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Principles and Predictive Value of Screening
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Objectives
• Discuss principles of screening• Describe elements of screening tests• Calculate sensitivity, specificity and
positive predictive value• Discuss how a clinician can make test
results more meaningful to the client• Explore factors that influence clinical
interpretation and explain how to individualize them for each client
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Screening
• Objective is to reduce mortality and morbidity with early detection
• Screening is the application of a test to people. It assist with early identification of a disease.
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Principles of Good Screening Programs
• Screen for health problems that– Are important to the individual and community– Have an acceptable form of treatment– Has a natural history that is adequately
understood– Has a recognizable latent or early
symptomatic stage– Has a suitable screening test – Is economically beneficial
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The Screening Test
• Ideally should be inexpensive, easy to administer (low risk) and with minimal discomfort
• There should be a Gold Standard based on the evidence
• Results should be accurate/valid and reliable/reproducible/precise
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Accurate/Valid
• Defined as:The degree to which a variable actually
represents what it is supposed to represent.
• Best way to assess– Compare with a reference
• Threatened by systematic error (bias)– Due to observer, subject and/or instrument
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Reliable/Precise
• Defined as– The degree to which a variable has nearly the
same value when measured several times
• Best way to assess– Repeated measures
• Threatened by random error– Due to observer, subject and/or instrument
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Predictive Value
• Is determined by Sensitivity, Specificity and the Prevalence of the disease
• Prevalence is defined as the number of patients per 100,000 population who have the disease at a given time
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SensitivityThe fraction of those with the disease correctly identified as positive by the test.
SpecificityThe fraction of those without the disease correctly identified as negative by the test.
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Positive predictive value (+ PV)
The fraction of peoplewith positive testswho actually have the condition.
Negative predictive value(-PV)
The fraction of peoplewith negative testswho actually don't havethe condition.
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The sensitivity and specificity are properties of the test. The positive and negative predictive values are properties of both the test and the
population you test. If you use a test in two populations with
different disease prevalence, the predictive values will be different. A screening test is most useful if directed to a high-risk population (high prevalence
and high predictive value).
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How to remember
Sensitivity: "I know my patient has the disease. What is the chance that the test will show that my patient has it?“
Specificity: "I know my patient doesn't have the disease. What is the chance that the test will show that my patient doesn't have it?"
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Cont.
+PV: “I just got a positive test result back on my patient. What is the chance that my patient actually has the disease?”
-PV: “I just got a negative test result back on my patient. What is the chance that my patient actually doesn't have the disease?”
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Now to the Math
Patient with the disease
Patient without the
disease
Test is positive
ATrue Positive
BFalse Positive
Test is negative
CFalse
Negative
DTrue Negative
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Using the 2X2 table you can calculate Sensitivity = a / (a+c)Specificity = d / (b+d)
+ PV = a/(a+b)- PV = d/(c+d)
Knowing the prevalence of the disease in the population is
necessary for these calculations
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Understanding Predictive Value
• Prevalence is defined as the number of patients per 100,000 population who have the disease at a given time.
• A high +PV indicates a strong chance that a person with a positive test has the disease whereas a low +PV is usually found in populations with low prevalence of the condition being examined. A high -PV means that a negative test in effect rules out the disease.
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Effects of PrevalenceSensitivity=95% Specificity=95%
Population’s
Prevalence
0.1%
1.0%
2.0%
5.0%
50%
Predictive Value of a Positive Test
1.9%
16.1%
27.9%
50%
95%
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Effects of PrevalenceSensitivity=99% Specificity=99%
Population’sPrevalence
0.1%1.0%2.0%5.0%50%
Predictive Value of a Positive Test
9.0%50%
66.9%83.9%99%
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SpPins and SnNoutSpPIn
When a sign, test or symptom has an extremely high specificity (say, over 95%), a positive result tends to rule in the diagnosis. For example, the specificity of 3 or more positive responses on a CAGE questionnaire in diagnosing alcoholism is >99% among internal medicine patients. Therefore, if a person does answer "yes" to 3 or 4 of the CAGE questions, it rules in the diagnosis of alcohol dependency.
SnNOutWhen a sign, test or symptom has a high sensitivity, a negative result rules out the diagnosis. For example, the sensitivity of the loss of retinal vein pulsation in diagnosing high intracranial pressure is 100 per cent. Therefore, if a person displays retinal vein pulsation, it rules out important increases in intracranial pressure.
http://www.minervation.com/cebm2/docs/spPinsnNout.html
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Website Reading
1. Testing a Testhttp://www.jr2.ox.ac.uk/bandolier/band3/b3-1.html
By, J A Muir Gray MD FRCP (Glas) MRCGP FFCM Director of Health Policy and Public Health
2. SpPins and SnNoutshttp://www.minervation.com/cebm2/docs/spPinsnNout.html
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Suggested Assignment
• Guided discussion or an individual assignment about a specific screening– Exploring the natural history of the disease, the gold
standard, different population (prevalence), and calculating specificity, sensitivity, +PV and –PV
– Debating the pro and cons of this screening as it relates to the Principles of Screening and Screening Test
– Interpretation of results and relaying information to clients
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The End
This presentation was created by:
Mary Beth Bigley, DrPH-c, ANP
Assistant Professor
Director of the Nurse Practitioner Program
The George Washington University
You are welcome to contact me to discuss the use of this material and additional learning activities. [email protected]