Sensitivity and Specificity

Sensitivity and specificity are two fundamental concepts in medical statistics that are used to assess the performance of diagnostic tests. They provide crucial information about the accuracy of a test in detecting the presence or absence of a specific disease or condition.

Sensitivity

Sensitivity refers to the proportion of individuals with the disease who test positive for the disease. It represents the ability of a test to correctly identify true positives. A high sensitivity indicates that the test is effective in detecting the disease when it is present. For example, if a test for tuberculosis has a sensitivity of 95%, it means that 95 out of 100 people with tuberculosis will test positive for the disease.

Specificity

Specificity refers to the proportion of individuals without the disease who test negative for the disease. It represents the ability of a test to correctly identify true negatives. A high specificity indicates that the test is effective in ruling out the disease when it is not present. For example, if a test for hepatitis C has a specificity of 98%, it means that 98 out of 100 people without hepatitis C will test negative for the disease.

Let us recap some key terms...