Screening Tests
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Screening tests Natural history of disease prepathogenesis
pathogenesis X
Stage of prepathogenesis when there
are no symptoms of the disease
Stage of pathogenesis, when the
disease manifests itself by certain symptoms and signs which bring the patient to the physician
There are two types of tests: Screening tests & diagnostic tests Purpose of screening tests:
To detect individuals with risk factors that
predispose to disease development, thus preventive interventions could be done (primary prevention) To identify persons with early or asymptomatic ( latent disease) that can be effectively treated leading to better outcome (secondary prevention)
Examples Overt carcinoma of the cervix is preceded by a stage when
cancer cells are localized called carcinoma in situ, if detected prevent the development of the disease
Senile keratosis of the skin ( benign lesion) has a great
probability of transformation to malignancy, so its detection and removal is a preventive measure
Thus detection in the prepathogenic state or early stages of the disease requires the examination of symptomless or apparently healthy individuals which means
Purpose of diagnostic tests It is to move the estimated probability of disease toward either
end of the probability scale. When the estimated probability of the disease is close to Zero, the disease can be ruled out, when the estimated likelihood of a disease is close to 100, the disease is confirmed
disease probability scale Zero probability
100% probability
(The test is used to measure the probability of an outcome(
Screening vs. diagnostic tests - Screening test is done in the prepathogenic state - Persons who are positive are more likely to have the disease, and who are negative are more likely not to have the disease - Applied to a pop. with low probability of the risk factor or disease prevalence relative to those with symptoms
- Diagnostic test is done in the pathogenic state -Persons may be positive or negative for the disease - Applied to a pop. with high probability of risk factor or disease prevalence relative to those with no symptoms
Criteria of the successful screening program The disease: The disease should be common enough (high
prevalence) to warrant a search for its risk factors or latent stages, because screening for rare disease leads to unacceptable cost- benefit ratios
The morbidity or mortality of the untreated condition
must be substantial (potential of screening)
An effective preventive intervention or therapy should
exist and should have a more beneficial outcome when applied to the prepathogenic than the pathogenic state
Criteria for a successful screening program:
The disease: - Early detection and intervention must improve disease outcome - The natural history of the disease should be
understood, such that the detectable prepathogenic stage is known and identifiable - Facilities for diagnosis and appropriate treatments should be available for individuals who screen positive
The screening test It must be suitable to the population and suitable for
routine application Maintenance of test accuracy over time and freedom
from screening related adverse effects A combination of the objective and subjective criteria
must be present
Criteria of screening tests
objective criteria
Operating characteristics
( sensitivity + specificity = validity) Predictive value ( positive &
negative) Cost effectiveness
Subjective criteria Individual and public
acceptability ( rapid, simple, painless, with no complications) Financing ( inexpensive
)
Screening test will divide examined apparently healthy population
Healthy
With abnormality
Being rapid and simple, screening test is subjected to many errors, so a confirmatory test must be done to evaluate its results. This will be applied for both healthy and people with abnormality as revealed by the screening test: confirmatory test
Healthy The test done to this group
will help to assure that none of them has the disease By this test some of the healthy will be fined to have the disease (false negative), and others will be negative for it ( true negative)
With abnormality The test done to this group
will help to assure that all of them really have the disease and none of them is negative for it So, by this test some of the population proved before to have the disease will be negative for it (false positive) and others will be proved to be positive for it ( true positive)
Screening test +ve
Confirmatory test +ve -ve a b
-ve
c
d
Total
a+c
b+d
total a+b c+d a+b+c+d
a) Individuals positive by the screening test are also positive by the confirmatory test (true positives) b) Individuals positive by the screening test , but negative by the confirmatory test ( false positives) c) Individuals negative by the screening test , but positive by the confirmatory test (false negatives) d) Individuals negative by the screening test and negative by the confirmatory test ( true negatives)
The overall validity =
a+d a+b+c+d
zero validity
% 100% validity
X
A 100% valid test is one that
A Zero % valid screening
has no false positives (b) or false negatives (c) results Which means that its results agree 100% with confirmatory test So, this screening test could be considered a diagnostic test (screening test= diagnostic test)
test doesn’t give any true positives (a) or true negatives (d) Which means that its results agree zero% with the confirmatory test ( this test must be rejected)
Sensitivity Definition: It is the ability of the test to give positive results in
diseased population .It is the percentage of persons with the disease of interest who have +ve test results= a/a+c x100,(by relating the true positives by the screening test to all positives by the confirmatory test The greater the sensitivity of the test, the more likely that the
test will detect persons with the disease of interest Tests of high sensitivity are important to rule out the disease,
that is a –ve result would virtually exclude the possibility that the patient has the disease of interest
specificity Definition : It is the ability of the test to give negative results in free
population. It is the percentage of persons without the disease of interest who have –ve test results = d/ d+b x 100, ( by relating the true negatives by the screening test to all negatives by the confirmatory tests The greater the specificity, the more likely that persons without the
disease of interest will be excluded by the test. Very specific tests are used to confirm the presence of the disease If the test is highly specific, a positive test result would strongly
implicate the disease of interest
The effect of false positives: - False positives tend to swamp true positives in population, because most diseases we test for are rare
The effect of false negatives: - Delayed intervention - disregard of early signs and symptoms which may lead to delayed diagnosis
Risks of screening: Labeling effect: individuals truly diagnosed to have the disease will be positive for the disease to the end. Some of the individuals who were finally truly diagnosed
as not having the disease may be diagnosed as having the disease by the screening test (false positives), these may path through psychic trauma, spent unexpected money to reach the final diagnosis of being healthy
Relation between sensitivity and specificity: sensitivity and specificity are inversely related +ve -ve
total
+ve -ve
+ve
14
8
22
+ve
-ve
1
91
92
-ve
total
15
99
114
total
10 (a) 5 (c ) 15
12 (b) 87 (d) 99
total 22 92 114
Sensitivity=a/a+cx100=14/15x 100=93%
Sensitivity=a/a+cx100=10/15x 100=66.6%
Specificity= d/d+bx100= 91/99x100 = 92%
Specificity= d/d+bx100=87/99x100=87.8%
Predictive values Whereas the operating criteria of a test are of major
help in selecting a screening test, the predictive value of a test is a major aid in interpretation of results. The operating criteria of a test are descriptors of
accuracy of a test, the predictive values are estimations of disease probability
+ve predictive value: It is the probability of the presence of the
disease given the test result is positive. It is the percentage of persons with +ve test results who actually have the disease of interest =(a/a+b)x100
-ve predictive value: It is the probability of the absence of the
disease given the test result is negative. It is the percentage of persons with –ve test results who actually have not the disease of interest= (d/d+c)x100
Relation between predictive values and disease prevalence: screening in women with no breast mass
+ve -ve
screening in women with breast mass
total
+ve
-ve
total
+ve
14
8
22
+ve
113
15
128
-ve
1
91
92
-ve
8
181
189
total
15
99
114
total
121
196
317
Prevalence=15/114x100= 13% Sensitivity =14/15x100=93% Specificity=91/99x100=92% +pv=14/22x100=64% -pv=91/92x100=99%
Prevalence=121/317x100=38% Sensitivity=113/121x100=93% Specificity= 181/196x100=92% +pv= 113/128x100=88% -pv=181/189x100=96%
Sources of bias in the evaluation of a screening program: Lead time bias Length bias Volunteer bias
Lead time bias: Lead time: it is the interval between the diagnosis of
a disease at screening and the usual time of diagnosis by symptoms lead time I diagnosis by screening
I diagnosis by symptoms
Lead time bias: Consider a condition where the natural history allows
for an earlier diagnosis, however survival does not improve despite identifying it earlier - The 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 of screening from the survival standpoint
Lead time bias: Assume survival is the time between screen and
death Does not into account the lead time between diagnosis at screening and usual diagnosis survival=14 years
I diagnosis by screening in 1994
I death in 2008
Lead time bias survival=14 years
I
I true survival=10 years
lead time 4 years
I
I
I
diagnosis
usual time of
death
by screening in 1994
diagnosis via symptoms in 1998
in 2008
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 the disease developed rapidly Screening will preferentially pick up slowly developing
disease (longer opportunity to be screened) which usually has a better prognosis
O
P
biological onset of disease
Y
disease detectable via screening
D
symptoms begin
death
Screening O
P O
O
P Y
O
Y P
D Y
D
P
Y
D
O O
D
P
P Y
Y
D D
Time
Volunteer bias: This occurs when those accept to participate are
different from the others Volunteers tend to have:
- better health - lower mortality - likely to adhere to prescribed medical regimens
Screening in breast cancer There is an evidence of effectiveness that breast physical
ex.& breast mamography done annually to women above 50years will reduce mortality of breast cancer Risks : Each rad of radiation delivered to the breast increases woman’s chance to develop breast cancer by 6/1000.000/year. This increases for developing breast cancer by less than 1% each time False positive results occur in 1.5% of examination, which leads to biopsies that are unnecessary. cost effectiveness: is measured by comparing the reduction in mortality achieved with the financial costs of screening
*2/3 of the effectiveness of breast cancer screening program can be achieved by screening with physical examination only * Adding mammography increases the effectiveness more than 50% but increases the cost *The cost of increasing life expectancy by reducing mortality from cancer= 5000$ for physical ex. * Adding annual mamography gains additional year of life expectancy at a cost of 25000$
Conclusion
Sensitivity will determine the number of diseased people that will be missed (false -ve) and this increases when sensitivity decreases.
Specificity will determine the number of well people wrongly included as diseased ( false positive) and this increases when specificity decreases.
A test with false positives gives false alarm and psychological trauma
A test with false negatives gives a false sense of security and the disease may progress to non-curable stage
High disease prevalence will increase the + pv and decrease the - pv
pathogenesis X
Stage of prepathogenesis when there
are no symptoms of the disease
Stage of pathogenesis, when the
disease manifests itself by certain symptoms and signs which bring the patient to the physician
There are two types of tests: Screening tests & diagnostic tests Purpose of screening tests:
To detect individuals with risk factors that
predispose to disease development, thus preventive interventions could be done (primary prevention) To identify persons with early or asymptomatic ( latent disease) that can be effectively treated leading to better outcome (secondary prevention)
Examples Overt carcinoma of the cervix is preceded by a stage when
cancer cells are localized called carcinoma in situ, if detected prevent the development of the disease
Senile keratosis of the skin ( benign lesion) has a great
probability of transformation to malignancy, so its detection and removal is a preventive measure
Thus detection in the prepathogenic state or early stages of the disease requires the examination of symptomless or apparently healthy individuals which means
Purpose of diagnostic tests It is to move the estimated probability of disease toward either
end of the probability scale. When the estimated probability of the disease is close to Zero, the disease can be ruled out, when the estimated likelihood of a disease is close to 100, the disease is confirmed
disease probability scale Zero probability
100% probability
(The test is used to measure the probability of an outcome(
Screening vs. diagnostic tests - Screening test is done in the prepathogenic state - Persons who are positive are more likely to have the disease, and who are negative are more likely not to have the disease - Applied to a pop. with low probability of the risk factor or disease prevalence relative to those with symptoms
- Diagnostic test is done in the pathogenic state -Persons may be positive or negative for the disease - Applied to a pop. with high probability of risk factor or disease prevalence relative to those with no symptoms
Criteria of the successful screening program The disease: The disease should be common enough (high
prevalence) to warrant a search for its risk factors or latent stages, because screening for rare disease leads to unacceptable cost- benefit ratios
The morbidity or mortality of the untreated condition
must be substantial (potential of screening)
An effective preventive intervention or therapy should
exist and should have a more beneficial outcome when applied to the prepathogenic than the pathogenic state
Criteria for a successful screening program:
The disease: - Early detection and intervention must improve disease outcome - The natural history of the disease should be
understood, such that the detectable prepathogenic stage is known and identifiable - Facilities for diagnosis and appropriate treatments should be available for individuals who screen positive
The screening test It must be suitable to the population and suitable for
routine application Maintenance of test accuracy over time and freedom
from screening related adverse effects A combination of the objective and subjective criteria
must be present
Criteria of screening tests
objective criteria
Operating characteristics
( sensitivity + specificity = validity) Predictive value ( positive &
negative) Cost effectiveness
Subjective criteria Individual and public
acceptability ( rapid, simple, painless, with no complications) Financing ( inexpensive
)
Screening test will divide examined apparently healthy population
Healthy
With abnormality
Being rapid and simple, screening test is subjected to many errors, so a confirmatory test must be done to evaluate its results. This will be applied for both healthy and people with abnormality as revealed by the screening test: confirmatory test
Healthy The test done to this group
will help to assure that none of them has the disease By this test some of the healthy will be fined to have the disease (false negative), and others will be negative for it ( true negative)
With abnormality The test done to this group
will help to assure that all of them really have the disease and none of them is negative for it So, by this test some of the population proved before to have the disease will be negative for it (false positive) and others will be proved to be positive for it ( true positive)
Screening test +ve
Confirmatory test +ve -ve a b
-ve
c
d
Total
a+c
b+d
total a+b c+d a+b+c+d
a) Individuals positive by the screening test are also positive by the confirmatory test (true positives) b) Individuals positive by the screening test , but negative by the confirmatory test ( false positives) c) Individuals negative by the screening test , but positive by the confirmatory test (false negatives) d) Individuals negative by the screening test and negative by the confirmatory test ( true negatives)
The overall validity =
a+d a+b+c+d
zero validity
% 100% validity
X
A 100% valid test is one that
A Zero % valid screening
has no false positives (b) or false negatives (c) results Which means that its results agree 100% with confirmatory test So, this screening test could be considered a diagnostic test (screening test= diagnostic test)
test doesn’t give any true positives (a) or true negatives (d) Which means that its results agree zero% with the confirmatory test ( this test must be rejected)
Sensitivity Definition: It is the ability of the test to give positive results in
diseased population .It is the percentage of persons with the disease of interest who have +ve test results= a/a+c x100,(by relating the true positives by the screening test to all positives by the confirmatory test The greater the sensitivity of the test, the more likely that the
test will detect persons with the disease of interest Tests of high sensitivity are important to rule out the disease,
that is a –ve result would virtually exclude the possibility that the patient has the disease of interest
specificity Definition : It is the ability of the test to give negative results in free
population. It is the percentage of persons without the disease of interest who have –ve test results = d/ d+b x 100, ( by relating the true negatives by the screening test to all negatives by the confirmatory tests The greater the specificity, the more likely that persons without the
disease of interest will be excluded by the test. Very specific tests are used to confirm the presence of the disease If the test is highly specific, a positive test result would strongly
implicate the disease of interest
The effect of false positives: - False positives tend to swamp true positives in population, because most diseases we test for are rare
The effect of false negatives: - Delayed intervention - disregard of early signs and symptoms which may lead to delayed diagnosis
Risks of screening: Labeling effect: individuals truly diagnosed to have the disease will be positive for the disease to the end. Some of the individuals who were finally truly diagnosed
as not having the disease may be diagnosed as having the disease by the screening test (false positives), these may path through psychic trauma, spent unexpected money to reach the final diagnosis of being healthy
Relation between sensitivity and specificity: sensitivity and specificity are inversely related +ve -ve
total
+ve -ve
+ve
14
8
22
+ve
-ve
1
91
92
-ve
total
15
99
114
total
10 (a) 5 (c ) 15
12 (b) 87 (d) 99
total 22 92 114
Sensitivity=a/a+cx100=14/15x 100=93%
Sensitivity=a/a+cx100=10/15x 100=66.6%
Specificity= d/d+bx100= 91/99x100 = 92%
Specificity= d/d+bx100=87/99x100=87.8%
Predictive values Whereas the operating criteria of a test are of major
help in selecting a screening test, the predictive value of a test is a major aid in interpretation of results. The operating criteria of a test are descriptors of
accuracy of a test, the predictive values are estimations of disease probability
+ve predictive value: It is the probability of the presence of the
disease given the test result is positive. It is the percentage of persons with +ve test results who actually have the disease of interest =(a/a+b)x100
-ve predictive value: It is the probability of the absence of the
disease given the test result is negative. It is the percentage of persons with –ve test results who actually have not the disease of interest= (d/d+c)x100
Relation between predictive values and disease prevalence: screening in women with no breast mass
+ve -ve
screening in women with breast mass
total
+ve
-ve
total
+ve
14
8
22
+ve
113
15
128
-ve
1
91
92
-ve
8
181
189
total
15
99
114
total
121
196
317
Prevalence=15/114x100= 13% Sensitivity =14/15x100=93% Specificity=91/99x100=92% +pv=14/22x100=64% -pv=91/92x100=99%
Prevalence=121/317x100=38% Sensitivity=113/121x100=93% Specificity= 181/196x100=92% +pv= 113/128x100=88% -pv=181/189x100=96%
Sources of bias in the evaluation of a screening program: Lead time bias Length bias Volunteer bias
Lead time bias: Lead time: it is the interval between the diagnosis of
a disease at screening and the usual time of diagnosis by symptoms lead time I diagnosis by screening
I diagnosis by symptoms
Lead time bias: Consider a condition where the natural history allows
for an earlier diagnosis, however survival does not improve despite identifying it earlier - The 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 of screening from the survival standpoint
Lead time bias: Assume survival is the time between screen and
death Does not into account the lead time between diagnosis at screening and usual diagnosis survival=14 years
I diagnosis by screening in 1994
I death in 2008
Lead time bias survival=14 years
I
I true survival=10 years
lead time 4 years
I
I
I
diagnosis
usual time of
death
by screening in 1994
diagnosis via symptoms in 1998
in 2008
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 the disease developed rapidly Screening will preferentially pick up slowly developing
disease (longer opportunity to be screened) which usually has a better prognosis
O
P
biological onset of disease
Y
disease detectable via screening
D
symptoms begin
death
Screening O
P O
O
P Y
O
Y P
D Y
D
P
Y
D
O O
D
P
P Y
Y
D D
Time
Volunteer bias: This occurs when those accept to participate are
different from the others Volunteers tend to have:
- better health - lower mortality - likely to adhere to prescribed medical regimens
Screening in breast cancer There is an evidence of effectiveness that breast physical
ex.& breast mamography done annually to women above 50years will reduce mortality of breast cancer Risks : Each rad of radiation delivered to the breast increases woman’s chance to develop breast cancer by 6/1000.000/year. This increases for developing breast cancer by less than 1% each time False positive results occur in 1.5% of examination, which leads to biopsies that are unnecessary. cost effectiveness: is measured by comparing the reduction in mortality achieved with the financial costs of screening
*2/3 of the effectiveness of breast cancer screening program can be achieved by screening with physical examination only * Adding mammography increases the effectiveness more than 50% but increases the cost *The cost of increasing life expectancy by reducing mortality from cancer= 5000$ for physical ex. * Adding annual mamography gains additional year of life expectancy at a cost of 25000$
Conclusion
Sensitivity will determine the number of diseased people that will be missed (false -ve) and this increases when sensitivity decreases.
Specificity will determine the number of well people wrongly included as diseased ( false positive) and this increases when specificity decreases.
A test with false positives gives false alarm and psychological trauma
A test with false negatives gives a false sense of security and the disease may progress to non-curable stage
High disease prevalence will increase the + pv and decrease the - pv
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