Test sensitivity

Test Sensitivity is a statistical measure in Epidemiology that quantifies the ability of a test to correctly identify those with a disease. It is also known as the true positive rate, hit rate, or recall.

Definition

Test sensitivity is defined as the proportion of true positive results (those with the disease who test positive) to the sum of true positive and false negative results (those with the disease who test negative). It is a measure of how well a test can identify true cases of a disease.

Calculation

The formula for calculating test sensitivity is:

Sensitivity = (Number of true positives) / (Number of true positives + Number of false negatives)

This formula gives the proportion of actual positives that are correctly identified as such.

Importance

Test sensitivity is important in determining the effectiveness of a diagnostic test. A test with high sensitivity is able to correctly identify a high proportion of true positive cases, reducing the likelihood of false negative results. This is particularly important in the early detection of diseases, where early treatment can significantly improve outcomes.

Limitations

While test sensitivity is a useful measure of a test's effectiveness, it does not provide a complete picture. It does not take into account false positive results (those without the disease who test positive), which are measured by Test specificity. A test with high sensitivity but low specificity can result in a high number of false positives, leading to unnecessary treatment and anxiety.

See also

• Test specificity
• Positive predictive value
• Negative predictive value
• Receiver operating characteristic

References

Test sensitivity Resources
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