Epidemiology: Practice Question

Specificity — Correct answer

Specificity (the true negative rate) is a measure of a test's ability to exclude a condition correctly, in other words, specificity measures the ability of a test to correctly identify all the negative cases out of all the actual negative cases. It tells us how well the test can rule out individuals who do not have the condition. A high specificity indicates that the test is good at correctly identifying individuals who do not have the condition, reducing the likelihood of unnecessary interventions for those who are healthy. A positive result in a test with high specificity is useful for "ruling in" disease, since the test rarely gives positive results in healthy patients. High specificity is good as a confirmatory test.

Specificity = (True Negatives) / (True Negatives + False Positives) = True Negatives / Total number of healthy people in the population

Sensitivity

Sensitivity (true positive rate) is a measure of a test's ability to identify a condition correctly - how frequently the test is positive in people with the disease. It measures the ability of a test or model to correctly identify all the positive cases out of all the actual positive cases. A high sensitivity indicates that the test is good at identifying individuals who truly have the condition, minimizing the chances of missing positive cases. It is most relevant in situations where failing to detect a positive case could have serious consequences. A negative result in a test with high sensitivity is be useful for "ruling out" disease because it rarely misdiagnoses cases in which patients have the disease.

Sensitivity = (True Positives) / (True Positives + False Negatives) = True Positives / Total number of sick people in the population

Positive predictive value

True positives / (True positives + False positives)

Negative predictive value

True negatives / (True negatives + False negatives)