Question

A 35-year-old lady comes for a consultation. She is worried since both her parents are on treatment for diabetes. She seeks advice from you in taking care of her health.
How will you assess the performance of a screening test?

Hint:

Sensitivity and specificity are the most critical factors in assessing the effectiveness of a screening test. High sensitivity ensures that no cases are missed, while high specificity ensures that healthy individuals are not misdiagnosed.

Answer 1

The performance of a screening test is assessed by calculating sensitivity, specificity, PPV, NPV, and accuracy. These metrics help determine the reliability and effectiveness of a screening test in identifying both those with and without the disease.
The performance of a screening test can be assessed using the following metrics:

Step 1: Sensitivity
Sensitivity refers to the proportion of true positives correctly identified by the test. A high sensitivity test ensures that those who have the disease are correctly identified. It is calculated as: \[ \text{Sensitivity} = \frac{\text{True Positives}}{\text{True Positives + False Negatives}} \]

Step 2: Specificity
Specificity refers to the proportion of true negatives correctly identified by the test. A high specificity test reduces the number of healthy individuals who are wrongly diagnosed. It is calculated as: \[ \text{Specificity} = \frac{\text{True Negatives}}{\text{True Negatives + False Positives}} \]

Step 3: Positive Predictive Value (PPV)
PPV is the probability that a positive test result correctly indicates the presence of the disease. It is calculated as: \[ \text{PPV} = \frac{\text{True Positives}}{\text{True Positives + False Positives}} \]

Step 4: Negative Predictive Value (NPV)
NPV is the probability that a negative test result correctly indicates the absence of the disease. It is calculated as: \[ \text{NPV} = \frac{\text{True Negatives}}{\text{True Negatives + False Negatives}} \]

Step 5: Accuracy
Accuracy refers to the proportion of all true results (both positive and negative) in the total number of cases examined. It is calculated as: \[ \text{Accuracy} = \frac{\text{True Positives + True Negatives}}{\text{Total Population}} \]