**Question:** All comprise inherent properties of a screening test except-

A. Sensitivity
B. Specificity
C. Positive Predictive Value (PPV)
D. Negative Predictive Value (NPV)

**Core Concept:** A screening test is a diagnostic tool used to identify individuals with an unknown or asymptomatic condition. The inherent properties of a screening test are Sensitivity, Specificity, PPV, and NPV. Sensitivity represents the proportion of true positive results to all actual positive cases. Specificity is the proportion of true negative results to all actual negative cases. PPV is the probability that a person with a positive test result actually has the disease, while NPV is the probability that a person with a negative test result does not have the disease.

**Why the Correct Answer is Right:** Option C (Positive Predictive Value) and D (Negative Predictive Value) are not inherent properties of a screening test. PPV and NPV depend on the prevalence of the disease in the population being tested, not the test itself. A screening test's PPV is calculated by multiplying its Sensitivity and Prevalence, while NPV is calculated by multiplying the Specificity and Prevalence.

**Why Each Wrong Option is Incorrect:**

A. Sensitivity and Specificity are essential to evaluate the performance of a screening test as they represent the test's ability to correctly identify positive and negative cases, respectively.

B. Negative Predictive Value (NPV) is the probability that a person with a negative test result does not have the disease. It depends on the prevalence of the disease in the population being tested.

C. Positive Predictive Value (PPV) is the probability that a person with a positive test result actually has the disease. It depends on the prevalence of the disease in the population being tested.

**Clinical Pearl:** When interpreting a screening test result, it is essential to consider the prevalence of the disease in the population being tested. A high prevalence increases PPV, indicating a higher probability of the disease in those with a positive test result. Conversely, a low prevalence increases the risk of false positives, making PPV low. Similarly, a high prevalence increases NPV, indicating a lower probability of the disease in those with a negative test result. A low prevalence increases the risk of false negatives, making NPV high. Understanding these values helps in making informed decisions about further diagnostic testing and treatment.