Transcript South Asian Cardiovascular Research Methodology Workshop Basic Epidemiology Screening and its Useful Tools Thomas Songer, PhD.

South Asian Cardiovascular
Research Methodology Workshop
Basic Epidemiology
Screening and its Useful Tools
Thomas Songer, PhD
Screening
• The early detection of
– disease
– precursors of disease
– susceptibility to disease
in individuals who do not show
any signs of disease
Goel
Purpose of Screening
• Aims to reduce morbidity and mortality from
disease among persons being screened
• Is the application of a relatively simple,
inexpensive test, examinations or other
procedures to people who are asymptomatic,
for the purpose of classifying them with respect
to their likelihood of having a particular
disease
• a means of identifying persons at increased
risk for the presence of disease, who warrant
further evaluation
Diagnosis = Screening
• Screening tests can also often be used as
diagnostic tests
• Diagnosis involves confirmation of
presence or absence of disease in someone
suspected of or at risk for disease
• Screening is generally in done among
individuals who are not suspected of
having disease
Natural History of Disease
Detectable subclinical disease
Susceptible
Host
Subclinical
Disease
Point of
Exposure
Clinical
Disease
Diagnosis
sought
Onset of
symptoms
Screening
Stage of Recovery,
Disability, or Death
Screening Process
Population
(or target group)
Screening
Test
Negative
Test
Positive
Unaffected
Affected
Re-screen
Intervene
Clinical
Exam
Examples of Screening Tests
•
•
•
•
•
Questions
Clinical Examinations
Laboratory Tests
Genetic Tests
X-rays
Goel
Validity of Screening Tests
Key Measures
•
•
•
•
Sensitivity
Specificity
Positive Predictive Value
Negative Predictive Value
Paneth
Terminology
Validity is analogous to accuracy
The validity of a screening test is how
well the given screening test reflects
another test of known greater
accuracy
Validity assumes that there is a gold
standard to which a test can be
compared
Paneth
Screening
Test
Disease
Present
Absent
Positive
a
b
a+b
Negative
c
d
c+d
b+d
N
a+c
Screening
Test
Disease
Present
Absent
Positive
True
positives
False
positives
Negative
False
negatives
True
negatives
Sensitivity
Screening
Test
• Proportion of individuals who have the
disease who test positive (a.k.a. true
positive rate)
• tells us how well a “+” test picks up disease
Disease
yes no
+
-
a
c
b
d
a+c b+d
a+b
c+d
N
Sensitivity =
a
a+c
Specificity
Screening
Test
• Proportion of individuals who don’t
have the disease who test negative
(a.k.a. true negative rate)
• tell us how well a “-” test detects no
disease
Disease
yes no
+
-
a
c
b
d
a+c b+d
a+b
c+d
N
Specificity =
d
b+d
Screening Principles
• Sensitivity
– the ability of a test to correctly identify
those who have a disease
• a test with high sensitivity will have few false
negatives
• Specificity
– the ability of a test to correctly identify
those who do not have the disease
• a test that has high specificity will have few
false positives
Predictive Value
• Measures whether or not an individual
actually has the disease, given the results
of a screening test
• Affected by
– specificity
– prevalence of preclinical disease
– Sensitivity
• Prevalence =
a+c
a+b+c+d
Screening
Test
Disease
Present
Absent
Positive
a
b
a+b
Negative
c
d
c+d
b+d
N
a+c
Positive Predictive Value
Screening
Test
• Proportion of individuals who test
positive who actually have the disease
Disease
yes no
+
-
a
c
b
d
a+c b+d
a+b
c+d
N
P.P.V.
=
a
a+b
Negative Predictive Value
Screening
Test
• Proportion of individuals who test
negative who don’t have the disease
Disease
yes no
+
-
a
c
b
d
a+c b+d
a+b
c+d
N
N.P.V.
=
d
c+d
A test is used in 50 people with disease and
50 people without. These are the results.
Screening
Test
Disease
Present
Absent
Positive
48
3
51
Negative
2
47
49
50
50
100
Paneth
Screening
Test
Disease
Present
Absent
Positive
48
3
51
Negative
2
47
49
50
50
100
Sensitivity = 48/50
Specificity = 47/50
Positive Predictive Value = 48/51
Negative Predictive Value = 47/49
Paneth
So… you understand the
accuracy of a screening test …
What is the next step?
Put screening to use in the
population
Considerations in Screening
Severity
Prevalence
Understand Natural History
Diagnosis & Treatment
Cost
Efficacy
Safety
Criteria for a Successful
Screening Program
• Disease
– present in population screened
– high morbidity or mortality; must
be an important public health
problem
– early detection and intervention
must improve outcome
Criteria for a Successful
Screening Program
• Disease
– The natural history of the disease
should be understood, such that
the detectable sub-clinical disease
stage is known and identifiable
Criteria for a Successful
Screening Program
• Screening Test
– should be relatively sensitive and
specific
– should be simple and inexpensive
– should be very safe
– must be acceptable to subjects and
providers
Criteria for a Successful
Screening Program
• Have an Exit Strategy
– Facilities for diagnosis and appropriate
treatments should be available for
individuals who screen positive
– It is unethical to offer screening when
no services are available for
subsequent treatment
Screening Strategies
High-Risk Strategy
• Cost-effective
• Intervention
appropriate to the
individual
• Fails to deal with the
root causes of disease
• Subjects motivated
• Small chance of
reducing disease
incidence
Population Approach
• Potential to alter the
root causes of disease
• Large chance of
reducing disease
incidence
• Small benefit to the
individual
• Poor subject motivation
• Problematic risk-benefit
ratio
NCI Guidelines for Screening
Mammography
“There is a general consensus among experts that
routine screening every 1-2 years with
mammography and clinical breast exam can
reduce breast cancer mortality by about onethird for women ages 50 and over.”
“Experts do not agree on the role of routine
screening mammography for women ages 40 to
49. To date, RCTs have not shown a statistically
significant reduction in mortality in this age.”
Screening is not
always free of risk
In population screening….
False positives tend to swamp true
positives in populations, because most
diseases we test for are rare
Paneth
Risks of Screening
• True Positives
– “labeling effect” (classified as diseased
from the time of the test forward)
• False Positives
– anxiety
– fear of future tests
– monetary expense
Risks of Screening
• False Negatives
– delayed intervention
– disregard of early signs or symptoms
which may lead to delayed diagnosis
Sources of Bias in the Evaluation
of Screening Programs
• Lead time bias
• Length bias
• Volunteer bias
Lead time bias
• Lead time: interval between the diagnosis of a
disease at screening and the usual time of
diagnosis (by symptoms)
Lead Time
Diagnosis
by screening
Diagnosis
via symptoms
Bias in Screening:
Lead-Time Bias
•Consider a condition where the natural history
allows for an earlier diagnosis, however, survival
does not improve despite identifying it earlier
•A screening program here will…
– over-represent earlier diagnosed cases
– survival will appear to increase
• but in reality, it is increased by exactly the
amount of time their diagnosis was advanced by
the screening program
– Thus there is no benefit to screening from a
survival standpoint.
Lead time bias
• Assumes survival is time between screen and
death
• Does not take into account lead time between
diagnosis at screening and usual diagnosis.
Survival = 14 years
Diagnosis
by screening
in 1994
Death
in 2008
Lead time bias
Survival = 14 years
True Survival = 10 years
Lead Time 4 years
Diagnosis
by
screening
in 1994
Usual time of
diagnosis
via symptoms
in 1998
Death
in 2008
Bias in Screening:
Length Bias
• Most chronic diseases, especially cancers, do
not progress at the same rate in everyone.
• Any group of diseased people will include some
in whom the disease developed slowly and some
in whom it developed rapidly.
• Screening will preferentially pick up slowly
developing disease (longer opportunity to be
screened) which usually has a better prognosis
Paneth
O
P
Y
D
Biological
onset of
disease
Disease
detectable
via screening
Symptoms
Begin
Death
Length bias
Screening
O
P
O
O
P
Y
O
Y
P
D
Y
D
P
Y
O
O
D
P
Y
D
P
Y
D
D
Time
Volunteer bias
• Type of bias where those who choose to
participate are likely to be different from
those who don’t
• Volunteers tend to have:
– Better health
– Lower mortality
– Likely to adhere to prescribed medical
regimens