Here are the calculations for the predictive values of a positive HIV test with 95% sensitivity and 98% specificity in populations with different prevalence rates: 1) Prevalence of HIV in blood donors = 2% Total tested = 1000 With HIV = 1000 * 0.02 = 20 Without HIV = 1000 - 20 = 980 Sensitivity = 95% Specificity = 98% True Positives (a) = Sensitivity * With HIV = 0.95 * 20 = 19 False Positives (b) = (1 - Specificity) * Without HIV = 0.02 * 980 = 20 False Negatives (c) = (1 - Sensitivity) * With HIV = 0

1. DIAGNOSTIC AND SCREENING TESTS

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.

15. Cont…

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?