Sensitivity & Speceficity diagnostic test (3).ppt

Dr Abdullah A.Almikhlafy
Diagnostic tests:
Sensitivity & Speceficity
09/29/24
Dr-Abdullah A.Almikhlafy

In a perfect world, medical tests would always
be correct. For example, women could undergo
a diagnostic test that would unequivocally
determine whether breast cancer was present
and the test would have no side effects.
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A positive test result would indicate that cancer was
present and a negative test result would indicate that cancer
was absent. In reality, however, every test is fallible.
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A 54-year-old high school teacher visited her family practitioner for
an annual checkup. She reported no illnesses during the preceding
year, felt well, and had no complaints. The hot flashes she had
experienced a year ago had resolved without treatment.
The results of the mammogram were not normal, and the radiologist
suggested that a breast biopsy be performed. The family practitioner
notified the patient of the abnormal mammogram and referred her
to a surgeon, who concurred that physical examination of the breast
was normal.
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Based on the mammographic abnormality, however, the surgeon
and the radiologist agreed that fine-needle aspiration (FNA) of the
abnormal breast under radiologic guidance was indicated. Evaluation
of the FNA specimen by a pathologist revealed cancer cells, and the
patient was scheduled for further surgery the following week.
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Performance characteristics of a test:
• Sensitivity
• Specificity
• Positive predictive value of a test (PPV)
• Negative predictive value of a test (NPV)
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• Choice of a threshold.
• Impact of disease prevalence, sensitivity and
specificity on predictive values.
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Population with affected and non-affected
individuals
Affected
Non-affected
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A perfect diagnostic test identifies the affected
individuals only
Affected
Non-affected
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In reality, tests are not perfect
Affected
Non-affected
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Format for comparison of the results of a diagnostic test with the
"true" status of a disease.
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Any diagnostic test can be evaluated in this manner. The
first step in the evaluation of a test is determining the
"true" status of the disease.
The "true" status of the disease is determined by the (gold standard test)
Gold Standard Test:
Definition: The diagnostic test that is considered the most
accurate test for a particular condition. If the gold standard
test is positive, it is highly likely that the person has the
disease. If the gold standard test is negative, it is highly likely
that the person does not have the disease.
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Sensitivity and specificity are
terms used to describe the
validity of the FNA test relative
to the surgical excisional biopsy.

Sensitivity
The sensitivity of a test is defined as the percentage of
persons with the disease of interest who have positive
test results.
What is the complement of sensitivity ???
09/29/24
It is defined as the fraction of the diseased who
test positive.

Estimating the sensitivity of a test
 Identify affected individuals with a gold standard.
 Obtain a wide panel of samples that are representative
of the population of affected individuals.
 Test the affected individuals .
 Estimate the proportion of affected individuals that are
positive with the test.
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Comparison of FNA test results with findings from surgical
excisional biopsies in women without palpable breast masses.
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Sensitivity =TP / (TP + FN)
In our example what is the sensitivity of
the FNA test ???
Sensitivity = Probability ( T+ | D+ )
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The greater the sensitivity of a test, the more likely the test will
detect persons with the disease of interest.
For the FNA test, 93% of all the patients with breast cancer had
positive test results.
Tests with great sensitivity are useful clinically to rule out the
presence of a disease.
That is, a negative result would virtually exclude the possibility that
the patient has the disease of interest.
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Specificity
Specificity of a test is defined as the percentage of persons
without the disease of interest who have negative test
results.
Specificity is calculated as follows:
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In our example what is the specificity y of the FNA test ???

In our example, the specificity of the FNA test is:
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The greater the specificity of a test, the more likely it is
that persons without the disease of interest will be
excluded from consideration of having the disease.
Very specific tests often are used to confirm the presence of a
disease.
If the test is highly specific, a positive test result would strongly
suggest the presence of the disease of interest.
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Positive & Negative Predictive Value
Sensitivity and specificity are descriptors of the accuracy of
a test.
Two measures concerning the estimation of the probability
of the presence or absence of disease are the positive
predictive value (PV+
) (PPV) and the negative predictive
value (PV–
) (NPV) .
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The PV+
is defined as the percentage of persons with positive test
results who actually have the disease of interest.
The PV+
therefore allows us to estimate how likely it is that the
disease of interest is present if the test is positive.
The PV+
is calculated as follows:
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The PV+
is the percentage of persons with positive test
results who have the disease. The calculation of the PV+
for the FNA test is:
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The average probability of breast cancer among women in this
sample prior to the FNA test was 15 affected women out of 114
total women, or 13%. After the FNA test, the probability of breast
cancer for a woman with a positive test result increased to 64%.
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The PV–
is defined as the percentage of persons with negative test
results who do not have the disease of interest. The general
formula for the calculation of PV–
is:
For the FNA test data in our example, the PV–
is
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Before the FNA was performed, the average likelihood of not
having breast cancer among women in this sample was 99
unaffected women out of 114 total women, or 87%.
After a negative FNA result, the probability of not having breast
cancer increased to 99%.
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Now that the post-FNA probability of disease has been calculated
for either a positive or negative test result, the usefulness of the
FNA test for a patient with a nonpalpable breast lesion can be
considered.
A positive test result increased the probability of breast cancer
from 13% to 64%. Whether the probability of breast cancer is 13%
or 64%, further work-up is indicated.
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Both before and after a positive FNA result, the clinician
would conclude that the likelihood of breast cancer was too
great to forego a test such as a surgical biopsy, which would
provide the most definitive diagnosis.
09/29/24

Sensitivity & Speceficity diagnostic test (3).ppt

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