Public Health Assignment

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Public Health Screening
Lecture 18
Some Examples of Screening Tests
Blood Screening of
Newborns for:
• PKU
• HIV
• Sickle Cell Disease, etc.
Screening (through a
Questionnaire) for
Depression
Fasting Plasma Glucose
Test for Type 2
Diabetes
Screening for High
Blood Pressure
(Hypertension)
Pap Smear for Cervical
Cancer
Genetic Screening of
Potential Parents
• Tay Sachs Disease
• Cystic Fibrosis
What is Screening for Disease?
Two Definitions
Screening–the presumptive
identification of unrecognized
disease or defects by the
application of tests,
examinations, or other
procedures that can be applied
rapidly.
Screening refers to the
application of a test to people
who are as yet asymptomatic
for the purpose of classifying
them with respect to their
likelihood of having a particular
disease.
The screening procedure itself does
NOT diagnose illness.
Why
Screen?
Positive screening results are followed
by diagnostic tests to confirm actual
disease.
The primary objective of screening is to
reduce mortality from disease through
early detection (secondary prevention).
Primary, Secondary and Tertiary Prevention
Primary
Prevention: the
prevention of disease
before it occurs. All
of the target
population is still
healthy.
Secondary Prevention:
limiting the progression of
the disease. The target
population is in the early
preclinical phases of the
disease, before symptoms
have appeared. Screening
is a form of secondary
prevention.
Tertiary Prevention:
restoring the patient’s
optimal functioning.
The target population
has symptoms of the
disease. They have all
been diagnosed with
it.
Examples of Primary Prevention
Getting
vaccinated
Getting vaccinated to avoid getting an infectious disease
regularly to avoid getting non-communicable
Exercising Exercising
diseases
Eating
healthy
Eating a healthy diet to avoid getting noncommunicable diseases
Getting a mammogram to screen
for early stages of breast cancer
Examples
of
Secondary
Prevention
Getting a colonoscopy to screen
for polyps which could develop
into colon cancer
Getting a blood test to screen for
high cholesterol, which could lead
to cardiovascular disease
Physical therapy for stroke patients to enable them
to recover as much function as possible
Examples
of Tertiary
Prevention
An exercise program appropriate for people with type
2 diabetes to keep their blood glucose levels as close
as possible to normal, and to prevent complications,
such as blindness or limb amputations
Medications to those who survived heart attacks to
prevent a second (and possibly fatal) attack.
Mass Screening and Selective Screening
• Mass screening–screening on a large scale
of total population groups regardless of risk
status.
• Selective screening–screens subsets of the
population at high risk for disease.
•
More economical, and likely to yield more
true cases.
•
Example: Screening high-risk persons for Tay-Sachs disease.
What is Tay-Sachs Disease?
•
•
•
Tay-Sachs Disease is a rare genetic disease passed
from parents to children. It is the genetic lack of an
enzyme that helps to break down fatty substances.
Without this enzyme fatty substances build up in the
brain and spinal cord, where they destroy nerve cells.
Around the age of 6 months, the child starts to show
signs of developmental problems. For instance the baby
loses the ability to turn over, sit up and crawl. The brain
continues to deteriorate, until death, usually around age
four.
Eastern and Central European Jews, French Canadians,
Cajuns and the Amish are at higher risk for having this
genetic disorder than other groups of people.
Selective screening would screen only people at high
risk for passing on this genetic disorder. A parent with
one such gene does not get the disease, but can pass it
on. A child with two such genes (one from each parent)
will develop Tay-Sachs disease.
• An implicit assumption underlying the
Criteria for
Screening
concept of screening is that early
detection, before the development of
symptoms, will lead to a more favorable
prognosis.
Appropriate
Situations
for
Screening
Tests and
Programs
Social
Scientific
Ethical
The health problem should be important for
the individual and the community.
Diagnostic follow-up and intervention
should be available to all who require them.
Social
There should be a favorable cost-benefit
ratio.
Public acceptance must be high.
• Natural history of the condition should be
adequately understood.
•
Scientific
This knowledge permits identification of early
stages of disease and appropriate biologic
markers of progression.
• Prevalence of the disease or condition is high.
• Prevalence of the preclinical stage of the disease
should be high in the general population.
The program can alter the natural history of the
condition in a significant proportion of those
screened.
Treatment given before symptoms develop
should be more beneficial than after symptoms
develop.
Suitable, acceptable tests for screening and
diagnosis of the condition as well as acceptable,
effective methods of prevention are available.
Ethical
Characteristics of a Good Screening Test
Simple–easy to
learn and perform.
Rapid–quick to
administer; results
available rapidly.
Acceptable–to
target group.
• Impose minimal
discomfort.
Inexpensive–good
cost-benefit ratio.
Valid (accurate)
Safe–no harm to
participants.
Reliable
(repeatable)
Reliability (Precision) of a Screening Test
The ability of a measuring
instrument to give
consistent results on
repeated trials.
Repeated measurement
reliability–the degree of
consistency among
repeated measurements
of the same individual on
more than one occasion.
Validity
(Accuracy) of
a Screening
Test
The ability of a
measuring
instrument to give a
true measure.
Can be evaluated
only if an
accepted and
independent
method for
confirming the
test
measurement
exists.
Representation of Reliability and Validity
Source of image: https://explorable.com/images/validity-and-reliability.jpg
Refers to the ability of the test to correctly
identify people who have the disease and those
who don’t. Two of the main components are:
Validity of
a Screening
Test
Sensitivity
Specificity
Measures of
the Validity of
Screening
Tests
Sensitivity–the ability of the test
to identify correctly all screened
individuals who actually have the
disease (a/a+c).
Specificity–the ability of the test
to identify correctly all screened
individuals who actually do not
have the disease (d/b+d).
How to
Determine
Sensitivity and
Specificity
• Sensitivity and Specificity are
determined by comparing the results
obtained by the screening test with
those derived from some definitive
diagnostic procedure.
2 By 2 Table
Gold
Standard
(Diagnostic Procedure)
Screening
Test Result
Disease
Present
Disease
Absent
Positive
Test Result
a
b
a+b
Negative
Test Result
Total
c
d
c+d
a+c
b+d
Total
Finding the Sensitivity of the Test with a 2X2 Table
Sensitivity = A / (A+C)
Test
Result
Tested
Positive
Tested
Negative
Total
Gold
Disease
Present
A
Standard
Disease
Absent
B
Total
a+b
Have disease
and + Test
No disease but
+ Test
All with +
Test
C
D
c+d
Have disease
but – Test
No disease and All with – Test
– Test
a+c
b+d
All Really
Diseased
All really not
diseased
Everyone
Screened
How
accurate is
the
screening
test in
identifying
people
with the
disease?
Finding the Specificity of the Test with a 2X2 Table
Specificity = D / (B+D)
Test
Result
Tested
Positive
Tested
Negative
Total
Gold
Disease
Present
A
Standard
Disease
Absent
B
Total
a+b
Have disease
and + Test
No disease but
+ Test
All with +
Test
C
D
c+d
Have disease
but – Test
No disease and All with – Test
– Test
a+c
b+d
All Really
Diseased
All really not
diseased
Everyone
Screened
How
accurate is
the
screening
test in
identifying
people
without
the
disease?
Interpretations
Sensitivity: Of the
truly diseased
persons, X % tested
positive.
Specificity: Of the
persons who truly do
not have the disease,
X% tested negative.
Example: Blood Test for Diabetes
Screening Test:
Single Fasting Blood
Glucose Test
Gold Standard: Oral
Glucose Tolerance Test
Gold Standard: Oral
Glucose Tolerance Test
Total
Positive for the Single
Fasting Blood Glucose
Test
35
15
50
Negative for the Single
Fasting Blood Glucose
Test
35
485
520
Total
70
500
570 Total Patients
Positive for the Oral
Glucose Tolerance Test
(Have Diabetes)
Negative for the Oral
Glucose Tolerance Test
(Don’t Have Diabetes)
Sensitivity
35/70 = 0.5 x 100 = 50%
Screening Test:
Single Fasting Blood
Glucose Test
Gold Standard: Oral
Glucose Tolerance Test
Gold Standard: Oral
Glucose Tolerance Test
Total
Positive for the Single
Fasting Blood Glucose
Test
35
15
50
Negative for the Single
Fasting Blood Glucose
Test
35
485
520
Total
70
500
570 Total Patients
Positive for the Oral
Glucose Tolerance Test
(Have Diabetes)
Negative for the Oral
Glucose Tolerance Test
(Don’t Have Diabetes)
Specificity
485/500 = 0.97 x 100 = 97%
Screening Test:
Single Fasting Blood
Glucose Test
Gold Standard: Oral
Glucose Tolerance Test
Gold Standard: Oral
Glucose Tolerance Test
Total
Positive for the Single
Fasting Blood Glucose
Test
35
15
50
Negative for the Single
Fasting Blood Glucose
Test
35
485
520
Total
70
500
570 Total Patients
Positive for the Oral
Glucose Tolerance Test
(Have Diabetes)
Negative for the Oral
Glucose Tolerance Test
(Don’t Have Diabetes)
Interpretations
Sensitivity: Of
those who truly had
diabetes, 50 %
tested positive.
Specificity: Of those
who truly did not
have diabetes, 97%
tested negative.
Relationships
of Sensitivity
and
Specificity
As sensitivity increases,
specificity decreases.
As specificity increases,
sensitivity decreases.
Better Specificity (Cut-Off at C)
Better Sensitivity (Cut-Off at A)
Relationship
Between
Sensitivity
and
Specificity
To improve sensitivity, the cut point
used to classify individuals as diseased
should be moved farther in the range
of the nondiseased (normals).
To improve specificity, the cut point
should be moved farther in the range
typically associated with the disease.
More
Measures
of the
Validity of
Screening
Tests
Positive Predictive Value –the
proportion of individuals screened
positive by the test who actually
have the disease (a/a+b).
Negative Predictive value–the
proportion of individuals screened
negative by the test who do not
have the disease (d/c+d).
Finding the Positive Predictive Value of the Test with a 2X2 Table
Positive Predictive Value = A / (A+B)
Test
Result
Tested
Positive
Tested
Negative
Total
Gold
Disease
Present
A
Standard
Disease
Absent
B
Total
a+b
Have disease
and + Test
No disease but
+ Test
All with +
Test
C
D
c+d
Have disease
but – Test
No disease and All with – Test
– Test
a+c
b+d
All Really
Diseased
All really not
diseased
Everyone
Screened
How
accurate is
a positive
value from
this
screening
test?
Finding the Negative Predictive Value of the Test with a 2X2 Table
Negative Predictive Value = D / (C+D)
Test
Result
Tested
Positive
Tested
Negative
Total
Gold
Disease
Present
A
Standard
Disease
Absent
B
Total
a+b
Have disease
and + Test
No disease but
+ Test
All with +
Test
C
D
c+d
Have disease
but – Test
No disease and All with – Test
– Test
a+c
b+d
All Really
Diseased
All really not
diseased
Everyone
Screened
How
accurate is
a negative
value from
this
screening
test?
Interpretations
Positive Predictive
Value: Of all the
persons who test
positive, X% are
truly diseased.
Negative
Predictive Value:
Of all the persons
who test
negative, X%
truly are disease
free.
Positive Predictive Value
35/50 = 0.7 x 100 = 70%
Screening Test:
Single Fasting Blood
Glucose Test
Gold Standard: Oral
Glucose Tolerance Test
Gold Standard: Oral
Glucose Tolerance Test
Total
Positive for the Single
Fasting Blood Glucose
Test
35
15
50
Negative for the Single
Fasting Blood Glucose
Test
35
485
520
Total
70
500
570 Total Patients
Positive for the Oral
Glucose Tolerance Test
(Have Diabetes)
Negative for the Oral
Glucose Tolerance Test
(Don’t Have Diabetes)
Negative Predictive Value
485/520 = 0.93 x 100 = 93%
Screening Test:
Single Fasting Blood
Glucose Test
Gold Standard: Oral
Glucose Tolerance Test
Gold Standard: Oral
Glucose Tolerance Test
Total
Positive for the Single
Fasting Blood Glucose
Test
35
15
50
Negative for the Single
Fasting Blood Glucose
Test
35
485
520
Total
70
500
570 Total Patients
Positive for the Oral
Glucose Tolerance Test
(Have Diabetes)
Negative for the Oral
Glucose Tolerance Test
(Don’t Have Diabetes)
Interpretations
Positive Predictive
Value: Of all those
who tested positive
for diabetes, 70%
truly had it.
Negative
Predictive Value:
Of all those who
tested negative
for diabetes, 93%
truly didn’t have
it.
Other Measures from the 2 by 2 Table
Accuracy (or yield) of
a screening test-determined by the
formula:
(a+d)/(a+b+c+d).
Prevalence-determined by the
formula:
(a+c)/(a+b+c+d)
Accuracy
(Yield)
Accuracy is a function of both
the positive predictive value and
the negative predictive value.
It indicates what proportion of
those screened tested correctly.
Finding the Accuracy of a Screening Test
Accuracy = (A+D) / (A+B+C+D)
Gold Standard
Present Absent
Test
Result
Positive
Negative
Total
A
B
True
Positives
False
Positives
C
D
False
Negatives
True
Negatives
a+c
b+d
Total
a+b
c+d
N
ALL
What is the
accuracy
(or yield) of
the
screening
test?
Accuracy or Yield
(35 + 485) / 570 = 0.91 x 100 = 91%
Screening Test:
Single Fasting Blood
Glucose Test
Gold Standard: Oral
Glucose Tolerance Test
Gold Standard: Oral
Glucose Tolerance Test
Total
Positive for the Single
Fasting Blood Glucose
Test
35
15
50
Negative for the Single
Fasting Blood Glucose
Test
35
485
520
Total
70
500
570 Total Patients
Positive for the Oral
Glucose Tolerance Test
(Have Diabetes)
Negative for the Oral
Glucose Tolerance Test
(Don’t Have Diabetes)
Interpretation
The overall
accuracy (or yield)
of the screening test
was X %.
The overall accuracy
of the fasting blood
glucose test for type
2 diabetes was 91%.
Finding the Prevalence of the Disease
(A + C) / (A+B+C+D)
Gold Standard
Present Absent
Test
Result
Positive
Negative
Total
Prevalence
A
B
True
Positives
False
Positives
C
D
False
Negatives
True
Negatives
a+c
b+d
All
Diseased
Total
a+b
c+d
N
ALL
What is the
prevalence
of the
disease in
the
population
being
screened?
Prevalence of Diabetes in this Group
70 / 570 = 0.12 x 100 = 12%
Screening Test:
Single Fasting Blood
Glucose Test
Gold Standard: Oral
Glucose Tolerance Test
Gold Standard: Oral
Glucose Tolerance Test
Total
Positive for the Single
Fasting Blood Glucose
Test
35
15
50
Negative for the Single
Fasting Blood Glucose
Test
35
485
520
Total
70
500
570 Total Patients
Positive for the Oral
Glucose Tolerance Test
(Have Diabetes)
Negative for the Oral
Glucose Tolerance Test
(Don’t Have Diabetes)
Effects of
Disease
Prevalence
on the
Predictive
Value of a
Screening
Test
As the prevalence of the disease in
the population goes up, the positive
predictive value also increases, and
the negative predictive value declines.
When the prevalence of a disease
falls, the predictive value (+) falls, and
the predictive value (-) rises.
Another
Sample
Calculation
Prevention of, or
reduction in
reoccurrences
Reduction in
mortality in the
population
screened
Reduction of
complications
Improvement in
the quality of
life in screened
individuals
What do
we want
to achieve
through a
screening
program?
Name: _______________________________________________________________________________
Homework #7: Screening
Due Tuesday, December 3rd by the End of the Day (11:59 p.m.)
24 Total Points, Plus up to 2 Extra Credit Points (6% of Grade)
This is an individual homework assignment. While you are allowed to use any notes, textbooks or
readings, and to consult with the faculty instructor, if having trouble, you are expected to think
through this assignment and do it on your own without the collaboration of classmates. You
should wait until after you have listened to Lecture #18, read pages 189-202 of the textbook before
starting this homework assignment. Remember to have your notes in front of you while doing this
homework.
Absolutely no late homework assignments will be accepted. Please type your answers,
numbering all of the questions. Show all steps in all calculations, including the numerators and
denominators. Express the final answers of all calculations as percentages.
Part 1: Screening for Hearing Impairment (24 points in Total plus up to 2 extra credit
points, 2 points each)
A study was carried out to evaluate a hand-held audiometer as a screening test to identify
hearing-impairment among the elderly. The sensitivity and specificity of the test were estimated
by giving the screening test to 300 elderly persons who had undergone complete audiometric
examinations. Based on the complete audiometric exam, 190 were determined to have normal
hearing, and 110 were determined to have impaired hearing. Results are presented in the
following table, which shows the distribution of elderly persons, by presence or absence of
hearing impairment, and by results of the screening test for hearing impairment.
2 by 2 Table for a Test of the Accuracy of a Hand-Held Audiometer in the Identification of
Hearing Impairment in the Elderly
Screening Test
(Hand Held
Audiometer)
Positive
Negative
Total
Hearing Impairment
Present
Hearing Impairment
Absent
Total
80
30
110
66
124
190
146
154
300
1) Calculate the sensitivity of the screening test (hand held audiometer).
2) Write a sentence interpreting your result in #1 (the sensitivity of the screening test).
3) Calculate the specificity of the screening test.
4) Write a sentence interpreting your result in #3 (specificity of the screening test).
1
Name: _______________________________________________________________________________
5) Calculate the positive predictive value of the screening test.
6) Write a sentence interpreting your result in #5 (positive predictive value).
7) Calculate the negative predictive value of the screening test.
8) Write a sentence interpreting your result in #7 (negative predictive value).
9) Calculate the overall accuracy (or yield) of the screening test.
10) Write a sentence interpreting your result for #9 (accuracy or yield of the screening test).
11) Extra Credit: Based on all of your results for #1, 3, 5, 7 and 9, would you say that the
hand held audiometer is worth using to screen the elderly for hearing loss? Why or why
not?
12) Calculate the prevalence of hearing impairment in this sample of 300 elderly people.
13) If the prevalence of hearing impairment was 10%, would the positive predictive value
increase, decrease or stay the same? Provide a brief explanation to support your answer.
2
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