Sensitivity, Specificity, Positive Predictive Value, & Negative Predictive Value
In your post, you are to select a disease that no one else has selected. You can post early in the week to reserve your disease and then just reply to your original post when your material is done. Answer the following questions with your initial post.
1. What disease did you select?
2. Find two different incidence rates for this disease. This can be either the rates of the disease in two different countries, age groups, ethnicities, occupation, or any other classifier that might be important to your disease. Provide the two different rates here. Cite your source.
3. Select a screening test or a confirmatory test for your disease. Report on what the sensitivity and specificity percentages are and cite your source. Also, provide the cost of the test.
4. Using the method outlined in the excel document determine the PPV and NPV of using both screening tests in the two populations you selected.
5. How much did each true positive cost?
6. Does it make sense to implement mandatory screening in either population? Why or why not?
What you see below is a 2 x 2 table. We will be using it to explain how to calculate sensitivity and
specificity. Once that is explained, we will move on how to use sensitivity and specificity data
along with incidence information to estamate how many people will be found using a screening
program.
Example 1
Disease (+)
Disease (-)
Test (+)
a (True Positive)
b (False Positive) All Test Positive
Test (-)
c (False Neg)
d (True Negative) All Test Negative
All Diseased
All Well
Sensitivity
90% a/a+c
Specificity
95% d/d+b
Total Pop
Fake Data on an UNKNOWN DISEASE AND TEST
Disease (+)
Disease (-)
Test (+)
475
4974
Test (-)
53
94499
528
99472
Please continue to the next sheet labeled PPV & NPV.
5449
94551
100000
As you can see from our
fictitious example, the fake
screening test that we are
talking about using would
give 53 people a negative
result when they were sick,
4,974 a positive result when
they were not sick. This
doesn’t sound like a great
test, but that is all
dependent on the natural
history of the disease,
mortality associated with it,
sitivity and
fake
hat we are
ing would
a negative
y were sick,
result when
ke a great
he natural
ated with it,
1. Sensitivity and Specificity calculations are always on tests for disease. You can go into any Pharmacy and look at their pr
drug, or paternity tests and they have those numbers on them. The next topic is going to be how do we use that informati
developing screening policies.
All diseases occur in different populations at different rates, if a disease is higher in prevalence in a given population th
preditive value (finding cases) will increase. I am going to show you how to use incidence data along with sensitivity and sp
to generate a PPV and NPV.
Example 1
Disease (+)
Disease (-)
Test (+)
Sensitivity (a)
1 – Specificity (b)
All Test Positive
Test (-)
1 – Sensitivity ( c )
Specificity (d)
All Test Negative
Incidence Number Population -Incidence Number
2. Our previous Sen and S
Calculations were
respectively. Let’s insert t
the appropriate charts ba
information we have.
Total Pop
PPV = A/A+B
NPV = D/D+C
Step 1: Insert Sensitivity and Specificity
Disease (+)
Test (+)
Test (-)
Disease (-)
90% 1 – Specificity (b)
1 – Sensitivity ( c )
All Test Positive
95% All Test Negative
Incidence Number Population -Incidence Number
Total Pop
All you have is incidence
disease estimates in the p
now.
Step 2: Calculate C & D
Disease (+)
Test (+)
Test (-)
Disease (-)
90%
5% All Test Positive
10%
95% All Test Negative
Incidence Number Population -Incidence Number
Total Pop
Population A = 250 per 1,
population
Popuation B =
population
Step 3: Incidence data
Pop A
Disease (+)
Disease (-)
Put the incidence data int
table.
Test (+)
90%
5% All Test Positive
Test (-)
10%
95% All Test Negative
250
750
1000
Pop B
Disease (+)
90%
5% All Test Positive
Test (-)
10%
95% All Test Negative
3
Step 4: Completing the table
997
4. Multiply the percentag
x the incidence total in A
Multiple the percentages
the incidence total in B+D
Disease (-)
Test (+)
Pop A
3. Let’s say you wanted to
what
(PPV) and the negative pr
values (NPV) would be if
screened two different po
5. Calculate the PPV and
1000
6. Take the number of Tru
for Populations A and the
Population B and multiply
Disease (+)
Disease (-)
Test (+)
225,00
38,00
263,00
Test (-)
25,00
712,00
737,00
250
750
1000
for Populations A and the
Population B and multiply
cost of our fake test.
Pop B
Disease (+)
Disease (-)
Test (+)
3,00
50,00
53,00
Test (-)
0,00
947,00
947,00
3
997
1000
Step 5: Calculate the PPV and NPV
Population A
PPV
NPV
Population B
PPV
NPV
85,55%
96,61%
5,66%
100,00%
Step 6: Finances
Cost of Fake Test
25$
Pop A
Cost per Positive 1000 x $25 = $ 25,000
Pop B
Cost per Positive 1001 x $25 = $ 25,000
Summary
$25,000/225 = $111 dollars per positive found
$25,000/3 = $8,333 dollars per positive found
Notice how cheap the cost per positive is when you screening in a population with
any Pharmacy and look at their pregnancy,
be how do we use that information in
alence in a given population then their positive
data along with sensitivity and specificity data
2. Our previous Sen and Spec
Calculations were 90% & 95%
respectively. Let’s insert those into
the appropriate charts based on the
information we have.
3. Let’s say you wanted to find out
what the positive predictive values
(PPV) and the negative predictive
values (NPV) would be if you
screened two different populations.
All you have is incidence data on the
disease estimates in the population
now.
Population A = 250 per 1,000
population
Popuation B = 3 per 1,000
population
Put the incidence data into the 2 x 2
table.
4. Multiply the percentages in A & C
x the incidence total in A + C
Multiple the percentages in B & D x
the incidence total in B+D
5. Calculate the PPV and the NPV
6. Take the number of True Positives
for Populations A and then
Population B and multiply by the
for Populations A and then
Population B and multiply by the
cost of our fake test.

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