What does negative predictive value indicate?

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Multiple Choice

What does negative predictive value indicate?

Explanation:
Negative predictive value is the probability that a person does not have the disease given a negative test result. It is calculated as the number of true negatives divided by all negative test results (true negatives plus false negatives). This tells you, among those who test negative, how confident you can be that they are actually disease-free. It depends on how common the disease is in the population and on the test’s accuracy, especially its sensitivity and specificity. In practice, a high NPV means a negative result is reassuring that the person doesn’t have the disease, while a low NPV means a negative result may miss some cases. The other ideas refer to different metrics: the probability a positive result is a true disease (positive predictive value) and how often the test misses disease among those who have it (false negative rate, linked to sensitivity).

Negative predictive value is the probability that a person does not have the disease given a negative test result. It is calculated as the number of true negatives divided by all negative test results (true negatives plus false negatives). This tells you, among those who test negative, how confident you can be that they are actually disease-free. It depends on how common the disease is in the population and on the test’s accuracy, especially its sensitivity and specificity. In practice, a high NPV means a negative result is reassuring that the person doesn’t have the disease, while a low NPV means a negative result may miss some cases. The other ideas refer to different metrics: the probability a positive result is a true disease (positive predictive value) and how often the test misses disease among those who have it (false negative rate, linked to sensitivity).

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