Chapter 13 slides

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How do we delay disease
progress once it has started?
Epidemiology matters: a new introduction to methodological foundations
Chapter 13
1. What is screening?
2. When should we screen?
3. How do we evaluate a screening test?
4. How do we decide on a cut-off?
5. PPV, NPV, and prevalence
6. From screening test to screening program
7. Summary
Epidemiology Matters – Chapter 13
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1. What is screening?
2. When should we screen?
3. How do we evaluate a screening test?
4. How do we decide on a cut-off?
5. PPV, NPV, and prevalence
6. From screening test to screening program
7. Summary
Epidemiology Matters – Chapter 13
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Screening
Screening is the process in which we use a test to
determine whether an individual likely has a particular
health indicator or not or is likely to develop a particular
health indicator or not
Screening is not the same as diagnosis; screening tests give
us information about whether the disease is likely to be
present
A screening test assesses the presence of an underlying
marker that is associated with outcome of interest
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Screening, examples
 Women receive regular screening tests beginning in
young adulthood for cervical cancer (Pap smear)
 Physicians assess blood pressure and cholesterol as
screening tools for the development of cardiovascular
disease
 Women use home pregnancy tests to screen for presence
of an embryo or fetus
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1. What is screening?
2. When should we screen?
3. How do we evaluate a screening test?
4. How do we decide on a cut-off?
5. PPV, NPV, and prevalence
6. From screening test to screening program
7. Summary
Epidemiology Matters – Chapter 13
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When to screen
We screen for disease when we have the opportunity to reduce costs and risk
associated with diagnoses on large proportions of at-risk individuals
1.
We screen for health indicators that affect population health principally,
not for rare diseases (although there are exceptions for rare diseases
screen in utero)
2.
There should be sufficient time between biological onset of disease and
appearance of signs and symptoms of the disease exist so that screening
could detect the presence of the disease earlier than it would come to
clinical attention
3.
There should be available treatment for the disease so that early
detection improves the lives of affected
4.
Screening tests should be cheaper and less invasive than best available
diagnostic tool
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1. What is screening?
2. When should we screen?
3. How do we evaluate a screening test?
4. How do we decide on a cut-off?
5. PPV, NPV, and prevalence
6. From screening test to screening program
7. Summary
Epidemiology Matters – Chapter 13
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Screening test evaluation
1. Sensitivity
2. Specificity
3. Positive predictive value
4. Negative predictive value
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Screening test evaluation
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Screening test evaluation, example
Questions: Should all men be tested for prostate cancer
with the new screening tool?
 High rates of prostate cancer among Farrlandian men
 New test characterizes level of antigen in blood
demonstrated to be associated with prostate cancer
 Test is inexpensive and requires only a blood specimen
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Screening test evaluation, example
 240 men with confirmed incident diagnoses of
prostate cancer
 2,500 men confirmed free of prostate cancer
 Measure antigen level for all men
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Screening test evaluation
antigen among sample
D-
D+
Antigen
Mean level of antigen is higher among men with prostate cancer
Distributions of antigen overlap
 Between 37 and 56 ng/mL - both diseased and non-diseased men
 A cut-off if typically declared within this uncertain range
 Individuals above the cut-off are screening positive or below, screen negative
 Cut-off is often largely arbitrary and informs performance of screening test
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Screening test evaluation
sensitivity and specificity
 To assess the validity of a screening tool in
establishing the presence of disease we compare
with a gold standard
 Sensitivity: Whether individuals with disease are
correctly identified by the screening test as having
the disease
 Specificity: Whether individuals without the disease
are correctly identified by the screening test as not
having the disease
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Screening test evaluation
cut-off
Screening Cut-Off
 Screens
Negative
Screens 
Positive
D-
Antigen
D+
False Positives
Lowest value on the antigen distribution of men with prostate cancer = 38 ng/mL.
Cut-off score = 38 ng/mL
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Screening test evaluation
sensitivity
Among those with disease, what proportion does the screening test detect?
Interpretation: With a cut-off of 38 ng/mL, we have a test with 100% sensitivity.
Among those with prostate cancer, the test captures all cases. There are no false
negatives.
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Screening test evaluation
specificity
Among those without disease, what proportion does the screening test correctly
identify as disease free?
Interpretation: With a cut-off of 38 ng/mL, screening test classifies 61.2% of men
without prostate cancer as not having prostate cancer, remaining 38.8% are false
positive cases.
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Screening test evaluation
sensitivity and specificity tradeoffs
Test cut-off is very sensitive: All those who have the
disease will be captured by the test
Test cut-off is very specific: Individuals who do not have the
disease are will not screen positive
High sensitivity/low specificity tests are common in
practice; i.e., we will not miss many individuals with disease
but we also will screen positive those who do not have
disease
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Screening test evaluation
sensitivity and specificity, example
 Primary care physicians query patients about whether they engaged
in at least one episode of heavy drinking in the past year as a
screening tool for identifying individuals with an alcohol disorder
 Almost all individuals with an alcohol disorder will have engaged in at
least one episode of heavy drinking in the past year, but many
individuals without an alcohol disorder may have engaged in one or
more heavy drinking episodes as well.
 The test is sensitive, but not specific
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Screening test evaluation
PPV, NPV, and prevalence
How well does our screening test predict who is
diseased and who is not?
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Screening test evaluation
positive predictive value
Among those who screen positive, what proportion actually has the disease?
Interpretation: With a cut-off of 38 ng/mL, one fifth of the men who screen positive
on test have prostate cancer, leaving about 80% of men screening positive falsely.
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Screening test evaluation
negative predictive value
Among those who screen negative, what proportion actually do not have the
disease?
Interpretation: With a cut-off of 38 ng/mL, the test has perfect negative predictive
value. Among those who are negative on the screening test, we can be perfectly
confident that none of those individuals actually have the disease.
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Screening test evaluation
Assess sensitivity and specificity to understand the proportion
of diseased and non-diseased individuals correctly categorized as
diseased and non-diseased
Assess PPV and NPV to understand the proportion of positively
screened and negatively screened individuals that have disease
or are disease-free
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Screening test evaluation
cut-offs and tradeoffs, example
 Hypothetical screening test for prostate cancer set a
cut-off of 38 ng/mL
 Perfect sensitivity and negative predictive value
 Low specificity and positive predictive value
 Change cut-off for positivity to 45 ng/mL
 Individuals are positive on screening test if level of
antigen is 45 ng/mL or above
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Screening test evaluation
cut-offs and tradeoffs, example
Compared with original cut-off of ≥ 38 ng/mL
 Sensitivity decreased and specificity increased
 Positive predictive value increased
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Screening test evaluation
cut-offs and tradeoffs
Original cut-off
Why did sensitivity decrease?
Epidemiology Matters – Chapter 13
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Screening test evaluation
cut-offs and tradeoffs
Original cut-off
Why did sensitivity decrease?
Some individuals who have prostate cancer will
screen negative now - false negatives
As increase cut-off for positivity on a screening
test, number of individuals with the disease
who screen negative will increase - leading to
lower sensitivity
Epidemiology Matters – Chapter 13
New cut-off
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Screening test evaluation
cut-offs and tradeoffs
Sensitivity
Specificity
PPV
NPV
Numerator
Denominator
Numerator
Denominator
Numerator
Denominator
Numerator
Denominator
TP
TP + FN
TN
TN + FP
TP
TP + FP
TN
TN + FN
Effect of increasing a screening cut-off
Increase
Decrease in sensitivity
number of FN
Decrease
Increase in specificity
number of FP
Decrease
Increase in PPV
number of FP
Increase
Decrease in NPV
number of FN
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1. What is screening?
2. When should we screen?
3. How do we evaluate a screening test?
4. How do we decide on a cut-off?
5. PPV, NPV, and prevalence
6. From screening test to screening program
7. Summary
Epidemiology Matters – Chapter 13
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Ramifications of false positives vs.
false negatives
Low rate of false negatives preferred
 Infectious diseases critical to maintain low rate of false
negative
 When disease can be readily remediated if caught early but
devastating if not
Low rate of false positivity preferred
 When subsequent diagnostic test is invasive and expensive
procedures
 Screening is done routinely on low burden diseases
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A note
Empirical guidelines for screening can be created to optimize
screening cut-points; these are usually derived from receiver
operating characteristic (ROC) curves
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Multiple-stage screening
Two-stage screening test
1. Screen individuals using test with high sensitivity
2. Follow-up with test with high specificity
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1. What is screening?
2. When should we screen?
3. How do we evaluate a screening test?
4. How do we decide on a cut-off?
5. PPV, NPV, and prevalence
6. From screening test to screening program
7. Summary
Epidemiology Matters – Chapter 13
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Prevalence of screening health
indicator, example

Antigen screening test

Cut-off of 45 ng/mL

Screen two samples for prostate cancer
A. 1,500 men with prostate cancer family history; > 60
years old
B. 1,500 men with no prostate cancer family history; 40-60
years old
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Prostate cancer screening, sample A
Men with prostate cancer family history and > 60
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Prostate cancer screening, sample B
Men with no prostate cancer family history and 40 - 60
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Prostate cancer screening example
Sensitivity and specificity

Sample A and Sample B sensitivity = 90%

Sample A and Sample B specificity = 83%
PPV, positive predictive value

Sample A (family history, >60) PPV = 72.7%

Sample B (no family history, 40-60) PPV = 3.4%
NPV, negative predictive value

Sample A (family history, >60) NPV = 94.5%

Sample B (no family history, 40-60) NPV = 99.9%
PPV and NPV differ across samples. Why?
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Why does PPV change?
PPV is dependent on the prevalence of a health indicator in screened population
As prevalence  probability that individual who screens positive will be true case 
As prevalence 
probability of being true negative case 
Sensitivity and specificity are not directly influenced by prevalence
Sensitivity and specificity look among those who have the health indicator versus those who do
not
PPV and NPV are dependent on prevalence, and PPV increases as the prevalence of disease
increases.
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1. What is screening?
2. When should we screen?
3. How do we evaluate a screening test?
4. How do we decide on a cut-off?
5. PPV, NPV, and prevalence
6. From screening test to screening program
7. Summary
Epidemiology Matters – Chapter 13
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Screening test to screening program
Example 1: Detection based on screening compared with
detection based on symptoms
Example 2: Detection based on screening compared with
effect of screening on mortality
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Example 1: Cancer duration in Farrlandia
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Example 1: Cancer duration in Farrlandia,
screening at 10 years
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Example 1: Cancer duration in
Farrlandia, screening at 10 years
Screening at single time point is estimating the prevalence of cancer at time point
Cancer cases that are more likely to be detected have long duration and perhaps slowgrowing tumors
Problems with this
1.
Slow-growing tumors may not eventually cause death or disability - difficult to
predict which tumors will become symptomatic and which will not
2.
Compare cancer-related mortality among screened sample to non-screened
sample

Screened group may have fewer cancer-related deaths because may have
better cancer-related outcomes

Because tumors that are detected more likely to be slow growing tumors
that did not influence morbidity and mortality
Length-time bias: Inability to estimate the causal impact of screening test on
morbidity and mortality
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Example 2: Disease detection by screening
vs. symptoms
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Example 2: Screening vs. symptom
diagnosis
Person 1’s cancer detected through screening
Person 2’s cancer detected due to symptoms
Person 1 and person 2 have equal time from cancer onset to death
Time from cancer detection to death is longer in Person 1
Lead time: The time from detection from screening and detection through
symptoms afforded by screening test. This will always show a benefit in the
screened group - even if early detection did not really lengthen life
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Example 2: Disease detection by screening
vs. symptoms
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Example 2: observation time
When time from start of observation to death is the same in
both individuals - no association between screening and length
of life
When the time from start of observation to death shorter for the
not screened compared with screened - evidence that early
detection through screening has benefit on mortality
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1. What is screening?
2. When should we screen?
3. How do we evaluate a screening test?
4. How do we decide on a cut-off?
5. PPV, NPV, and prevalence
6. From screening test to screening program
7. Summary
Epidemiology Matters – Chapter 13
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Summary

Screening for health indicators is integral part of improving
population health

Screening predicts who will develop a specific disease and detects
disease among those in early stages

Screening tests need to be studied for validity (sensitivity and
specificity)

We often have a trade-off between sensitivity and specificity

Predictive value of screening test is maximized in populations with
high prevalence of health indicator of interest

Value of screening program will depend on cost-effectiveness,
minimal invasiveness, availability of effective treatment
Epidemiology Matters – Chapter 13
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epidemiologymatters.org
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