Regarding positive predictive value (PPV) and negative predictive value (NPV) in diagnostic test evaluation, all of the following statements are correct EXCEPT:
A. NPV is independent of disease prevalence and depends only on test sensitivity and specificity
B. A test with high sensitivity is useful for ruling out disease when the result is negative
C. PPV and NPV are post-test probabilities that depend on both test characteristics and disease prevalence
D. PPV increases when disease prevalence in the population increases
Explanation
Concept Overview
Key Point
PPV and NPV are post-test probabilities that are fundamentally dependent on disease prevalence in the population being tested. Unlike sensitivity and specificity (which are intrinsic test properties), PPV and NPV change with prevalence.
Analysis of Each Statement
Statement 1: PPV increases with prevalence — CORRECT
PPV = TP+FPTP
When prevalence increases, the number of true positives increases relative to false positives, causing PPV to rise. This is a direct mathematical relationship.
Clinical Pearl
A test with 95% specificity will have much higher PPV in a high-prevalence setting (e.g., screening symptomatic patients) than in a low-prevalence setting (e.g., screening asymptomatic populations).
Statement 2: NPV is independent of prevalence — INCORRECT
This is the trap answer. NPV is NOT independent of prevalence.
NPV = TN+FNTN
NPV depends on:
Test sensitivity (affects FN)
Test specificity (affects TN)
Disease prevalence (affects the ratio of TN to FN)
When prevalence decreases, there are more true negatives and fewer false negatives, so NPV increases. NPV is therefore highly dependent on prevalence.
High-YieldNEET PG
This is a common misconception in exam questions. Students often confuse the independence of sensitivity/specificity from prevalence with the independence of NPV/PPV — they are NOT the same.
Statement 3: High sensitivity useful for ruling out disease — CORRECT
A test with high sensitivity has a low false-negative rate.
Mnemonic
SnNout — Snensitivity rules Negative out. When a highly sensitive test is negative, disease is ruled out.
Statement 4: PPV and NPV are post-test probabilities — CORRECT
Both PPV and NPV are post-test probabilities that incorporate:
Pre-test probability (disease prevalence)
Test sensitivity and specificity
Summary Table
Table
Parameter
Depends on Prevalence?
Depends on Sensitivity?
Depends on Specificity?
Sensitivity
No
—
No
Specificity
No
No
—
PPV
Yes
Yes
Yes
NPV
Yes
Yes
Yes
Park 26e Ch 10
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