positive predictive value and negative predictive value study outcomes mini-presentation created by...
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![Page 1: Positive Predictive Value and Negative Predictive Value Study Outcomes Mini-Presentation Created by Thomas Hahn, MD Edited by John Kloke, PhD](https://reader036.vdocument.in/reader036/viewer/2022062518/5697bf831a28abf838c863c7/html5/thumbnails/1.jpg)
Positive Predictive Valueand
Negative Predictive Value
Study Outcomes Mini-PresentationCreated by Thomas Hahn, MD
Edited by John Kloke, PhD
![Page 2: Positive Predictive Value and Negative Predictive Value Study Outcomes Mini-Presentation Created by Thomas Hahn, MD Edited by John Kloke, PhD](https://reader036.vdocument.in/reader036/viewer/2022062518/5697bf831a28abf838c863c7/html5/thumbnails/2.jpg)
ObjectivesFollowing this presentation, the learner will be
able to:Understand the concepts and calculations for
positive predictive value and negative predictiveApply PPV and NPV to patient careCommunicate PPV and NPV to patients
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UNDERSTAND the CONCEPT
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PPV and NPVPositive Predictive Value: Probability that
subjects with a positive test have the disease.
Negative Predictive Value: Probability that subjects with a negative test do not have the disease.
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Positive Predictive ValuePositive Predictive Value: Proportion of positive
test results that are true positives
PPV = True Positives x 100% All Positives
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Negative Predictive ValueNegative Predictive Value: Proportion of negative
test results that are true negatives
NPV = True Negatives x 100% All Negatives
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2x2 Table
a (true positive)
b(false positive, Type 1 error)
c(false negative,
Type 2 error)
d(true negative)
Disease Present No Disease
Positive Test
Negative Test
Sensitivity = a/(a+c) Specificity = d/(d+b)
PPV = a/(a+b)
NPV = d/(d+c)
PPV = true positives x100% NPV = true negatives x100% (true positives + false positives) (true negatives + false negatives)
You need to know these equations for boards!
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PPV/NPV CharacteristicsPredictive value is determined by the
sensitivity and specificity of a testSensitivity (low false negatives) NPVSpecificity (low false positives) PPV
Predictive value is determined by the prevalence of a disease in the populationPrevalence PPV, NPVPrevalence PPV, NPV
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Example of Effect of Prevalence on PPV/NPV
Hypothetically test 10 people for Lyme disease in Lyme, Connecticut (high prevalence) and Boise, Idaho (low prevalence)
Lyme, Connecticut9/10 positive tests. High likelihood that the tests
are truly positive (Prevalence PPV, NPV)
Boise, Idaho9/10 negative tests. High likelihood that the tests
are truly negative (Prevalence PPV, NPV)
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Predictive Value and Low Disease Prevalence
How can you increase predictive value of a test when there is a low preclinical disease prevalence?Example: Breast cancer Prevalence is low in the population (about 1% in
2012)To increase PPV, target screening to those at
highest risk of developing the disease: women > 50 years old
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PPV/NPV vs Sensitivity/Specificity
Sensitivity and specificityFocus on the disease Important to epidemiologists and clinicians
Positive and negative predictive valuesFocus on the test Important to patients
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2x2 Table
a (true positive)
b(false positive, Type 1 error)
c(false negative,
Type 2 error)
d(true negative)
Disease Present No Disease
Positive Test
Negative Test
Sensitivity = true positives Specificity = true negatives all with disease all without disease
PPV = true positives all positives
NPV = true negatives
all negatives
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APPLY the OUTCOME
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Using Predictive ValueA PPV helps to answer the question: “If the
patient’s test is positive, what are the chances that the patient has the disease?”
Predictive values may make more sense to the patient than sensitivity/specificityExplains how many people with a positive test are
truly positive vs how many people with the disease will test positive.
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Application ExampleThe negative predictive value of a screening test
for Lyme disease is 50%? What does this mean?This is not a good test for ruling out Lyme disease.
50% of people with a negative test will actually have Lyme disease!!!
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COMMUNICATE the DATA
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Communicating to Patients
A patient presents with a tick bite, and you decide to test for Lyme disease using a new serum test. The patient asks you, “How good is this test?” Knowing that the PPV is 85%, how do you answer this question?“If your test is positive, there is an 85% chance
that you have the disease.” (test is 85% accurate)“Out of all the positive tests, 85% will be correct.”“If 100 people have a positive test, 85 of those will
have the disease and 15 will not have the disease.”
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Practice QuestionA study evaluating a two-tier screening test for
Lyme disease in a low prevalence area tested 4723 patients for Lyme disease. Of the patients who had positive tests, 12 had Lyme disease and 58 did not have Lyme disease. What is the positive predictive value of the test in this low prevalence area?A. 17%B. 20% C. 1% D. 15%
Disease No Disease
Positive Test 12 58
Negative Test 0 4653
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Practice QuestionA study evaluating a two-tier screening test for
Lyme disease in a low prevalence area tested 4723 patients for Lyme disease. Of the patients who had positive tests, 12 had Lyme disease and 58 did not have Lyme disease. What is the positive predictive value of the test in this low prevalence area?A. 17% (12/70 = PPV)B. 20% (12/58)C. 1% (70/4653)D. 15% Disease No Disease
Positive Test 12 58
Negative Test 0 4653
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The worst predictive value?
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ReferencesAAFP Family Medicine Board Review Course
http://www.ncbi.nlm.nih.gov/pubmed/26195017