A patient with suspected autoimmune thyroiditis undergoes a diagnostic test. The test correctly identifies 85% of individuals without the condition. Which of the following terms best describes the probability that a negative test result truly indicates the absence of autoimmune thyroiditis?

**B) Negative predictive value**

Negative predictive value is the probability that a negative test result truly indicates the absence of the disease. It is calculated as true negatives/(true negatives + false negatives). In this case, it represents the likelihood that a negative test accurately indicates the absence of autoimmune thyroiditis in the patient with suspected symptoms.

**Answer choice A:** False negative rate, is incorrect. The false negative rate is the proportion of individuals with the disease who receive a negative test result. It is calculated as false negatives/(false negatives + true positives).

**Answer choice C:** Positive predictive value, is incorrect. Positive predictive value is the probability that a positive test result truly indicates the presence of the disease. It is calculated as true positives/(true positives + false positives).

**Answer choice D:** Sensitivity, is incorrect. Sensitivity is the probability of a positive test result when the disease is present. It is calculated as true positives/(true positives + false negatives).

**Answer choice E:** Specificity, is incorrect. Specificity is the probability of a negative test result when the disease is absent. It is calculated as true negatives/(true negatives + false positives).

###### Key Learning Point

Negative predictive value is the probability that a negative test result truly indicates the absence of the disease. It is calculated as true negatives/(true negatives + false negatives). Negative predictive value is essential for understanding the reliability of a negative test result in ruling out a particular condition in a given patient.