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Screening

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Information about Screening
Health & Medicine

Published on February 17, 2014

Author: draneesalsaadi

Source: slideshare.net

Description

Screening as a tool for secondary prevention in public health
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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 Types of Screening Test Mass High Risk Multiphasic 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 F a i l s To D eal With Root Cause Of Disease. 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: Criteria for Disease Successful Screening 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: What Is The Definition Of Reliability ? • RELIABILTY: 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

Sensitivity Yield Validity Specificity Predictive Value 29

DISEASE TOTAL TEST a+b Test -ve c TOTAL Diseased No disease Test +ve a b d c+d b+d a+b+c+d a+c 30

Sensitivity DISEASE TOTAL Ability of the test to truly identify those who have the disease TOTAL True Positive Test +ve a b a+b Test -ve TEST Diseased No disease c d c+d a+c b+d a+b+c +d Sensitivity= a/(a+c) 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”]] Positive test and have the disease. Negative test and have the disease. 32

Specificity DISEASE Diseased TOTAL True Negative No disease Test +ve a b a+b Test -ve TEST The ability of the test to correctly identify those who do not really have the disease TOTAL c d c+d a+c b+d a+b+c +d Specificity= d/(b+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”]] Negative test and do not have the disease. Negative test and have the disease. 34

• 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 Sensitivity = 80/ 100 X 100= 80% Specificity = 800/ 900 X 100 = 88% 36

Practical Example EEG Results Brain Tumor 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% 37

DISEASE TEST Diseased TOTAL TOTAL No disease Test +ve a (True Positive) b (false Positive) a+b Test -ve c (false Negative) d (True Negative) c+d b+d a+b+c+d a+c 38

Predictive value DISEASE TOTAL Diseased Negative Predictive value Proportion of Individuals with positive test really have the disease TOTAL PPV=a/(a+b) Test +ve a b a+b Test -ve Proportion of Individuals with negative test really have no disease TEST Positive Predictive value No disease c d c+d a+c b+d a+b+c +d NPV= d/(c+d) 39

Practical Example Screening Test Results Diagnosis Total Positive Negative Diseased 40 100 Not Diseases 20 9840 60 9940 Total 140 9860 10,000 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% 40

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

What is better a test with high sensitivity or with high specificity…? 44

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 False Negative Anxiety Delayed Diagnosis Fear From Future Test Delayed Intervention Monetary Expenses Complications 49

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