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…
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.
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?