What is known as the proportion of negative test results that are true negatives?

The concept being referred to is the negative predictive value, which is a key measure in diagnostic testing. Negative predictive value indicates the likelihood that individuals who test negative for a disease actually do not have the disease. In other words, it reflects the proportion of true negative test results out of all negative test results.

Understanding negative predictive value is crucial in clinical practice, especially when evaluating the effectiveness of screening tests. A high negative predictive value means that the test is reliable in ruling out the disease when the result is negative, which can be particularly important in high-stakes situations.

In contrast, the other options do not pertain to the proportion of true negatives in this manner. Positive predictive value measures the proportion of true positives among all positive results, prevalence refers to the proportion of a population that has a particular disease at a given time, and the case-fatality rate is a measure of the severity of a disease, reflecting the proportion of cases that result in death. Each of these measures serves different purposes in epidemiology and clinical evaluation, but for assessing the reliability of negative test results specifically, negative predictive value is the appropriate concept.