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DIAGNOSTIC AND SCREENING TESTS
Diagnostic and Screening tests
 Diagnostic and screening tests are used to obtain
information that guide health personnel’s decision
to initiate or continue a therapeutic intervention.
 Tests performed in persons with a symptom or a
sign of an illness are usually termed as diagnostic
tests.
 Tests that are done in individuals with no such
symptoms or sign are called screening.
Diagnostic and screening tests
 Standardized interviews,
 Physical examinations,
 Laboratory tests,
 More sophisticated measurements such as
radiography, electro-cardiograph, slit-lamp
examination.
There are different types of screening,
each with specific aims;
1. Mass screening: It involves the screening of a whole
population.
2. Multiple or multi-phase screening: It involves the use
of a variety of screening tests on the same occasion.
3. Case finding or opportunistic screening; It is
restricted to patients who consult a health
practitioner for some other purposes.
Rationale of applying tests requires
judgment of:
 Person tested
 Costs of illness (monetary and physical)
 Costs of the tests.
 Cost of accuracy
Criteria for instituting a screening program
1. Disease Serious
High prevalence of preclinical stage
Natural history understood
Long period between first diagnosis and
overt disease
2. diagnostic test Sensitive and specific
Simple and cheap
Safe and acceptable
Reliable
3. Diagnosis and
treatment
Facilities are adequate
Effective, acceptable and safe treatment /
rehabilitative methods available
VALIDITY OF A DIAGNOSTIC
TEST
 A central issue in evaluating a test is its
validity, or the ability to differentiate
accurately between those who have the
disease and those who do not have.
 The validity of the test refers to the extent to
which the test is capable of correctly
diagnosing the presence or absence of the
disease concerned.
Cont…
 There are two important aspects of validity:
 These two aspects,
1) Correctly diagnosing as having a disease is
referred as the sensitivity.
2) Correctly diagnosing of not having a disease
are referred as the specificity of the test.
For example,
 A test is said to have a sensitivity of 90% if it
gives a positive result in 90% of persons who
actually have the disease.
 On the other hand, a test is said to have a
specificity of 90% if it gives a negative result
in 90% of persons who actually do not have
the disease.
Cont…
Sensitivity and specificity are calculated using the
following formula:
Sensitivity and specificity of test could be illustrated
through the following 2 x 2 table.
From this table, the following values
are commonly calculated:
Cont…
 Sensitivity and specificity are proportions
comparing test results to the “True” disease
situation, “Gold standard”.
 However, tests are actually used the other way
around when they are needed to predict which
individuals have the disease, hence the importance
of the positive and negative predictive values.
 The predictive value of a test which depends upon
the prevalence of a disease, as well as a test’s
sensitivity and specificity is the most important
measure determining its usefulness in a field.
Predictive value and its relationship
with prevalence
 Predictive Value Positive (PVP) – The probability
that a person with a positive result in a screening
or diagnostic test is in fact a true positive.
 Predictive Value Negative (PVN) – The
probability that a person with a negative result in a
screening or diagnostic test is in fact a true
negative.
 Prevalence – The total number of persons with
actual disease in the population.
Cont…
Predictive value and different prevalence
rates:
Calculations
Sensitivity = a Specificity = . d .
a + c b + d
= 380 . = . 1280 .
400 1600
= 95 % = 80 %
Example
 Considering a diagnostic test has a
sensitivity of 95 % and specificity of 80 %
and calculate the Positive and negative
predicative value when the prevalence of the
disease is:
1) 20 %?
2) 1%?
PV(+) = . P x Sn .
(P x Sn) + ((1 - P) x (1 - Sp))
= . 0.2 x 0.95 .
(0.2 x 0.95) + ((1 – 0.2) x (1 – 0.8))
= 0.54 or 54 %
 This means that of all the positives found by the
screening test only 54 % are true positives.
1a. Prevalence 20 %
PV(-) = . (1 – P) x Sp .
((1 – P) x Sp) + (P x (1 - Sn))
= . (1 – 0.2) x 0.80 .
((1 - 0.2) x 0.80) + ( 0.2 x (1 – 0.95))
= 0.98 or 98 %
 This means that of all the negatives found by the
screening test 98 % are true negatives.
1b. Prevalence 20 %
PV(+) = . P x Sn .
(P x Sn) + ((1 - P) x (1 - Sp))
= . 0.01 x 0.95 .
(0.01 x 0.95) + ((1 – 0.01) x (1 – 0.8))
= 0.045 or 4.5 %
This means that of all the positives found by the
screening test only 4.5 % are true positives.
2a. Prevalence 1 %
2b. Prevalence 1 %
PV(-) = . (1 – P) x Sp .
((1 – P) x Sp) + (P x (1 - Sn))
= . (1 – 0.01) x 0.80 .
((1 - 0.01) x 0.80) + ( 0.01 x (1 – 0.95))
= 0.999 or 99.9 %
This means that of all the negatives found by the
screening test almost all are true negatives.
Relationship between Prevalence and
predictive values
 Predictive value Positive
(when the sensitivity and
specificity constant) is
directly related to the
prevalence of a disease in a
community.
 Predictive value Negative
(when the sensitivity and
specificity constant) is
inversely related to the
prevalence of a disease in a
community.
P
r
e
v
a
l
PV (+)
PV (-)
P
r
e
v
a
l
 Home test.
For the following calculations, show the data first in the form
of a 2X2 table, starting with the marginal totals for those with
and without disease, based on the given prevalence rate.
Assuming a sensitivity of 95% and a specificity of 98% for the
EIA test for HIV-1 infection, what would be the predictive
value of the positive test for:
1. A population of 1000 blood donors with an estimated
prevalence rate of HIV-1 infection of 2%.
2. A population of 1000 female sex workers with an estimated
prevalence rate of HIV-1 infection of 28%.
3. From the above answers, what can you conclude about the
relationship between the PVP and the prevalence rate, with
sensitivity and specificity held constant?

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session three epidemiology.pptx

  • 2. Diagnostic and Screening tests  Diagnostic and screening tests are used to obtain information that guide health personnel’s decision to initiate or continue a therapeutic intervention.  Tests performed in persons with a symptom or a sign of an illness are usually termed as diagnostic tests.  Tests that are done in individuals with no such symptoms or sign are called screening.
  • 3. Diagnostic and screening tests  Standardized interviews,  Physical examinations,  Laboratory tests,  More sophisticated measurements such as radiography, electro-cardiograph, slit-lamp examination.
  • 4. There are different types of screening, each with specific aims; 1. Mass screening: It involves the screening of a whole population. 2. Multiple or multi-phase screening: It involves the use of a variety of screening tests on the same occasion. 3. Case finding or opportunistic screening; It is restricted to patients who consult a health practitioner for some other purposes.
  • 5. Rationale of applying tests requires judgment of:  Person tested  Costs of illness (monetary and physical)  Costs of the tests.  Cost of accuracy
  • 6. Criteria for instituting a screening program 1. Disease Serious High prevalence of preclinical stage Natural history understood Long period between first diagnosis and overt disease 2. diagnostic test Sensitive and specific Simple and cheap Safe and acceptable Reliable 3. Diagnosis and treatment Facilities are adequate Effective, acceptable and safe treatment / rehabilitative methods available
  • 7. VALIDITY OF A DIAGNOSTIC TEST  A central issue in evaluating a test is its validity, or the ability to differentiate accurately between those who have the disease and those who do not have.  The validity of the test refers to the extent to which the test is capable of correctly diagnosing the presence or absence of the disease concerned.
  • 8. Cont…  There are two important aspects of validity:  These two aspects, 1) Correctly diagnosing as having a disease is referred as the sensitivity. 2) Correctly diagnosing of not having a disease are referred as the specificity of the test.
  • 9. For example,  A test is said to have a sensitivity of 90% if it gives a positive result in 90% of persons who actually have the disease.  On the other hand, a test is said to have a specificity of 90% if it gives a negative result in 90% of persons who actually do not have the disease. Cont…
  • 10. Sensitivity and specificity are calculated using the following formula:
  • 11. Sensitivity and specificity of test could be illustrated through the following 2 x 2 table.
  • 12. From this table, the following values are commonly calculated:
  • 13. Cont…  Sensitivity and specificity are proportions comparing test results to the “True” disease situation, “Gold standard”.  However, tests are actually used the other way around when they are needed to predict which individuals have the disease, hence the importance of the positive and negative predictive values.  The predictive value of a test which depends upon the prevalence of a disease, as well as a test’s sensitivity and specificity is the most important measure determining its usefulness in a field.
  • 14. Predictive value and its relationship with prevalence  Predictive Value Positive (PVP) – The probability that a person with a positive result in a screening or diagnostic test is in fact a true positive.  Predictive Value Negative (PVN) – The probability that a person with a negative result in a screening or diagnostic test is in fact a true negative.  Prevalence – The total number of persons with actual disease in the population.
  • 16.
  • 17. Predictive value and different prevalence rates:
  • 18. Calculations Sensitivity = a Specificity = . d . a + c b + d = 380 . = . 1280 . 400 1600 = 95 % = 80 %
  • 19. Example  Considering a diagnostic test has a sensitivity of 95 % and specificity of 80 % and calculate the Positive and negative predicative value when the prevalence of the disease is: 1) 20 %? 2) 1%?
  • 20. PV(+) = . P x Sn . (P x Sn) + ((1 - P) x (1 - Sp)) = . 0.2 x 0.95 . (0.2 x 0.95) + ((1 – 0.2) x (1 – 0.8)) = 0.54 or 54 %  This means that of all the positives found by the screening test only 54 % are true positives. 1a. Prevalence 20 %
  • 21. PV(-) = . (1 – P) x Sp . ((1 – P) x Sp) + (P x (1 - Sn)) = . (1 – 0.2) x 0.80 . ((1 - 0.2) x 0.80) + ( 0.2 x (1 – 0.95)) = 0.98 or 98 %  This means that of all the negatives found by the screening test 98 % are true negatives. 1b. Prevalence 20 %
  • 22. PV(+) = . P x Sn . (P x Sn) + ((1 - P) x (1 - Sp)) = . 0.01 x 0.95 . (0.01 x 0.95) + ((1 – 0.01) x (1 – 0.8)) = 0.045 or 4.5 % This means that of all the positives found by the screening test only 4.5 % are true positives. 2a. Prevalence 1 %
  • 23. 2b. Prevalence 1 % PV(-) = . (1 – P) x Sp . ((1 – P) x Sp) + (P x (1 - Sn)) = . (1 – 0.01) x 0.80 . ((1 - 0.01) x 0.80) + ( 0.01 x (1 – 0.95)) = 0.999 or 99.9 % This means that of all the negatives found by the screening test almost all are true negatives.
  • 24. Relationship between Prevalence and predictive values  Predictive value Positive (when the sensitivity and specificity constant) is directly related to the prevalence of a disease in a community.  Predictive value Negative (when the sensitivity and specificity constant) is inversely related to the prevalence of a disease in a community. P r e v a l PV (+) PV (-) P r e v a l
  • 25.  Home test. For the following calculations, show the data first in the form of a 2X2 table, starting with the marginal totals for those with and without disease, based on the given prevalence rate. Assuming a sensitivity of 95% and a specificity of 98% for the EIA test for HIV-1 infection, what would be the predictive value of the positive test for: 1. A population of 1000 blood donors with an estimated prevalence rate of HIV-1 infection of 2%. 2. A population of 1000 female sex workers with an estimated prevalence rate of HIV-1 infection of 28%. 3. From the above answers, what can you conclude about the relationship between the PVP and the prevalence rate, with sensitivity and specificity held constant?