine the sensitivity in clinical test:
• True positive
o the test is positive and the patient has the disease
• False positive
o the test is positive but the patient does not have the disease.
• True negative
o the test is negative and the patient does not have the disease
• False negative
o the test is negative but still the patient has the disease
The sensitivity of a clinical test refers to the ability of the test to correctly identify those patients with the disease.
If the test has 100% sensitivity, it shows that all patients have diseases. If the test has 80% sensitivity, it shows 80% patients have diseases (True Positive) but 20% have no diseases (False Negative). If the disease is serious and treatable then higher sensitivity is important (e.g. cervical cancer).
Screening the female population by cervical smear testing is a sensitive test.