What happens to NPV when disease prevalence decreases?

What happens to NPV when disease prevalence decreases?

• A. NPV decreases
• B. NPV increases
• C. No change
• D. Depends on sensitivity

Answer: (B)

Lower disease prevalence increases the negative predictive value. NPV is the probability that a negative test truly means you don’t have the disease. With fixed test performance (sensitivity and specificity), when the disease is rarer (prevalence falls), the pool of people without disease grows relative to those with disease. This makes a negative result more likely to be a true negative, so NPV rises. The formula NPV = [Specificity × (1 − Prevalence)] / [Specificity × (1 − Prevalence) + (1 − Sensitivity) × Prevalence] shows that as prevalence decreases, the numerator and overall value of NPV increase. In practical terms, when disease is uncommon, a negative result is generally more trustworthy.

Lower disease prevalence increases the negative predictive value. NPV is the probability that a negative test truly means you don’t have the disease. With fixed test performance (sensitivity and specificity), when the disease is rarer (prevalence falls), the pool of people without disease grows relative to those with disease. This makes a negative result more likely to be a true negative, so NPV rises. The formula NPV = [Specificity × (1 − Prevalence)] / [Specificity × (1 − Prevalence) + (1 − Sensitivity) × Prevalence] shows that as prevalence decreases, the numerator and overall value of NPV increase. In practical terms, when disease is uncommon, a negative result is generally more trustworthy.