Course transcript - Northwest Center for Public Health Practice

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Screening in Public Health PracticeTranscript110 false positives from the total of 580 subjects without colon cancer—leaving uswith 470 true negatives.We know that sensitivity is defined as the number of true positives divided by thenumber of true positives plus false negatives. For the fecal occult blood test exampleshown here, sensitivity is calculated as the 90 true positives divided by the 90 truepositives plus the 30 false negatives—or 90 divided by 120—which equals 75%.This means that, for people who have colon cancer, 75% will have positive fecaloccult blood test results when screened. The screening test picks up the cancer 75%of the time. The higher the sensitivity, the less likely it is that there will be false negativetests.Let’s pause now while you answer some questions on what you have just learned.Exercise 3SpecificityNow let’s take a look at the specificity of the screeningtest. While sensitivity is looking for the number of truepositives, specificity focuses on the number of true negatives.Specificity is calculated by dividing the number oftrue negatives by the number of true negatives added tothe number of false positives. The result of the calculationis the likelihood that a screening test will be negative if theperson truly does not have the disease.What do we use specificity for? Similar to sensitivity, weuse it to help us determine whether this is a good test—should we use this test to screen for a certain disease inour population or might another test be more accurate?Let’s make this a little more practical by returning to ourcolon cancer and fecal occult blood test example.Example: Specificity of FOBTLooking at this table of the test results that we filled inearlier, let’s calculate the specificity. There were 470 truenegatives, so we take that number and divide it by thecombination of true negatives and false positives. Thisleaves us with 470 divided by 580, or 81%. Our interpretationof this is that for people who do not have coloncancer, 81% will have negative fecal occult blood testresults when screened. The higher the specificity, theless likely it is that there will be false positive tests. HighNorthwest Center for Public Health Practice 14
Screening in Public Health PracticeTranscriptspecificity might be particularly important when screening for a disease that requirescostly, invasive, or risky follow-up tests of individuals who screen positive—such ascolonoscopies to follow up for colon cancer. In that situation you might not wantto subject a large number of people without the disease (the false positives) to thefollow-up tests. Let’s pause now while you answer some questions on what you’vejust learned.Exercise 4Predictive Value of a Positive TestThe final two characteristics of screening tests that we’llconsider involve the test’s predictive value. The predictivevalue of a test depends on how good the test is (the sensitivityand specificity) and how common the disease beingscreened for is in the population being screened.Let’s start by talking about the predictive value of apositive test. This answers the question—among all peoplewho test positive on the screening test, what proportionreally have the disease? Or, on an individual level: If I testpositive on the screening test, what’s the likelihood that Ireally have this disease? To calculate the positive predictivevalue of a test, we divide the number of true positives by the number of truepositives combined with the number of false positives.This concept is an important one for public health professionals designing screeningprograms, as we’ll discuss in a bit. It is helpful for deciding which subset of thepopulation should be screened, and knowing the predictive value in the populationthat has been screened helps us interpret test results for screenees. For this is thequestion that people who test positive on a screening test usually ask; for instance,after being told of a positive Pap smear, a woman may ask “How likely is it that Ihave cervical cancer?” The predictive value of a positivetest answers that question. Let’s calculate the answer,using our previous example.Example: Positive Predictive ValueReturning again to our example of fecal occult blood tests,how would we calculate the predictive value of this test?In the population in this example, there are 90 truepositives—those who were correctly identified from thescreening test as having cancer, and 110 false positives—those who were incorrectly identified from the screeningtest as having cancer. The equation for the positiveNorthwest Center for Public Health Practice 15
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Course transcript - Northwest Center for Public Health Practice

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