Case 1: Mr. Jones is a 51-year-old male who comes to your office for a screening colonoscopy. He tells you that he had a friend who had a colon perforation from a colonoscopy and he is reluctant to undergo one himself. He has heard that there is a new blood test for colon cancer and asks you why he can’t have this instead. You do a quick search for this test and learn that it has low sensitivity but high specificity.
Case 2: Mrs. Smith has been on a therapeutic heparin drip with a goal partial thromboplastin time (PTT) of 60 to 80. For the last 3 lab draws, her values have been 70, 73, and 69. Because her PTT has been at goal, you have not changed the rate of her drip. On her next set of labs her PTT suddenly becomes 133.
Case 3: Jane Doe has a urine specimen with the following results:
- 2 to 3 white blood cells
- 50,000 bacteria per high-power field
- Negative nitrite
- Negative leukocyte esterase
- Multiple squamous epithelial cells
1. Should you order this new blood test for Mr. Jones?
2. What is the next step in evaluating Mrs. Smith’s newly elevated PTT?
Doctors spend a significant portion of their time ordering and interpreting various lab tests, but knowing when and which test to order is not always easy. As a general rule with any diagnostic testing, it is important to ask the following questions: “What am I looking for?” and “How will the results change the management of this patient?” The sensitivity, specificity, positive predictive value, and negative predictive values are all critical statistics that help you determine the answers to those questions (Table 13-1).
Table 13-1. Calculations of Predictive Value, Sensitivity, and Specificity |Favorite Table|Download (.pdf)
Table 13-1. Calculations of Predictive Value, Sensitivity, and Specificity
|Test Result||Disease||No Disease|
|Positive||A (true-positive)||B (false-positive)||Positive predictive value (PPV) = A/A + B|
|Negative||C (false-negative)||D (true-negative)||Negative predictive value (NPV) = D/C + D|
|Sensitivity = A/A + C||Specificity = D/B + D|
It should be noted that the positive predictive value and negative predictive values will be affected by the prevalence of the condition. Hence, when ordering tests for something very rare, the likelihood of a false test goes up. This is demonstrated in Table 13-2, where for the same specificity and sensitivity the positive predictive value increases dramatically as the disease prevalence goes from 2% in Table 13-2A to 20% in Table 13-2B. Awareness of such principles will maximize your likelihood of testing your patients appropriately.
Table 13-2. Effect of Disease Prevalence on Positive and Negative ...