Diagnostic Tests

Afshin Ostovar

Bushehr University of Medical Sciences

Bushehr, 2013

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A normal individual is a person; Who has not been sufficiently examined

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Introduction

It is necessary to distinguish between people in the population who have the disease and those who do not.

clinical arenaPublic health arena

How good is the test in separating populations of people with and without the disease in question?

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Biologic Variation of Human Populations

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Bimodal curve

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Unimodal curve

Validity of screening Tests

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Tests with Dichotomous Results

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Gold Standard

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False Positive effectsBurden on the health care system

Labeling effect

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False Negative effects

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Tests of Continuous Variables

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Sensitivity= 5/20 = 25%

Specificity= 18/20 = 90%

Tests of Continuous Variables

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Sensitivity= 17/20 = 85%

Specificity= 6/20 = 30%

Different cut-offs

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Multiple Tests

Sequential (Two-stage) Testing

Simultaneous (Parallel) Testing

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Sequential (Two-stage) Testing

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Test 1

Diabetes

+ _

Test Results+

_

10000

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Prevalence = 5%

Diabetes

+ _

Test Results+

_

500 9500 10000

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Sensitivity = 70%

Diabetes

+ _

Test Results+ 350

_ 150

500 9500 10000

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Specificity = 80%

Diabetes

+ _

Test Results+ 350 1900

_ 150 7600

500 9500 10000

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Final Result of Test 1

Diabetes

+ _

Test Results+ 350 1900 2250

_ 150 7600 7750

500 9500 10000

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Test 2

Diabetes

+ _

Test Results+

_

350 1900 2250

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Sensitivity= 90%

Diabetes

+ _

Test Results+ 315

_ 35

350 1900 2250

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Specificity=90%

Diabetes

+ _

Test Results+ 315 190

_ 35 1710

350 1900 2250

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Final Result of two Tests

Diabetes

+ _

Test Results+ 315 190 2250

_ 185 9310 7750

500 9500 10000

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Net sensitivity = 315/500 = 63%

Net Specificity = 9310/9600 = 98%

Simultaneous Testing

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Test A

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Test B

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Test A

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Test B

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Predictive Value

Predictive Value PositiveIf the test results are positive in this

patient, what is the probability that this patient has the disease.

Predictive Value NegativeIf the test results are negative in this

patient, what is the probability that this patient do not have the disease

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Predictive Value Positive

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The predictive value is affected by two factors:

o the prevalence of the disease in the population tested

o the specificity of the test being used, when the disease is infrequent.

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Relationship between Predictive Value and Disease Prevalence

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Relationship between Predictive Value and Disease Prevalence

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Relationship between Predictive Value and Disease Prevalence

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Relationship between Predictive Value and

Specificity

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Relationship between Predictive Value and

Specificity

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Relationship between Predictive Value and

Specificity

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Relationship between Predictive Value and

Specificity

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