Application of a test or a procedure to large number of population who have no symptoms of a particular disease for the purpose of determining their likelihood of having the disease.

1. Dr. Dalia El-Shafei
Lecturer, CommunityMedicineDepartment, Zagazig
University

2. Levels of Prevention:Levels of Prevention:
No DiseaseNo Disease AsymptomaticAsymptomatic
PreventionPrevention 1ry1ry
preventionprevention
2ry2ry
preventionprevention
3ry3ry
preventionprevention
 Remove riskRemove risk
factorsfactors
Early detectionEarly detection
Early treatmentEarly treatment
ReduceReduce
complicationscomplications
Clinical DiseaseClinical Disease

3. Screening :Screening :
Application of a test or a procedure toApplication of a test or a procedure to
large number of population who have nolarge number of population who have no
symptoms of a particular disease for thesymptoms of a particular disease for the
purpose of determining their likelihoodpurpose of determining their likelihood
of having the disease.of having the disease.

4. Asymptomatic Symptomatic

6. Possibly diseased

7. 4outcomes
Diseased individuals
+ve by screening
Diseased individuals
-ve by screening
Non Diseased individuals
-ve by screening
Non Diseased individuals
+ve by screening

8.  Goals reduce morbidity or mortality fromGoals reduce morbidity or mortality from
disease:disease:
 Objectives :Objectives :
Early detection of disease amongEarly detection of disease among
subclinical cases.subclinical cases.
Identify at risk individuals.Identify at risk individuals.
Identify carriers of disease.Identify carriers of disease.

11. Screening TestsScreening Tests
They can be in the form of:They can be in the form of:
 QuestionsQuestions
 ExaminationsExaminations
 Laboratory testsLaboratory tests
 X-Rays ??? (Miniature Mass Radiography)X-Rays ??? (Miniature Mass Radiography)

12. Screening ProgramScreening Program
 Mass screening.Mass screening.
 Selective screening.Selective screening.
 Opportunistic screening.Opportunistic screening.

13.  Advantages :Advantages :
 Magnitude of disease can be precisely assessed.Magnitude of disease can be precisely assessed.
 Early detected cases can be controlled.Early detected cases can be controlled.
 disadvantages :disadvantages :
 Not 100% accurate test.Not 100% accurate test.
 Costly.Costly.
 Adverse effect.Adverse effect.
 Anxiety due to false positives.Anxiety due to false positives.
 Sense of security due to false negatives.Sense of security due to false negatives.

14. Criteria for screening programCriteria for screening program
1- Disease :1- Disease :
 Important health problem.Important health problem.
 Understood natural history.Understood natural history.
 Identifiable symptomatic stage.Identifiable symptomatic stage.
 Long DPCP.Long DPCP.
2- Treatment & Diagnosis:2- Treatment & Diagnosis:
 Accepted or useful treatment.Accepted or useful treatment.
 Available facilities for further diagnosis & treatment.Available facilities for further diagnosis & treatment.
 Cost/benefit is balanced.Cost/benefit is balanced.
 Favorably influence prognosis “non-melanotic skin carcinoma:Favorably influence prognosis “non-melanotic skin carcinoma:
completely cureable” “Ca. cervix: good prognosis” “Ca. lung:completely cureable” “Ca. cervix: good prognosis” “Ca. lung:
no value”.no value”.

15. 3- Test :3- Test :
 Simple.Simple.
 Rapid.Rapid.
 Non-invasive.Non-invasive.
 Cheap.Cheap.
 Accepted.Accepted.
 Valid.Valid.
 Reliable.Reliable.
 Can be done by non-medicals.Can be done by non-medicals.

16. ScreeningScreening versusversus clinical examinationclinical examination
Screening Clinical examination
Used in population studies On individuals
Absence of medical indication Presence of medical
indication
Treatment can’t be described
upon results
Treatment can be described
upon results
Subjects can be classified:
Likely to be ill
Likely to be free
Subjects can be classified:
Diseased
Not diseased

17. Terms Related toTerms Related to
Screening TestsScreening Tests
 ValidityValidity - relates to accuracy (correctness)- relates to accuracy (correctness)
 ReliabilityReliability – repeatability– repeatability
 AccuracyAccuracy -proportion of true test results among all test results-proportion of true test results among all test results
 YieldYield - the # of tests that can be done in a time period- the # of tests that can be done in a time period

18. A. ReliabilityA. Reliability
The ability of a test or combination of tests to give
consistent results in repeated applications, whether
correct or incorrect.
This could be a function of the test, for example,
one nurse making repeat blood pressure
measurements on an individual; or of the person
performing the test, for example, ten different
nurses measuring the blood pressure of the same
individual.

19. SensitivitySensitivity
It is the proportion of true positives among all cases:It is the proportion of true positives among all cases:
a/(a+c)a/(a+c)
The ability of the test to detect true positives from allThe ability of the test to detect true positives from all
those who are diseased.those who are diseased.
B. ValidityB. Validity
Measured by test’s ability to do what it’s supposed to do.Measured by test’s ability to do what it’s supposed to do.

20. SpecificitySpecificity
It is the proportion of true negatives among allIt is the proportion of true negatives among all
noncases : d/(b+d)noncases : d/(b+d)
The ability of the test to detect true negativesThe ability of the test to detect true negatives
from all those not diseased.from all those not diseased.

21. SENSETIVITY (+ve) SPECIFICITY (-ve)
Important penalty for missing a
disease
- Serious disease + definite ttt exist
“TB, Hodgkin’s dis.”
- Spread “gonorrhea, syphilis”
Subsequent diagnostic evaluation
of +ves associated with minimal
risks & costs “BP for HPN”
False +ve results harm pts.
Physically, emotionally,
financially.
- Cancer “chemotherapy ”
- HIV “stigma”
Subsequent diagnostic evaluation
of +ves associated with high
risks & costs “biopsy for breast
cancer”
Trade-offs between sensitivity & specificity:
Inverse relationship
Trade-offs between sensitivity & specificity:
Inverse relationship

22. Predictive valuesPredictive values
 Positive Predictive Value “PPV”:
- Probability of disease in a patient with +ve test result
- Proportion of a +ve test that are truly +ve (truly diseased)
= a/a+b
 Negative Predictive Value “NPV”:
- Probability of disease in a patient with +ve test result
- Proportion of a -ve test that are truly -ve (truly non-diseased)
= d/c+d

23. PPredictive value (PV) of a positive test:PPredictive value (PV) of a positive test:
The proportion of a positive test that are trulyThe proportion of a positive test that are truly
positive (truly diseased) : a/(a+b)positive (truly diseased) : a/(a+b)
 The PV of a positive test increases with increasingThe PV of a positive test increases with increasing
sensitivity and specificity.sensitivity and specificity.
 If the prevalence of a disease in the populationIf the prevalence of a disease in the population
increases the PV also increases and the reverse is true.increases the PV also increases and the reverse is true.
 High risk population are frequently chosen forHigh risk population are frequently chosen for
screening thus increasing the yield and PV of ascreening thus increasing the yield and PV of a
positive test.positive test.

24. The predictive value of a positive
test increases as the prevalence of
diseases increases even with the
same sensitivity & specificity of
the screening test.
(See the following example)

25. Disease Non Diseased
50 50 100
50 50
100 100
100
200
True Diagnosis Total
Test Result
Positive
Negative
Disease Non Diseased
60 40 100
60 40
120 80
100
200
Disease Non Diseased
40 60 100
40 60
80 120
100
200

26. Application:
If the target condition is sufficiently rare,
even tests with excellent sensitivity &
specificity can have low positive predictive
value (PPV) generating more false positives
than true positive results.

27. C. AccuracyC. Accuracy
It is the proportion of true test results amongIt is the proportion of true test results among
all test results:all test results:
(a+d)/(a+b+c+d)(a+d)/(a+b+c+d)

28. Gold standard test
+ve -ve Total
+ve a
(true+ve)
b
(false+ve)
a +b PVP= a/a+bPVP= a/a+b
x100x100
–ve c
(false -ve)
d
(true -ve)
c+d PVN=d/c+dPVN=d/c+d
x 100x 100
Total a+c b+d a+b+c+d
Sensitivity =Sensitivity =
a/a+c x 100a/a+c x 100
Specificity =Specificity =
d/b+d x 100d/b+d x 100
Accuracy=
a+d/a+b+c+d
Screeningtest

29. Example:Example:
+ve+ve -ve-ve TotalTotal
+ve+ve
––veve
15(true+ve)15(true+ve)
10(false -ve)10(false -ve)
30(false+ve)30(false+ve)
45(true45(true ––ve)ve)
4545
5555
TotalTotal 25 (dis.)25 (dis.) 75 (free)75 (free) 100100
 Sensitivity = 15/25 x 100 = 60%Sensitivity = 15/25 x 100 = 60%
 Specificity = 45/75 x 100 = 60%Specificity = 45/75 x 100 = 60%
 Predictive value +ve = 15/45x 100= 33.3%Predictive value +ve = 15/45x 100= 33.3%
 Predictive value –ve =45/55x 100= 81.8%Predictive value –ve =45/55x 100= 81.8%
 Accuracy= 15+45/100 x 100=60%Accuracy= 15+45/100 x 100=60%
Mammography (gold standard)Mammography (gold standard)
SelfexamSelfexam
(screening)(screening)

30. True positives
True negatives
False positives
False negatives

31. True positives
True negatives
False positives
False negatives
80
60
40
20
Total 100 100

32. •Sensitivity: True Positives
All Diseased
a/(a+c) = 80%
•Specificity: True Negatives
All non diseased
d/(b+d) = 60%
Validity

33. Screening EthicsScreening Ethics
 Informed consent for testing and follow up.Informed consent for testing and follow up.
 Considerations of the risks of screening.Considerations of the risks of screening.
 Distributive justice.Distributive justice.

34. Risks of ScreeningRisks of Screening
A.A. True PositiveTrue Positive
““Labeling effect” Person is classified as “diseased” fromLabeling effect” Person is classified as “diseased” from
the time of the test forward in time.the time of the test forward in time.
B.B. False PositiveFalse Positive
 Financial burdenFinancial burden
 Harm from confirmatory test (which may be invasive)Harm from confirmatory test (which may be invasive)
 -ve psychological impact-ve psychological impact
 Fear of future screens “phobia”Fear of future screens “phobia”

35. Risks of ScreeningRisks of Screening
C.C. True NegativesTrue Negatives
Costs & risks of screening testsCosts & risks of screening tests
D.D. False NegativesFalse Negatives
- False sense of security.- False sense of security.
-Delayed interventionDelayed intervention
-Disregard of early signs and symptomsDisregard of early signs and symptoms
-Loss of confidence in medical care systemLoss of confidence in medical care system

36.  Exercise :-Exercise :-
 A medical research team conduct a trial to find if highA medical research team conduct a trial to find if high
plasma level of breast carcinoma promoting factor (BCPF)plasma level of breast carcinoma promoting factor (BCPF)
could be used to diagnose breast cancer.could be used to diagnose breast cancer.
 Out of 1600 patients included in the study ,600Out of 1600 patients included in the study ,600
demonstrated by breast biopsy(the gold standard) to havedemonstrated by breast biopsy(the gold standard) to have
breast cancer (D+) and 1000 were found to be disease –breast cancer (D+) and 1000 were found to be disease –
free(D-)free(D-)
 Out of the 600 demonstrated to have breast cancer ,570Out of the 600 demonstrated to have breast cancer ,570
were positive by BCPF(T+) and Out of the 1000 were foundwere positive by BCPF(T+) and Out of the 1000 were found
to be disease –free,850 were negative by BCPF(T-)to be disease –free,850 were negative by BCPF(T-)

37. It is an example of studying the performance of a newIt is an example of studying the performance of a new
diagnostic testdiagnostic test
PATHOLOGYPATHOLOGY
STUDIED TESTSTUDIED TEST
BreastBreast
cancer(D+)cancer(D+)
No breastNo breast
cancer (D-)cancer (D-)
TotalTotal
Marker (+)Marker (+)
(T+)(T+)
570 (TP)570 (TP) 150 ( FP)150 ( FP) 720720
Marker (-)Marker (-)
(T-)(T-)
30 (FN)30 (FN) 850 (TN)850 (TN) 880880
TotalTotal 600600 10001000 16001600

38. Sensitivity, specificity, predictive value positive & predictiveSensitivity, specificity, predictive value positive & predictive
value negative can be calculatedvalue negative can be calculated
Sensitivity=Sensitivity= 570/600 = 0.95 = 95%570/600 = 0.95 = 95%
Specificity=850/1000 = 0.85 = 85%Specificity=850/1000 = 0.85 = 85%
Predictive value positive=Predictive value positive= 570/720 = 0.79=79%570/720 = 0.79=79%
Predictive value negative=Predictive value negative= 850/880 = 0.97=97%850/880 = 0.97=97%

39.  Another Exercise :-Another Exercise :-
 A medical research team conduct a trial to find if a bloodA medical research team conduct a trial to find if a blood
marker could be used to diagnose breast cancer.marker could be used to diagnose breast cancer.
 Out of 1600 patients included in the study ,600Out of 1600 patients included in the study ,600
demonstrated by breast biopsy(the gold standard) to havedemonstrated by breast biopsy(the gold standard) to have
breast cancer (D+) and 1000 were found to be disease –breast cancer (D+) and 1000 were found to be disease –
free(D-)free(D-)
 Out of the 600 demonstrated to have breast cancer ,570Out of the 600 demonstrated to have breast cancer ,570
were positive by the marker “BCPF”(T+) and Out of thewere positive by the marker “BCPF”(T+) and Out of the
1000 were found to be disease –free,850 were negative by1000 were found to be disease –free,850 were negative by
“BCPF”(T-)“BCPF”(T-)

40. Feedback of the another Exercise :-Feedback of the another Exercise :- It is an example ofIt is an example of
studying the validity of a new screening diagnostic teststudying the validity of a new screening diagnostic test
PATHOLOGY
STUDIED
TEST
Breast
cancer(D+)
No breast
cancer (D-)
Total
Marker (+)
(T+)
570 (TP) 150 ( FP) 720
Marker (-)
(T-)
30 (FN) 850 (TN) 880
Total 600 1000 1600

41.  Feedback of Exercise (cont.):-Feedback of Exercise (cont.):-
 Sensitivity, specificity, predictive value positive & predictive valueSensitivity, specificity, predictive value positive & predictive value
negative can be calculatednegative can be calculated
 Sensitivity=Sensitivity= 570/600 = 0.95 = 95%570/600 = 0.95 = 95%
 Specificity=850/1000 = 0.85 = 85%Specificity=850/1000 = 0.85 = 85%
 Predictive value positive=Predictive value positive= 570/720 = 0.79=79%570/720 = 0.79=79%
 Predictive value negative=Predictive value negative= 850/880 = 0.97=97%850/880 = 0.97=97%

42. Find the validity of testing sugar in urine for detection ofFind the validity of testing sugar in urine for detection of
diabetes from the following tablediabetes from the following table
gold
standard
Screening
Blood sugar
curve +ve
Diabetic
Blood sugar
curve –ve
Non- Diabetic
Total
+ ve diabetes by
urine test
25 15 40
- ve diabetes by
urine test
20 40 60
Total 45 55 100

43.  Sensitivity= 25/45 = 55.5%Sensitivity= 25/45 = 55.5%
 Specificity=40/55 = 72.7%Specificity=40/55 = 72.7%
 Predictive value positive=Predictive value positive= 25/40 = 62.3%25/40 = 62.3%
 Predictive value negative=Predictive value negative= 40/60 = 66.7%40/60 = 66.7%

44. Two hundred individuals (80with and 120 withoutTwo hundred individuals (80with and 120 without
infarction were examined by two laboratoryinfarction were examined by two laboratory
methods (A&B) to find out which of these lab.methods (A&B) to find out which of these lab.
Tests is more valid in detection of coronaryTests is more valid in detection of coronary
infarction:infarction:
 Test A: the number of detected infraction cases by test wereTest A: the number of detected infraction cases by test were
70.40 of them were truly infracted cases.70.40 of them were truly infracted cases.
 Test B: the number of detected infraction cases by test wereTest B: the number of detected infraction cases by test were
100.60 of them were truly infracted cases.100.60 of them were truly infracted cases.

45. Gold standard
Screening
TEST
Infarction No infarction Total
+ ve infarction by
test A
40 (TP) 30 ( FP) 70
- ve infarction by
Test A
40 (FN) 90 (TN) 130
Total 80 120 200

46. test Atest A
 Sensitivity= 40/80= 50%Sensitivity= 40/80= 50%
 Specificity=90/55120 = 75%Specificity=90/55120 = 75%

Predictive value positive=Predictive value positive= 40/70 = 57%40/70 = 57%

Predictive value negative=Predictive value negative= 90/130 = 69%90/130 = 69%

47. ((test Btest B))
Gold standard
Screening
TEST
Infarction No infarction Total
+ ve infarction by
test B
60 (TP) 40 ( FP) 100
- ve infarction by
Test B
20 (FN) 80 (TN) 100
Total 80 120 200

48. ((test Btest B))
 Sensitivity= 60/80 = 75%Sensitivity= 60/80 = 75%
 Specificity=80/120 = 66.7%Specificity=80/120 = 66.7%

Predictive value positive=Predictive value positive= 60/100 = 60%60/100 = 60%

Predictive value negative=Predictive value negative= 80/100 = 80%80/100 = 80%

49. IGT No
IGT
Total
+ve 50
TP
35
FP
85
-ve 8
FN
103
TN
111
Total 58 138 196
Predictive value of positive
= 50 =58.8%
85
Predictive value of negative
= 103 =92.8%
111
Remember:- Sensitivity =
86.2%
Specificity =
Predictive value varies with
prevalence (pretest probability).