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1 SCREENING TEST Dr. Khanchit Limpakarnjanarat Thailand MOPH – US CDC Collaboration (TUC)

SCREENING TEST

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SCREENING TEST. Dr. Khanchit Limpakarnjanarat Thailand MOPH – US CDC Collaboration (TUC). SCREENING TEST. Did any one of participants experience in using screening test in your daily work? What is it?. [ANC, health check up, patient with fever, surveillance, etc] - PowerPoint PPT Presentation

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1

SCREENING TEST

Dr. Khanchit LimpakarnjanaratThailand MOPH – US CDC Collaboration

(TUC)

2

SCREENING TEST

• Did any one of participants experience in using screening test in your daily work? What is it?

• [ANC, health check up, patient with fever, surveillance, etc]• Whenever primary prevention is possible, it is the best approach to prevent disease occurrence and/or epidemic.• Two possible approaches to early diagnosis

–Depends on awareness of warning signs–Active detection of disease in asymptomatic cases

3

Know the Seven Warning Signs of Cancer…

•Appearance of a lump in a breast or elsewhere

•A change in a mole or wart

•A sore that doesn't heal

•Indigestion or difficulty swallowing

•Nagging cough or hoarseness

•Unusual bleeding

•Persistent respiratory problems

[American Cancer Society]

4

CAGE screening for alcoholism

• Have you ever felt you should Cut down on your drinking?

• Have people Annoyed you by criticizing your drinking?

• Have you ever felt bad or Guilty about your drinking?

• Have you ever had a drink first thing in the morning to steady your nerves or to get rid of a hangover (Eye-opener)?

5

The CAGE questions for alcohol abuse

Number of positive answers to the 4 CAGE questions

Alcohol abuse

YES NO

3 or 4

2, 1 or none

ac d

b

a + c

b + d

c + d

a + b

a + b + c + d

(True +)

60

(False +)

1

400

(True -)

57

(False -)117

401

518

457

61

Suckett D. A Primer on the Precision and Accuracy of the Clinical Examination. JAMA 267(19):2638-2644, May 1992

Sens. = 60/117=0.51Spec. = 400/401=0.998

PVP = 60/61 = 0.98PVN = 400/457 = 0.88

6

Schema relating path of detection to outcome

[Dr. Maureen Handerson]A. CURRENT SITUATION

Self referral Care for chromic

disease

Diagnosis

Surveillance Recovery

B. FUTURE PROJECTION

Self referral Care for chromic

disease

Diagnosis

Surveillance Recovery

Source: Mausner & Bahn: Epidemiology-an introductory text, Chapter9 - screening in detection of disease

7

Screening test

is the basic tool of screening program and must be thoroughly understood since screening is designed to be applied to large group of people, screening test should be easy to use, rapid and inexpensive. They should also be able to carry out largely by technicians

1.2

8

Screening Test

Definition: the PRESUMPTIVE

identification of unrecognized disease or defect by the application of tests, examinations, or other procedures which can be applied rapidly to sort out apparently well persons who probably have a disease from those who probably do not.

A screening test is not intended to be diagnostic. Persons with positive or suspicious findings must be referred to their physicians for diagnosis and necessary treatment.

[Commissioned on Chronic Illness –1951]

9

Goal of Screening Test

•To reduce morbidity or mortality from the disease among the people screened by early treatment of the cases discovered. (Clinical Medicine)

•To help guide preventive and control measures in general or specific populations. (Epidemiology and Public Health)

10Flow diagram for a mass screening test

APPARENTLY WELL POPULATION TO BE TESTED(Well persons plus those with

undiagnosed disease)

+

Negatives on test

Positives on test, no diseasePositives on test, disease present

+

++

+

Rescreen at prescribed interval

Negatives (normal)

- persons presumed to be free of disease under study

SCREENING TEST

++++

+

+++++

++

+

++DIAGNOS

TIC PROCEDURES

Positives (abnormal)

- persons presumed to have the disease or be at increased risk in future

THERAPEUTIC INTERVENTION

Disease or risk factor present

Disease or risk factor absent

Rescreen at prescribed interval

11

PURPOSES OF SCREENING

• DIAGNOSIS• IDENTIFY TOXIC CHEMICAL AGENTS• ESTIMATE MAGNITUDE OF DISEASE OR

PUBLIC HEALTH CONDITIONS• IDENTIFICATION OF PEOPLE AT HIGH RISK

12

PURPOSE OF SCREENING (1)

•DIAGNOSIS: Series of test perform on a symptomatic patient for whom a diagnosis has not yet been established.

Example: Patients with hematuria may need UA, urine culture, cystoscopy, bladder biopsy, several types of X-ray, several blood chemistry studies

13

PURPOSE OF SCREENING (2)

•IDENTIFY TOXIC CHEMICAL AGENTS: Chemical agents may be screened by means of laboratory tests or epidemiologic surveillance in order to identify those substances likely to be toxic.

Example: Pb poisoning surveillance by Pb screening among children

14

•ESTIMATE MAGNITUDE OF DISEASE OR PUBLIC HEALTH CONDITIONS: Some screening procedures can be used to estimate the prevalence of various conditions which may lead to disease control objectives. Major methodologic problem in this area is the relation between ‘detected’ prevalence and the underlying ‘true’ prevalence, e.g., sample size, sampling technics.

Example: Serologic testing, GenProbe testing, Cervical Pap’s smear, Tuberculin skin test, CXR

PURPOSE OF SCREENING (3)

15

PURPOSE OF SCREENING (4)

•IDENTIFICATION OF PEOPLE AT HIGH RISK: People at high risk may be who do not yet have the disease. The link between screening for a risk factor and a disease may not be sharp.

Example: Identify smokers, identify drinkers by MAST test, HT may be a risk factor for CVD or may be early disease detection itself

16

Types of Screening Program

• Selective screening specific disease in people at risk

• Mass screening test large number of people

17

Selective screening

• Selective screening: Tests are used to detect a specific disease among people who are at risk of having disease.– Single disease: e.g., CXR for pneumoconiosis in

coal miners or FBS for evidence of DM in diabetic patients’ relatives

– Multiphasic screening program: e.g., ANC in pregnant women

18

Mass screening

• Mass screening: Large number of people are tested for the presence of disease or condition without specific emphasis to their individual risk of having disease or condition– Single disease: e.g., cervical pathology for

cancer of cervix, mammography for breast cancer

– Multiphasic screening program: e.g., Biochemical profile in community survey

19

Lead time and screening test

• Lead time is the time interval from detection by screening test to the time at which diagnosis would have been made without that screening.

• Length of lead time interval may vary from person to person (short and long lead time)

• Importance of lead time is for disease control and by early detection and early treatment to prevent spread and disability of affected persons. Screening test is valuable in reducing severe morbidity and mortality

20

Measurements used in screening tests

• Validity – test is capable to differentiate presence or absence of disease

• Yield – brought unrecognized disease to diagnosis

• Reliability – consistent result when test more than once

21

Creation of 2 x 2 table – initial step for calculation

TEST “Screening”

+

-

Yes No

DISEASE “Gold standard”

a bc d

True pos False pos

False neg True neg

22

VALIDITY• Validity is the indication of which test is capable

of differentiating the presence or absence of a disease concerned

SENSITIVITY = ability of test to detect people who actually have the disease (True Positive)

SPECIFICITY = ability of test to identify correctly people who actually do not have the disease (True Negative)

23

1. Sensitivity = proportion of subjects with disease who have the positive test from screening

= a / a+c

or = TP / TP + FN2. Specificity = proportion of subjects without disease

who have the negative test from screening

= d / b+d

or = TN / FP + TN3. Accuracy of the test = a + d / a + b + c + d

= TP + TN / Total screened

Validity of screening test

24

YIELD

• Yield is the amount of previously unrecognized disease which is diagnosed and brought to treatment as a result of the screening

PREDICTIVE VALUE POSITIVE (PVP) is the likelihood that an individual with a positive test has the disease

PREDICTIVE VALUE NEGATIVE (PVN) is the likelihood that an individual with a negative test does not have the disease

25

Yield of screening test

• Predictive Value Positive (PVP)PVP = a / a + b

or = TP / TP + FP

• Predictive Value Negative (PVN)PVN = d / c + d

or = TN / TN + FN

9

26

RELIABILITY (Precision)

• Reliability is one that give consistent results when the test is performed more than once on the same individual under the same conditions. It is also called ‘Repeatability’

27

Reliability**Precision**Repeatability

Number of agreed positive= -------------------------------------

Number of positive either time

a= --------------

(a + b + c)

28

Trade off point

Cut off point“Criterion of Positivity”

29

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5Persons without disease

Persons with Disease

Trade off point

abc

d

Num

ber

o f p

ers o

n sReal situation of screening test

Persons with disease = a + c

Persons without disease = b + d

30

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

HealthySick

Trade off point

a

d

Num

ber

o f p

ers o

n sHypothetical best screening test

31

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Trade off point A

Healthy

Sick

Num

ber

of p

ers o

n sShifting of trade off point A

abc

d

X

32

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

HIV-free population

HIV-positive population

Num

ber

o f p

ers o

n sSetting of trade off point A on sensitivity and specificity of HIV EIA assay

c

A B

Negative test Positive test

FALSE POS

High SEN / Low SPEC

33

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Trade off point B

Healthy

Sick

Num

ber

of p

ers o

n sShifting of trade off point B

ab

c

d

X

34

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

HIV-free population

HIV-positive population

Num

ber

o f p

ers o

n sSetting of trade off point B on sensitivity and specificity of HIV EIA assay

A B

Negative test Positive test

FALSE NEG

Low SEN / High SPEC

35

Correlation of SCREENING TEST VS.

True results = True positive (a)= True negative (d)

False results = False positive (b)= False negative (c)

GOLD STANDARD

A B

TEST “Screening”

+

-

Yes No

DISEASE “Gold standard”

a bc d

True pos False pos

False neg True neg

36

1. Sensitivity = proportion of subjects with disease who have the positive test from screening

= a / a+c

or = TP / TP + FN

2. Specificity = proportion of subjects without disease who have the negative test from screening

= d / b+d

or = TN / FP + TN

Validity of screening test

37

Specificity should be increased relative to sensitivity:

• When the false positive result can harm patient physically, emotionally, or financially, e.g., HIV infection

• When the cost or risk associated with further diagnostic technique are substantial, such as breast cancer, for which the definitive diagnostic evaluation of a positive screening test is a biopsy

38

Sensitivity should be increased at the expense of specificity:

• When the penalty associated with missing a case is high such as disease is serious and definitive treatment exist, e.g., PKU

• When the disease can spread, e.g., syphilis

• When subsequent diagnostic evaluations of positive screening tests are associated with minimal cost and risk, e.g., series of B.P. readings to ascertain HT

39

PROBLEMS WITH SCREENING TEST

1. Lack of information on negative tests : Prostate specific antigen (PSA) for

prostate cancer

2. Lack of information in the non-disease :MRI to diagnose prolapse disk

3. Lack of standards for disease• Consequence of imperfect standards : diagnosis of gall stone by U/S vs. Cholecystogram

Clinical Epidemiology - KKU

40

Table : sensitivity and specificity of blood sugar to diagnose DM [Public Health Service, US, 1960]

708090

100110120130140150160170180190200

98.697.194.388.685.771.464.357.150.047.142.938.634.327.1

8.825.547.669.884.192.596.999.499.699.8

100.0100.0100.0100.0

Blood Sugar level2 hrs-post meal

(mg %)

Sensitivity(%)

Specificity(%)

41

ROC of accuracy of blood sugar test (2 hours post meal) to diagnosis DM [Public Health Service, Diabetes program guide Publ. No. 506, Washington DC, US Government Printing Office, 1960]

Specificity (%)

Diagnosis point

1 -

Sen

siti

vity

(%

)

Sen

siti

vity

(%

)[T

rue

po

siti

ve]

6.5B1 - Specificity (%)

42

Combination of test

To enhance sensitivity or specificity of the screening test

• Test in series: person is called “positive” when he tests +ve to all of a series of test, “negative” if he tests –ve to any. This enhance the SPECIFICITY of the test

• Test in parallel: person is labeled “positive” if he tests +ve to any of a test, “negative” if he tests –ve to all. This enhance the SENSITIVITY of the test

43

MULTIPLE TESTS CONCEPT

Types Step of event Result

Serialtesting

Paralleltesting

sensitivity specificity

sensitivity specificity

+

+

+

A

B

C

-

-

-

A B C+ + +

6.6B

Positive = all test +ve

Positive = any test +ve

44

Perinatal HIV Outcome Monitoring System (PHOMS)

•Criteria for diagnosis of HIV status in children = uninfected–HIV antibody negative at least 1 time in any age group; (serial or parallel)

–PCR negative at least 2 times at a different interval and last test must be after 2 months old (serial or parallel)

Serial to increase specificity

Parallel to increase sensitivity

45

Perinatal HIV Outcome Monitoring System (PHOMS)

•Criteria for diagnosis of HIV status in children = infected–HIV antibody positive at least 2 times with different technic, age > 18 months; (serial or parallel)

–PCR positive at least 2 times at a different interval in any age group (serial or parallel)

Serial to increase specificity

Serial to increase specificity

46

Yield of screening test

• Predictive Value Positive (PVP) is likelihood that an individual with a positive test has the disease

PVP = a / a + b or = TP / TP + FP

• Predictive Value Negative (PVN) is likelihood that an individual with a negative test does not have the disease

PVN = d / c + d or = TN / TN + FN

This measurement is useful to M.D. especially PVP

48

Binomial Mathematical ModelIf p = prevalence of disease sens.= sensitivity of test spec.= specificity of test

Then; PVP = p(sens)

p(sens) + (1–p)(1-spec)

PVN = (1-p) spec

(1–p) spec + p(1-sens)PV or yield can be affected by Prevalence, and

Specificity and slightly affected by Sensitivity10.2

49

Results of screening test in two different populations:

sensitivity=.99, specificity=.99Population A (prevalence = 100,000/1,000,000 = 0.10)

Disease+ Disease- Total

Test+ 99,000 9,000 108,000

Test- 1,000 891,000 892,000

100,000 900,000 1,000,000

PVP = TP / (TP+FP) = 99,000/(99,000+9,000) = .917 = 91.7%

PVP = (p)(sens) = (.1)(.99) = .917

(p)(sens)+(1-spec)(1-p) (.1)(.99)+(1-.99)(1-.1)

50

Test results of screening test in two different

populations: sensitivity=.99, specificity=.99Population B (prevalence = 1,000/1,000,000 = 0.001)

Disease+ Disease- Total

Test+ 990 9,990 10,980

Test- 10 989,010 989,020

1,000 999,000 1,000,000

PVP = TP / (TP+FP) = 990/(990+9,990) = .090 = 9.0%

PVP = (p)(sens) = (.001)(.99) = .090

(p)(sens)+(1-spec)(1-p) (.001)(.99)+(1-.99)(1-.001)

51

Relationship between prevalence of disease and predictive value, with sensitivity and specificity held constant at 95%

[adapted from Vecchio, 1966]

0102030405060708090

100

0 20 40 60 80 100

Positive test

Negative test

Prevalence of disease (percentage)

Pre

dict

ive

valu

e (p

erce

ntag

e)

12

52

PVP as a function of prevalence, sens = .99

0102030405060708090

100

0 10 20 40 60 80 100

Positive test

Prevalence of disease (percentage)

Pre

dict

ive

valu

e (p

erce

ntag

e) Spec = .99Spec =

.90Spec = .80

53

PVN as a function of prevalence, spec = .99

0102030405060708090

100

0 10 20 40 60 80 100

Negative test

Prevalence of disease (percentage)

Pre

dict

ive

valu

e (p

erce

ntag

e) Sens = .99Sens = .90

Sens = .80

54

Reliability**Precision**Repeatability

Number of agreed positive= -------------------------------------

Number of positive either time

a= --------------

(a + b + c)

55

Screening of breast cancer by Mammography

Cancer+ Cancer- Total

Test+ 31 108 139

Test- 24 20048 20072

65 20156 20211

Reliability = a / a+b+c = 31 / 31+24+108

= 31 / 163

= 19.0%

56

Four sources of variability

• Biological variation (specimens)

• Variation due to the test method or measurement (test)

• Intra-observer variation (examiner)

• Inter-observer variation (examiners)

57

Increase reliability can be made through:

• Standardization of procedures

• Intensive training of observers

• Periodic quality control

• Use of 2 or more observers making independent observations

58

Reliability and Validity of Instruments

A – reliable and valid C – reliable but not valid

B – not reliable but valid D – not reliable and not valid

Fre

quen

cy

A

B

C

D

True value Measurement

X

59

2X 2 table of screening test, definitions and formulas

Test

positive

negative

Diseasepresent absent

True positive

False positive

a + bc + d

False negative

True negative

a b

c da + c

b + d

a + b + c + d

+PV = a / a + b-PV = d / c + d

Sensitivity

= a / a + c

Specificity

= d / b + dAccuracy= a+d / a+b+c+d

Prevalence= a+c / a+b+c+d

60

Example 1: Screening of breast cancer by clinical examination

Clin exam

positive

negative

Breast cancerpresent absent

34

2000021

156

55 20156 20211

20021

190

Sensitivity = 34/55 X 100 = 61.3% Specificity = 20000/20156 X 100 = 99.2%

PVP = 34/190 X 100 = 17.9% PVN = 20000/20021 X 100 = 99.9%

61

Example 2: Screening of breast cancer by mammography

Mammography

positive

negative

Breast cancerpresent absent

31

2004824

108

55 20156 20211

20072

139

Sensitivity = 31/55 X 100 = 56.4% Specificity = 20048/20156 X 100 = 99.5%

PVP = 31/139 X 100 = 22.3% PVN = 20248/20072 X 100 = 99.9%

62

Example 3: Screening of breast cancer by clinical examination and follows by mammography

positive

negative

Breast cancerpresent absent

19

15515

1

34 156 190

170

20

PVP = 19/20 X 100 = 95%

Mammography

63

Example of prevalence and PVGiven; Sensitivity = 95% Specificity = 95%

Test +Test -

True+

True-

Total

Suppose Prevalence = 10%

Test +Test -

True+

True-

Total

Suppose Prevalence = 20%

950

450

400

1900

2000

100

76008000

2300770010000

10000

9000

1000

14008600

50

8550

PVP =

PVN =

PVP =

PVN =

950/1400 = 67.9%

8550/8600 = 99.4%

1900/2300 = 82.6%

7600/7700 = 98.7%

64

Breast cancer mortality rates at different times after start of follow-up between screened group (mammography)

and controls

No. of women with cancer

No. of deaths (from start to follow-up)

5 years 10 years 18 years

•Screened group•Control group

307

310

39

63

95

133

126

163

% difference 38.1 28.6 22.7

Source: Shapiro 1989

65

SimpliRED VS. WB and EIA VS. WB

+

-

+ -

362

1

0

2133

SimpliREDSensitivity = 100%Specificity = 99.95%

WB

Sim

pli

RE

D

+

-

+ -

362

9

0

2125

EIASensitivity = 100%Specificity = 99.58%

WB

EIA

Conclusion

66

Conclusion of SimpliRED and EIA

• SimpliRED is as sensitive and specific as EIA, but more expensive

• It had excellent correlation with the gold standard WB

• It provided rapid, accurate and on-site HIV status identification

• It required no equipment and minimal training• For this study, it saved unnecessary CD4 testing of

HIV samples

70

Principle of good screening program (1)1. The condition being sought is an important health

problem for the individual and the community. Since screening requires the commitment of large amounts of money, manpower, and other resources, screening should be undertaken only when it has the potential to lead to a significant decrease in rates of disability or death or both

2. There is an acceptable form of treatment for patients with recognizable disease. The goal of screening is to prevent disability or death or both. However, if there is no generally accepted treatment, it is premature to embark on a screening program

3. The natural history of the condition, including its development from latent to declared disease, is adequately understood. This is perhaps the most crucial of all the criteria in determining the feasibility of screening.

71

Principle of good screening program (2)

4. There is a recognizable latent or early symptomatic stage

5. There is a suitable screening test or examination for detecting the disease at the latent or early symptomatic stage, and this test is acceptable to the population

6. The facilities required for diagnosis and treatment of patients revealed by the screening program are available. Many screening programs have had little effect because planning for them did not include adequate and effective mechanisms for follow-up of positives

7. There is an agreed policy on whom to treat as patients

8. Treatment at the pre-symptomatic, borderline stage of a disease favorably influences its course and prognosis

72

Principle of good screening program (3)

9. The cost of the screening program (which would include the cost of diagnosis and treatment) is economically balanced in relation to possible expenditure on medical care as a whole

10.Case finding is a continuing process, not a “once and for all” project. Some conditions, e.g., Phenylketonuria must be screened for once, early in life. Others should be monitored repeatedly. When repeated screening is necessary, empirical studies are needed to determine the optimal interval between screenings

[Wilson and Jungner, WHO 1968]

73

Criteria for instituting screening program

Disease - Serious

- High prevalence of pre-clinical stage

- Natural history: undertood

- Long period between first signs and overt disease

Pre-test - Sensitive and specific

- Simple and cheap

- Safe and acceptable

- Reliable

Diagnosis - Facilities are adequate

and treatment - Effective, acceptable, and safe treatment available

78

Questions ?

79

80

81

Directigen Flu A + B

FLU OIA QuickVue Influenza

Test

ZstatFlu

Examples of Rapid Tests

82

• Test Factors • Sensitivity- Proportion of positive tests by gold standard

that are also positive by screening test (true positives)

• Specificity- Proportion of negative tests by gold standard that are also negative by screening test (true negatives)

• Prevalence- Proportion of tested population with influenza

• Other factors• Type and quality of respiratory specimen• Day of illness when specimen was obtained• Compliance with test procedures• Interpretation of result

Factors Affecting Rapid Test Performance

83

• Sensitivity: median = 70-75%

• Specificity: median = 90-99%• Calculated under ideal conditions• Most data are from children with

influenza A (H1N1) or A (H3N2)• Sensitivity to detect influenza A > B• No published data on H5N1

Summary of Published Data on Performance of Rapid Influenza Tests*

*Uyeki, T. 2003. Peds Infectious Disease (22) 164-77.

84

New Uses for Rapid Tests In Thailand

• Febrile respiratory illness outbreak investigation

• Research – Outpatient disease burden– Seasonality– Cost of illness

• Expanded human influenza surveillance

• H5N1 avian influenza clinical management

85

Seasonality of Outpatient Influenza

Using Rapid Tests; 2003-2004

29%

21%

0% 0% 0%

9%13%

27%

45%40%

12%

31%

0%

10%

20%

30%

40%

50%

Aug

Sep Oct NovDec Ja

nFeb Mar Apr

May Jun Ju

l

Month

Prop

ortio

n Po

sitiv

e