Predictive values affected by prevalence vs Intrinsic test characteristics
How to tell Predictive values affected by prevalence and Intrinsic test characteristics apart when a board question makes them look alike.
Prevalence changes post-test probability, so PPV rises and NPV falls as prevalence increases; sensitivity and specificity stay intrinsic to the test because their formulas condition on disease status.
Side by side
PPV and NPV change when disease prevalence changes: higher prevalence raises PPV and lowers NPV; lower prevalence lowers PPV and raises NPV.
Sensitivity and specificity are intrinsic test characteristics and usually do not change just because prevalence changes.
Predictive values start from the tested population, so pretest probability changes the fraction of true positives among positives and true negatives among negatives.
Sensitivity and specificity condition on true disease status, so they describe the assay rather than the population prevalence.
High prevalence: PPV up, NPV down. Low prevalence: PPV down, NPV up.
Sensitivity = TP/(TP+FN); specificity = TN/(TN+FP); neither formula includes prevalence.
The trap
Low prevalence increases NPV; high prevalence increases PPV.
The repair move
Before naming the answer, force the stem through the separator: Low prevalence increases NPV; high prevalence increases PPV.
Try a free question
CoreA new screening test for ovarian cancer has SENSITIVITY 90% and SPECIFICITY 85%. When the test is moved from a high-risk population (prevalence 15%) to a general screening population (prevalence 1%), which property of the test changes the most?
Show answer and explanation
Answer: A. Positive predictive value (PPV) decreases as prevalence drops. PPV depends on PREVALENCE. At LOW prevalence, even with high sensitivity and specificity, false positives outnumber true positives, dropping PPV. Sensitivity and specificity are INTRINSIC to the test and don't change with prevalence (their formulas condition on disease status). NPV behaves oppositely: it rises as prevalence falls.
Why the other choices are tempting
- B. Sensitivity is intrinsic and unchanged by prevalence.
- C. Specificity is intrinsic and unchanged by prevalence.
- D. Both stay the same.
- E. Test validity (sensitivity and specificity) is unchanged; only the predictive values change with population.
Flashcards
Tap a card to flip it.
What clue supports Negative predictive value?
Choose Negative predictive value when the stem gives this pattern: Negative predictive value is probability of no disease after a negative test and is highest when prevalence is low.
What clue supports Positive predictive value with prevalence?
Choose Positive predictive value with prevalence when the stem gives this contrasting pattern: Positive predictive value is probability of disease after a positive test and rises when prevalence is high.
Quick answers
What is the fastest way to tell Predictive values affected by prevalence from Intrinsic test characteristics?
Prevalence changes post-test probability, so PPV rises and NPV falls as prevalence increases; sensitivity and specificity stay intrinsic to the test because their formulas condition on disease status.
What is the key clue for Predictive values affected by prevalence?
PPV and NPV change when disease prevalence changes: higher prevalence raises PPV and lowers NPV; lower prevalence lowers PPV and raises NPV.
What is the key clue for Intrinsic test characteristics?
Sensitivity and specificity are intrinsic test characteristics and usually do not change just because prevalence changes.
What is the common trap with Predictive values affected by prevalence vs Intrinsic test characteristics?
Low prevalence increases NPV; high prevalence increases PPV.