A study is conducted to evaluate the properties of a new test for diagnosing ovarian cancer. The study enrolled 200 patients who truly have ovarian cancer and 300 patients who truly do not. Study results showed that the test is 80% sensitive and 70% specific. Based on this information, which of the following is the approximate number of false negative test results found in this study?

Question

A study is conducted to evaluate the properties of a new test for diagnosing ovarian cancer.  The study enrolled 200 patients who truly have ovarian cancer and 300 patients who truly do not.  Study results showed that the test is 80% sensitive and 70% specific.  Based on this information, which of the following is the approximate number of false negative test results found in this study?

Quizplus · Accepted Answer

11ec160b_3727_5ad9_9249_e31919d2b0d4_MD0001_00 Of the individuals who truly have a disease (ie, "positive condition" in the 2 × 2 table), some will have a positive test result for the disease (ie, true positive [TP]) whereas others will have a negative test result despite truly having the disease (ie, false negative [FN]). The number of FN is equal to the number of individuals who truly have the disease (ie, TP + FN) minus the number of TP: FN = (TP + FN) − TP Given that 200 patients truly have ovarian cancer ("positive condition"), this means that (TP + FN) = 200. To calculate TP (and subsequently determine FN), it is possible to use the sensitivity of the test (ie, a test's ability to correctly identify individuals with the disease), given by: Sensitivity = TP / (TP + FN) In this case, the sensitivity of the test is TP / (TP + FN) = 80% (or 0.80). Using this information, the number of TPs can be calculated: Sensitivity = TP / (TP + FN) 0.80 = TP / 200 TP = 160 Now the number of FN can be determined: FN = (TP + FN) − TP = 200 − 160 = 40 The number of TP and FN can be more quickly calculated using the following equations: TP = (Sensitivity) × (Number of patients who truly have the disease) FN = (1 − Sensitivity) × (Number of patients who truly have the disease) (Choices B, C, and E) 90 is the number of false positives (FP), 160 is the number of TP, and 210 is the number of true negatives (TN) found in the study. (Choice D) 200 is the number of individuals who truly have ovarian cancer (ie, TP + FN) in the study. Educational objective: False negatives (FN) refer to individuals who test negative for a disease but who truly have the disease. The number of FN can be calculated using the number of individuals who truly have the disease and the sensitivity of the test, or by using the formula: FN = (1 − Sensitivity) × (Number of patients who truly have the disease).

A Study Is Conducted to Evaluate the Properties of a New