Overview
This lecture explains the critical concepts of sensitivity and specificity in medical testing, focusing on understanding false negatives and false positives.
Sensitivity
- Sensitivity refers to a test's ability to correctly identify patients with a disease (true positives).
- High sensitivity means the test has no or very few false negatives.
- A false negative occurs when a person has the disease but the test results are negative.
- Example: Some autoimmune disease tests have low sensitivity, missing true cases.
Specificity
- Specificity refers to a test's ability to correctly identify patients without the disease (true negatives).
- High specificity means the test has no or very few false positives.
- A false positive occurs when a person does not have the disease but the test results are positive.
- Example: Mammograms with low specificity may incorrectly indicate cancer in healthy individuals.
Key Terms & Definitions
- Sensitivity — The likelihood that a test correctly identifies those with the disease (avoids false negatives).
- Specificity — The likelihood that a test correctly identifies those without the disease (avoids false positives).
- False Negative — When a disease is present but the test indicates absence.
- False Positive — When a disease is absent but the test indicates presence.
Action Items / Next Steps
- Review examples of diseases and diagnostic tests with varying sensitivity and specificity levels.
- Understand how false negatives and false positives impact patient care decisions.