SCREENING

Asst. Prof. Sumattna GlangkarnRN, MSc. (Epidemiology), PhD (Nursing studies)

sumattana.g@msu.ac.thsglangkarn@hotmail.co.uk

Levels of Prevention

Primordial preventionPrimary preventionSecondary preventionTertiary prevention

Primordial prevention Phase of disease: Underlying

economic, social, and environmental conditions leading to causation

Aim: Establish and maintain conditions that minimised hazards to health

Actions: Measures that inhibit the emergence of environmental, economic, social and behavioural conditions.

Target: Total population or selected groups; achieved through public health policy and health promotion.

Primary prevention

Phase of disease: Specific causal factors Aim: Reduce the incidence of disease Actions: Protection of health by personal

and communal efforts, such as enhancing nutritional status, providing immunizations, and eliminating environmental risks

Target: Total population, selected groups and healthy individuals; achieved through public health policy.

Secondary prevention

Phase of disease: Early stage of disease Aim: Reduce the prevalence of disease by

shortening its duration Actions: Measures available to individuals

and communities for early detection and prompt intervention to control disease and minimise disability (e.g. through screening programmes).

Target: Individuals at high risk and patients; achieved through preventive medicine.

Tertiary prevention

Phase of disease: Late stage of disease (treatment, rehabilitation)

Aim: Reduce the number and/or impact of complications

Actions: Measures aimed at softening the impact of long-term disease and disability; minimising suffering, maximising potential years of useful life.

Target: Patients; achieved through rehabilitation.

Screening test Screening is performed in order to identify

whether have a disease for which they currently have no symptoms

Screening is not performed to diagnose illness.

It aims to improve the outcomes of those who are affected, by detecting a disease before its symptoms have developed.

If the disease can be diagnosed and treated at an early stage, illness and mortality can be reduced.

In practice, screening test are never completely

accurate. ‘False-positive’ results, in which the test

indicates that a subject has the disease when it reality they do not.

‘False-negative’ results, in which the test indicates that there is no disease present, when it reality the subject does have the disease.

A good screening test should keep false-positive and false-negative results to an absolute minimum.

The UK National Screening Committee’s criteria for appraising the viability, effectiveness and appropriateness of a screening programme Condition

Test Treatment Screening programme

Condition The condition should be an important health

problem. The epidemiology and natural history of the

condition, including development from latent to declared disease, should be adequately understood and there should be a detectable risk factor, disease marker, latent period or early symptomatic stage.

All of the cost-effective primary prevention interventions should have been implemented as far as is practicable.

If the carriers of a mutation are identified as a result of screening the natural history of people with this status should be understood, including the psychological implications.

Test There should be a simple, safe, precise and

validated screening test. The distribution of test values in the target

population should be known, and a suitable-cut-off level should be defined and agreed.

The test should be acceptable to the population.

There should be an agreed policy on the further diagnostic investigation of individuals with a positive test result, and on the choices available to those individuals.

Treatment There should be an effective treatment or

intervention for patients identified through early detection, with evidence of early treatment leading to better outcomes than late treatment.

There should be agreed evidence-based policies covering which individuals should be offered treatment, and the appropriate treatment to be offered.

Clinical management of the condition and patient outcomes should be optimised by all healthcare providers prior to participation in a screening programme.

Screening programme

There should be evidence from high-quality randomised controlled trials that the screening programme is effective in reducing mortality or morbidity.

There should be evidence that the complete screening programme (including testing, diagnostic procedures, treatment/intervention) is clinically, socially and ethically acceptable both to health professional and to the public.

The benefit from the screening programme should outweigh the physical and psychological harm (caused by the test, diagnostic procedures and treatment).

The opportunity cost of the screening programme (including testing, diagnosis and treatment, administration, training and quality assurance) should be economically balanced in relation to expenditure on medical care as a whole (i.e. value for money).

There should be a plan for managing and monitoring the screening programme and an agreed set of quality assurance standards.

Adequate staffing and facilities for testing, diagnosis, treatment and programme management should be made available prior to the commencement of the screening programme.

All other options for managing the condition should have been considered (e.g. improving treatment, providing other services), to ensure that no more cost-effective interventions could be introduced or current interventions increased within the resources available.

Evidence-based information explaining the consequences of testing, investigation and treatment should be made available to potential participants to assist them in making an informed choice.

Public pressure both to widen the eligibility criteria for reducing the screening interval and to increase the sensitivity of the testing process should be anticipated. Decisions about these parameters should be scientifically justifiable to the public.

If screening is for a mutation the programme should be acceptable to people identified as carriers and to other family members

Evaluation of proficiency of test

Precision (or Repeatability or R eliability) is the ability of a

measurement to give consistent re sults on repeated trials

Validity (or Accuracy) is the abili ty of a measuring instrument to gi ve a true value. Validity can be eva

luated only if there exists an accep ted and independent (gold standar

d) method for confirming the condition.

SENSITIVITY and SPECIFICITY

Sensitivity is the ability of a tes t to give positive results in a gro

up of persons with the disease ( True positive)

Specificity is the ability of a test to give negative results in a gro up of persons without the disea se (True negative)

Screening test

True situationScreening test result Disease Non-disease

Total

Positive a (TP) b (FP) a+b

Negative c (FN) d (TN) c+d

Total a+c b+d N

SENSITIVITY and SPECIFICITY

Sensitivity = TP 100x = a x 100

TP + FN a + c

Specificity = TN 100 = 100d x TT T T T++

ACCURACY

Accuracy = 100TP + TN x

Grand total = a + d

100 a + b + c + d

Conditions that require s high sensitivity test

The disease is fatal if missed. If it is de tected at an early stage, the patients would have high probability of survivi

ng, or getting cured. The disease has the high potential of s

pread to other people if not detected. The confirmatory test is available for t

hose who have screened as positive.

Conditions that require s high specificity test

The false positive will give fatal im pression for the persons screened

. The disease is not yet detected by

other method, or the diagnosis ha s to be done through more painful or more complicated methods suc

h as liver biopsy.

Example: A pregnancy test is a dministered to 100 pregnant

- 100women and non pregnant -women, the result are shown:

Test result Pregnant Non-pregnant

+ 95 2

- 5 98

Total 100 100

Sensitivity, Specificit y and Accuracy

Sensitivity = 95 100x = 95 %

100

Specificity =98 100 = 98 %

100 Accuracy = 95 98 100+ x

= 9 6 .5 % 100100

Example: TTTTT TTTTTTTTT TTTT , A, B and C were applied

to 1,000 patients with di T TTTTTTT TTTTTTTT(

ed on the basis of glucos e tolerance tests) and to

3 ,0 0 0 persons free of diabetes. Test A 90yielded positive results in

0 1200diabetics and , non diabe tics.

Test B 600gave positive results in diabetics and 300 non diabetics.

Test C waspositivein850diabeticsand450nondi abeti cs.

FIND:-

Test A, B, C Sensitivity = ? Specificity = ? Accuracy = ?

Results of Test A

Test A DM Non-DM Total

+ 900 1,200 2,100

- 100 1,800 1,900

Total 1,000 3,000 4,000

Results of Test B

Test B DM Non-DM Total

+ 600 300 900

- 400 2,700 3,100

Total 1,000 3,000 4,000

Results of Test C

Test C DM Non-DM Total

+ 850 450 1,300

- 150 2,550 2,700

Total 1,000 3,000 4,000

Competency of the Tests

Test A B C

Sensitivity (%) 90.0 60.0 85.0

Specificity (%) 60.0 90.0 85.0

Accuracy (% 67.5 82.5 85.0

Test A : Best when we want a high ly sensitive test

Test B : Best when we want a high ly specificity test

Test C : Most valid of the three be cause it has high both in sensitivity

and specificity.

Competency of the Tests

Predictive value

Ability to detect unrecognis ed disease a nd estimation of number of cases in the

population Positive predictive value : probability of

the person having the disease when the test is positive

Negative predictive value : probability of the person not having the disease when the test is negative

PPV & NPV

Positive predictive value (PPV)

= a x 100 a + b

Negative predictive value (NPV)

= d x 100 c + d

Example: A test with sensitivity 95% and

specificity 95% is applied to a population of 10,000

with estimated prevalence of a specified

disease 10%Find : 1. Positive predictive value

2. Negative predictive value 3. Efficiency of the test 4. % False positive of the positive

test(to be used for mass screening

purpose)

Calculation :

Total population = 10,000Prevalence of disease = 10%Estimate sick persons = 0.1 x 10,000

= 1,000 (a + c)Estimate non-sick =10,000 – 1,000

= 9,000 (b + d)

Calculation (Cont.):

From sick persons:Sensitivity of the test = 95%True positive persons = 0.95 x 1,000

= 950 (a)False negative persons = 1,000 - 950

= 50 (c)

Calculation (Cont.):

From non sick persons:Specificity of the test = 95%True negative persons = 0.95 x 9,000

= 8,550 (d)False positive persons = 9,000 – 8,550

= 450 (b)

Result of Analysis of a s creening test

True situation Screening test result Disease Non-disease

Total

Positive 950 450 1,400

Negative 50 8,550 8,600

Total 1,000 9,000 10,000

Positive predictive value =950 x 100

1,400= 67.9%

Negative predictive value= 8,550 x 100

8,600= 99.4%

Calculation (Cont.):

Accuracy of the test = 950 + 8,550 x 100

10,000= 95.0%

False Positive of the positive test = 450 x 100

1,400= 32.1% (100-67.9)

Calculation (Cont.):

Example: From the previous example, suppose that the prevalence of the

specified disease in the study population is 50% Find : 1. Positive predictive value

2. Negative predictive value 3. Efficiency of the test 4. False positive of the test

Calculation :

Total population = 10,000Prevalence of disease = 50%Estimate sick persons = 0.5 x 10,000

= 5,000 (a + c)Then non-sick persons =10,000 – 5,000

= 5,000 (b + d)

Calculation (Cont.):

From the group of sick persons:Sensitivity of the test = 95%True positive persons = 0.95 x 5,000

= 4,750 (a)False negative persons =5,000 – 4,750

= 250 (c)

Calculation (Cont.):

From the group of non-sick persons:Specificity of the test = 95%True negative persons = 0.95 x 5,000

= 4,750 (d)False positive persons = 5,000 – 4,750

= 250 (b)

Result of Analysis of a s creening test

True situation Screening test result Disease Non-disease

Total

Positive 4,750 250 5,000

Negative 250 4,750 5,000

Total 5,000 5,000 10,000

Positive predictive value = 4,750x 100

5,000= 95.0%

Negative predictive value= 4,750 x 100

5,000 =

95.0%

Calculation (Cont.):

Accuracy of the test = 4,750 + 4,750 x 100

10,000= 95.0%

False Positive of the positive test = 250 x 100

5,000= 5% (100-95)

Calculation (Cont.):

Screening and Prevalence

When the same test is used for screening in populations with higher prevalence of disease, the lower false positives would be obtained.

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Test 1 มื่� Sensitivity 95% และ Specificity 95%

Test 2 มื่� Sensitivity 98% และ Specificity 98%Prevalenc

e(%)

Positive predictive value

Test 1 Test 2

0.1 ? ?1.0 ? ?2.0 ? ?5.0 ? ?

50.0 ? ?

Test 1 มื่� Sensitivity 95% และ Specificity 95%

Test 2 มื่� Sensitivity 98% และ Specificity 98%Prevalenc

e(%)

Positive predictive value

Test 1 Test 2

0.1 1.9 4.61.0 16.1 33.12.0 27.9 50.05.0 50.0 72.0

50.0 95.0 98.0

Type of error that can happen after making a

decisionTrue positive(Sensitivity)

Correct decision

False positive, Type II error ()

Error of commission Proportion of well persons diagnosed as

sickFalse negative, Type I error ()

Error of omission

Proportion of sick persons diagnosed as

well

True negative(Specificity)

Correct decision