A study is conducted to assess whether quantitative measurement of heat shock protein 90 alpha (Hsp90α) in plasma can improve diagnostic accuracy and help monitor treatment response in liver cancer patients. A total of 300 individuals (100 liver cancer patients and 200 healthy controls) participate in the study. Analyses reveal that 90 of the liver cancer patients have an abnormally high plasma Hsp90α level and that 12 of the healthy controls have an abnormally high plasma Hsp90α level. An abnormally high plasma Hsp90α level indicates a positive test for liver cancer. Which of the following values best represents the specificity of this test?

Question

A study is conducted to assess whether quantitative measurement of heat shock protein 90 alpha (Hsp90α) in plasma can improve diagnostic accuracy and help monitor treatment response in liver cancer patients.  A total of 300 individuals (100 liver cancer patients and 200 healthy controls) participate in the study.  Analyses reveal that 90 of the liver cancer patients have an abnormally high plasma Hsp90α level and that 12 of the healthy controls have an abnormally high plasma Hsp90α level.  An abnormally high plasma Hsp90α level indicates a positive test for liver cancer.  Which of the following values best represents the specificity of this test?

Quizplus · Accepted Answer

11ec160b_3722_c6e7_9249_919391c0501c_MD0001_00 The specificity of a test refers to its ability to correctly identify individuals without the disease. Specificity is equal to the number of individuals who do not have the disease and who test negative (true negatives [TN]) divided by the total number of individuals without the disease (TN + false positives [FP]): Specificity = TN / (TN + FP) In this example, 12 out of 200 healthy controls had an abnormally high plasma heat shock protein 90 alpha (Hsp90α) level (ie, tested positive); therefore, FP = 12 and TN = 188 (ie, 200 − 12). Therefore, the specificity of the test is as follows: Specificity = TN / (TN + FP) = 188 / (188 + 12) = 188 / 200 = 0.94 (or 94%) (Choice A) In this example, 6% is the false positive rate (FPR): FPR = FP / (TN + FP) = 12 / (188 + 12) = 12 / 200 = 0.06 (or 6%). FPR is the probability of a positive test in a patient without the disease (ie, FP); it is also the complement to specificity (ie, FPR = 1 − specificity = 1 − 0.94 = 0.06). (Choices B and D) The sensitivity of a test refers to its ability to correctly identify individuals with the disease. It is calculated as the number of individuals who have the disease and who test positive (true positives [TP]) divided by the total number of individuals with the disease (TP + false negatives [FN]): sensitivity = TP / (TP + FN). In this example, 90 of 100 liver cancer patients had an abnormally high plasma Hsp90α level (ie, tested positive); therefore, TP = 90 and FN = 10 (ie, 100 − 90). Accordingly, the sensitivity of the test is 90 / (90 + 10) = 90 / 100 = 0.90 (or 90%). Sensitivity is related to the false negative rate (FNR): FNR = 1 - sensitivity. FNR is the probability of a negative test result in a patient with the disease (ie, FN): FNR = FN / (TP + FN) = 10 / (10 + 90) = 10 / 100 = 0.10 (or 10%). (Choice C) In this example, 33% represents the proportion of study participants with liver cancer: 100 liver cancer patients / (100 liver cancer patients + 200 health controls) = 0.333 (or 33.3%). Educational objective: The specificity of a test is its ability to correctly identify individuals without the disease. Specificity can be calculated as follows: Specificity = True negatives / (True negatives + False positives)

A Study Is Conducted to Assess Whether Quantitative Measurement of Heat