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Difficulty: EasyDiagnostic and Screening Test Performance

An infectious disease clinic routinely screens its patients for *Neisseria gonorrhoeae* using a specific nucleic acid amplification assay. In this high-risk patient cohort, the disease prevalence is 18%18\%. The assay correctly identifies 94%94\% of patients who have the infection and correctly identifies 98%98\% of patients who are disease-free. A nearby university student health center recently adopted this identical assay to screen all incoming freshmen during orientation, a demographic with an estimated disease prevalence of 0.5%0.5\%. When applying this assay in the university setting rather than the infectious disease clinic, which of the following describes the expected changes in the test's performance characteristics?

  1. The probability of a true infection given a positive result will decrease, and the probability of a true absence of infection given a negative result will increase.Answer
  2. B
    The probability of a true infection given a positive result will increase, and the probability of a true absence of infection given a negative result will decrease.
  3. C
    The probabilities of a true infection given a positive result and a true absence of infection given a negative result will both decrease.
  4. D
    The probabilities of a true infection given a positive result and a true absence of infection given a negative result will both increase.
  5. E
    The probabilities of a true infection given a positive result and a true absence of infection given a negative result will remain unchanged.

Answer

The probability of a true infection given a positive result will decrease, and the probability of a true absence of infection given a negative result will increase.
The scenario describes implementing a diagnostic test in a lower-prevalence population (0.5%0.5\%) compared to its original high-prevalence setting (18%18\%). The probability that a positive test indicates a true infection is the Positive Predictive Value (PPV), which is directly proportional to disease prevalence. As prevalence drops, the ratio of false positives to true positives increases, causing the PPV to decrease. The probability that a negative test indicates a true absence of infection is the Negative Predictive Value (NPV), which is inversely proportional to disease prevalence. As prevalence drops, there are fewer actual disease cases in the pool of patients, making a negative result more reliable and causing the NPV to increase. The intrinsic properties of the test (identifying 94%94\% of diseased and 98%98\% of disease-free individuals) do not change.

Step-by-Step Solution

1
Identify the change in the clinical scenario.
The disease prevalence drops significantly from 18%18\% in the infectious disease clinic to 0.5%0.5\% in the university setting.
Understanding the shift in pre-test probability (prevalence) is essential for predicting how the test's performance metrics will behave in practice.
2
Determine the effect of decreased prevalence on the probability of a true infection given a positive result.
This probability represents the Positive Predictive Value (PPV). Because PPV is directly proportional to prevalence, a massive drop in prevalence means a higher proportion of positive test results will be false positives. Therefore, the PPV will decrease.
This establishes the first part of the correct conclusion based on fundamental epidemiological principles.
3
Determine the effect of decreased prevalence on the probability of a true absence of infection given a negative result.
This probability represents the Negative Predictive Value (NPV). NPV is inversely proportional to prevalence. With fewer actual disease cases in the population, a negative result becomes much more reliable. Therefore, the NPV will increase.
This confirms the second half of the correct conclusion.

Key Concept

The dependence of predictive values on disease prevalence.
Estimated Time:45s
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Topics

Diagnostic and Screening Test Performance

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