American Board of Surgery Qualifying Exam (ABS QE) Practice Test

What does Positive Predictive Value (PPV) measure?

1. The probability that a positive test result truly indicates disease presence

2. The ability of a test to correctly identify those without the disease

3. The proportion of true negatives among total negative tests

4. The overall accuracy of a screening test regardless of results

The correct answer is: The probability that a positive test result truly indicates disease presence

Positive Predictive Value (PPV) measures the probability that a positive test result truly indicates the presence of the disease. It is calculated as the number of true positive results divided by the total number of positive test results (true positives plus false positives). This metric is crucial in clinical practice because it helps healthcare providers understand the likelihood that a patient who tests positive actually has the condition. A high PPV indicates that the test is reliable for diagnosing the disease, which is particularly important in screening scenarios where making the right diagnosis can significantly affect patient outcomes. In contrast, the other options focus on different aspects of test performance metrics, such as sensitivity, specificity, and overall accuracy, rather than directly addressing what PPV signifies. For instance, the choice concerning the ability of a test to correctly identify those without the disease relates to Negative Predictive Value (NPV), while the proportion of true negatives is associated with specificity. Overall accuracy refers to the test's performance across all results, not specifically addressing the implications of positive results.