Question:medium
The diagnostic power of a test to correctly diagnose a disease (the proportion of positive test results that truly have the disease) is:
The diagnostic power of a test to correctly diagnose a disease (the proportion of positive test results that truly have the disease) is:
Show Hint
Among those who test positive, how many truly have the disease?
Updated On: Jun 23, 2026
- Negative predictive value
- Positive predictive value
- Sensitivity
- Specificity
Show Solution
The Correct Option is B
Solution and Explanation
Step 1: The phrase to lock onto is correctly diagnosing the disease among those who test positive. That is exactly the definition of positive predictive value, $PPV = \frac{TP}{TP + FP}$.
Step 2: Its mirror image is negative predictive value, $NPV = \frac{TN}{TN + FN}$, which describes how well a negative test rules disease out.
Step 3: Sensitivity and specificity are intrinsic test properties measured against disease status - sensitivity catches the diseased, specificity clears the healthy - so they are not what the stem asks. The predictive (post-test) quantity for a positive result is PPV.
\[\boxed{\text{Positive predictive value}}\]
Step 2: Its mirror image is negative predictive value, $NPV = \frac{TN}{TN + FN}$, which describes how well a negative test rules disease out.
Step 3: Sensitivity and specificity are intrinsic test properties measured against disease status - sensitivity catches the diseased, specificity clears the healthy - so they are not what the stem asks. The predictive (post-test) quantity for a positive result is PPV.
\[\boxed{\text{Positive predictive value}}\]
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