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SCREENING
Prepared By Dr. Anees AlSaadi
CMT-P R4
December 2013
1
SCREENING
• Outline:
– Definition of Screening.
– Differentiation between Screening and Diagnostic test?
– Uses/Purpose of Screening.
– Types and Examples of Screening test.
– Criteria for successful screening program.
– Relation ship between sensitivity and specify.
– Risk of Screening.
2
How We Can Define Screening ….?
3
Definition
The early detection of:
–Disease
–Precursors of Disease
–Susceptibility to Disease
In individuals who do not show any signs of
disease.
4
Definition
The presumptive identification of those who
probably have disease from those who do not
have
by
means of rapidly applied tests in apparently
healthy individuals.
5
Definition
6
Definition
Screening
7
How we can Differentiate Between
Screening and Diagnostic Tests ….?
8
Differentiate Between Screening and
Diagnostic Tests
Screening Diagnostic
Asymptomatic Suggestive clinical picture
Large group Single subject
Less accurate Accurate
Not conclusive Conclusive
Less expensive Expensive
Not basic for treatment Basic to treatment
9
What are the Uses of Screening ….?
10
Uses of Screening
Uses of Screening
Case Detection Perspective Screening
Case / Disease Control Prospective Screening
Research Natural History of Disease
Health Education Public Awareness
11
Purpose of Screening
• Reducing disease burden.
• Classifying people to likelihood of having a
particular disease.
• Mean of identifying high risk groups who
warrant further evaluation.
12
Screening Process
13
Types of Screening Test
What are the Type of Screening Tests …?
14
Types
Of
Screening
Test Mass
High Risk
Multiphasic
Types of Screening Test
15
Types of Screening Test
Population Approach
Not Cost Effective
Potential To Alter The Root Cause Of Disease
Large Chance To Reduce Disease Incidence
Small Benefit To The Individual
Poor Subject Motivation
Large Chance Of Reducing Disease Incidence
16
Types of Screening Test
High Risk Strategy
Fails To
D eal With
Ro o t Cau se
O f D isease.
17
Can You Give Some Examples For
Screening Tests … ?
18
Examples for Screening Tests
Infancy Pregnancy Elderly Adults
Growth Charts Weight Cancers Lipid profile
Metabolic
Screening
CBC Depression Blood pressure
Hearing Test Blood sugar Vitamin
deficiencies
BMI
19
Criteria For Successful Screening Test:
Successful
Screening
Criteria for
Disease
Criteria for Test
20
Criteria For Successful Screening Test:
• Criteria for Disease:
–Present in population screened.
–High burden &of high public health concern.
–Screening +Intervention must improve
outcome.
–Known natural history of the disease.
21
Criteria For Successful Screening Test:
• Criteria for Test:
– Reliable.
– Valid.
– Simple and inexpensive.
– Very safe.
– Acceptable to subjects and providers.
– Cost-effective.
– Exit strategy.
22
Criteria For Successful Screening Test:
• Exit strategy:
• Facilities for diagnosis and appropriate
treatments should be available for positive
subjects.
• Ethically not acceptable to offer screening
without available management.
23
Criteria For Successful Screening Test:
• RELIABILTY:
What Is The Definition Of
Reliability ?
What Are The Causes Of
Unreliability ?
24
Criteria For Successful Screening Test:
Definition of Reliability:
– Repeatability, Reducibility, Precision.
– Getting the same results, when the test
repeated in same target individuals in the
same settings.
25
Criteria For Successful Screening Test:
Causes of unreliability:
– Observer variation.
– Subject variation – Biological.
– Technical method error variation.
26
Criteria For Successful Screening Test:
• ACCEPTABILITY:
–The test should not be:
• Painful.
• Unsafe.
• Discomforting /Embarrassing.
• Socially/ believes not accepted.
27
Criteria For Successful Screening Test:
VALIDITY:
Ability of the test to distinguish between who
has the diseases and who does not.
28
Validity
Sensitivity
Specificity
Predictive
Value
Yield
29
DISEASE TOTAL
TEST
Diseased No disease
Test +ve a b a+b
Test -ve c d c+d
TOTAL a+c b+d a+b+c+d
30
Sensitivity
Ability of the test
to truly identify
those who have
the disease
Sensitivity=
a/(a+c)
True
Positive
DISEASE TOTAL
TEST
Diseased
No
disease
Test
+ve
a b a+b
Test
-ve
c d c+d
TOTAL a+c b+d a+b+c
+d
31
Sensitivity
[[A 90% Sensitivity means that 90% of the diseased
people screened by the test will give a “true
positive” and the remaining 10% a “false negative
results”]]
32
Positive test
and have the
disease.
Negative test
and have the
disease.
Specificity
The ability of the test
to correctly identify
those who do not
really have the disease
Specificity=
d/(b+d)
True
Negative
DISEASE TOTAL
TEST
Diseased
No
disease
Test
+ve
a b a+b
Test
-ve
c d c+d
TOTAL a+c b+d a+b+c
+d
33
Specificity
[[A 90% Specificity means that 90% of the non
diseased people screened by the test will give a “true
negative” result, and the remaining 10% a “false
negative results”]]
34
Negative test and do
not have the disease.
Negative test and have the
disease.
• False Positive error rate= (1-specificity)
• False Negative error rate = (1-sensitivity)
35
Assume a population of 1,000 people 100 have a disease 900
do not have the disease A screening test is used to identify the
100 people with the disease
36
Sensitivity = 80/ 100 X 100= 80%
Specificity = 800/ 900 X 100 = 88%
Practical Example
37
Brain Tumor
EEG Results Present Absent
Positive 36 54,000
Negative 4 306,000
Total 40 360,000
Sensitivity = 36/40 X 100 = 90%
Specificity = 306,000/360,000 X 100 = 85%
DISEASE TOTAL
TEST
Diseased No disease
Test +ve a (True Positive) b (false Positive) a+b
Test -ve c (false Negative) d (True Negative) c+d
TOTAL a+c b+d a+b+c+d
38
Predictive value
Positive
Predictive value
Proportion of
Individuals with
positive test really
have the disease
PPV=a/(a+b)
Negative
Predictive value
Proportion of
Individuals with
negative test really
have no disease
NPV= d/(c+d)
DISEASE TOTAL
TEST
Diseased
No
disease
Test
+ve
a b a+b
Test
-ve
c d c+d
TOTAL a+c b+d a+b+c
+d
39
Practical Example
Screening Test
Results
Diagnosis Total
Diseased Not Diseases
Positive 40 20 60
Negative 100 9840 9940
Total 140 9860 10,000
40
Sensitivity = 40/140 X100 = 28.57%
Specificity = 9840/9860 X100 =99.79%
Positive predictive value = 40/60X100 = 66.66%
Negative predictive value = 9840/9940X100 = 98.9%
Effects on Predictive Value
Prevalence Increases PPV Increases; NPV Decreases
Prevalence Decreases PPV Decreases; NPV Increases
Specificity Increases PPV Increases
Sensitivity Increases NPV Increases
41
Yield –the amount of previously unrecognized
disease that is diagnosed and brought to treatment as
a result of the screening program.
42
Practical Exercise
43
44
What is better a test with high sensitivity
or with high specificity…?
Relation Between Sensitivity &
Specificity
Sensitivity Specificity
False
Positive
45
Relation Between Sensitivity &
Specificity
Specificity Sensitivity
False
Negative
46
Relation Between Sensitivity &
Specificity
47
What
about
Risk of
Screening …?
48
Risk of Screening
True
Positive
Labelling
Effect
False
Positive
Anxiety
Fear From
Future Test
Monetary
Expenses
False
Negative
Delayed
Diagnosis
Delayed
Intervention
Complications
49
50

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screening-140217071714-phpapp02.pdf

  • 1. SCREENING Prepared By Dr. Anees AlSaadi CMT-P R4 December 2013 1
  • 2. SCREENING • Outline: – Definition of Screening. – Differentiation between Screening and Diagnostic test? – Uses/Purpose of Screening. – Types and Examples of Screening test. – Criteria for successful screening program. – Relation ship between sensitivity and specify. – Risk of Screening. 2
  • 3. How We Can Define Screening ….? 3
  • 4. Definition The early detection of: –Disease –Precursors of Disease –Susceptibility to Disease In individuals who do not show any signs of disease. 4
  • 5. Definition The presumptive identification of those who probably have disease from those who do not have by means of rapidly applied tests in apparently healthy individuals. 5
  • 8. How we can Differentiate Between Screening and Diagnostic Tests ….? 8
  • 9. Differentiate Between Screening and Diagnostic Tests Screening Diagnostic Asymptomatic Suggestive clinical picture Large group Single subject Less accurate Accurate Not conclusive Conclusive Less expensive Expensive Not basic for treatment Basic to treatment 9
  • 10. What are the Uses of Screening ….? 10
  • 11. Uses of Screening Uses of Screening Case Detection Perspective Screening Case / Disease Control Prospective Screening Research Natural History of Disease Health Education Public Awareness 11
  • 12. Purpose of Screening • Reducing disease burden. • Classifying people to likelihood of having a particular disease. • Mean of identifying high risk groups who warrant further evaluation. 12
  • 14. Types of Screening Test What are the Type of Screening Tests …? 14
  • 16. Types of Screening Test Population Approach Not Cost Effective Potential To Alter The Root Cause Of Disease Large Chance To Reduce Disease Incidence Small Benefit To The Individual Poor Subject Motivation Large Chance Of Reducing Disease Incidence 16
  • 17. Types of Screening Test High Risk Strategy Fails To D eal With Ro o t Cau se O f D isease. 17
  • 18. Can You Give Some Examples For Screening Tests … ? 18
  • 19. Examples for Screening Tests Infancy Pregnancy Elderly Adults Growth Charts Weight Cancers Lipid profile Metabolic Screening CBC Depression Blood pressure Hearing Test Blood sugar Vitamin deficiencies BMI 19
  • 20. Criteria For Successful Screening Test: Successful Screening Criteria for Disease Criteria for Test 20
  • 21. Criteria For Successful Screening Test: • Criteria for Disease: –Present in population screened. –High burden &of high public health concern. –Screening +Intervention must improve outcome. –Known natural history of the disease. 21
  • 22. Criteria For Successful Screening Test: • Criteria for Test: – Reliable. – Valid. – Simple and inexpensive. – Very safe. – Acceptable to subjects and providers. – Cost-effective. – Exit strategy. 22
  • 23. Criteria For Successful Screening Test: • Exit strategy: • Facilities for diagnosis and appropriate treatments should be available for positive subjects. • Ethically not acceptable to offer screening without available management. 23
  • 24. Criteria For Successful Screening Test: • RELIABILTY: What Is The Definition Of Reliability ? What Are The Causes Of Unreliability ? 24
  • 25. Criteria For Successful Screening Test: Definition of Reliability: – Repeatability, Reducibility, Precision. – Getting the same results, when the test repeated in same target individuals in the same settings. 25
  • 26. Criteria For Successful Screening Test: Causes of unreliability: – Observer variation. – Subject variation – Biological. – Technical method error variation. 26
  • 27. Criteria For Successful Screening Test: • ACCEPTABILITY: –The test should not be: • Painful. • Unsafe. • Discomforting /Embarrassing. • Socially/ believes not accepted. 27
  • 28. Criteria For Successful Screening Test: VALIDITY: Ability of the test to distinguish between who has the diseases and who does not. 28
  • 30. DISEASE TOTAL TEST Diseased No disease Test +ve a b a+b Test -ve c d c+d TOTAL a+c b+d a+b+c+d 30
  • 31. Sensitivity Ability of the test to truly identify those who have the disease Sensitivity= a/(a+c) True Positive DISEASE TOTAL TEST Diseased No disease Test +ve a b a+b Test -ve c d c+d TOTAL a+c b+d a+b+c +d 31
  • 32. Sensitivity [[A 90% Sensitivity means that 90% of the diseased people screened by the test will give a “true positive” and the remaining 10% a “false negative results”]] 32 Positive test and have the disease. Negative test and have the disease.
  • 33. Specificity The ability of the test to correctly identify those who do not really have the disease Specificity= d/(b+d) True Negative DISEASE TOTAL TEST Diseased No disease Test +ve a b a+b Test -ve c d c+d TOTAL a+c b+d a+b+c +d 33
  • 34. Specificity [[A 90% Specificity means that 90% of the non diseased people screened by the test will give a “true negative” result, and the remaining 10% a “false negative results”]] 34 Negative test and do not have the disease. Negative test and have the disease.
  • 35. • False Positive error rate= (1-specificity) • False Negative error rate = (1-sensitivity) 35
  • 36. Assume a population of 1,000 people 100 have a disease 900 do not have the disease A screening test is used to identify the 100 people with the disease 36 Sensitivity = 80/ 100 X 100= 80% Specificity = 800/ 900 X 100 = 88%
  • 37. Practical Example 37 Brain Tumor EEG Results Present Absent Positive 36 54,000 Negative 4 306,000 Total 40 360,000 Sensitivity = 36/40 X 100 = 90% Specificity = 306,000/360,000 X 100 = 85%
  • 38. DISEASE TOTAL TEST Diseased No disease Test +ve a (True Positive) b (false Positive) a+b Test -ve c (false Negative) d (True Negative) c+d TOTAL a+c b+d a+b+c+d 38
  • 39. Predictive value Positive Predictive value Proportion of Individuals with positive test really have the disease PPV=a/(a+b) Negative Predictive value Proportion of Individuals with negative test really have no disease NPV= d/(c+d) DISEASE TOTAL TEST Diseased No disease Test +ve a b a+b Test -ve c d c+d TOTAL a+c b+d a+b+c +d 39
  • 40. Practical Example Screening Test Results Diagnosis Total Diseased Not Diseases Positive 40 20 60 Negative 100 9840 9940 Total 140 9860 10,000 40 Sensitivity = 40/140 X100 = 28.57% Specificity = 9840/9860 X100 =99.79% Positive predictive value = 40/60X100 = 66.66% Negative predictive value = 9840/9940X100 = 98.9%
  • 41. Effects on Predictive Value Prevalence Increases PPV Increases; NPV Decreases Prevalence Decreases PPV Decreases; NPV Increases Specificity Increases PPV Increases Sensitivity Increases NPV Increases 41
  • 42. Yield –the amount of previously unrecognized disease that is diagnosed and brought to treatment as a result of the screening program. 42
  • 44. 44 What is better a test with high sensitivity or with high specificity…?
  • 45. Relation Between Sensitivity & Specificity Sensitivity Specificity False Positive 45
  • 46. Relation Between Sensitivity & Specificity Specificity Sensitivity False Negative 46
  • 47. Relation Between Sensitivity & Specificity 47
  • 49. Risk of Screening True Positive Labelling Effect False Positive Anxiety Fear From Future Test Monetary Expenses False Negative Delayed Diagnosis Delayed Intervention Complications 49
  • 50. 50