Screening II
Criterion of Positivity test value at which the screening test outcome is considered positiveTest Result
Clearly Negative Grey Zone Clearly Positive
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A B C
Selection cutoff point:
Low Cutoff PointIn-Between Cutoff
High Cutoff Point
Which is Preferred: High Sensitivity or High Specificity?
If you have a fatal disease with no treatment (such as for early cases of AIDS), optimize specificityIf you are screening to prevent transmission of a preventable disease (such as screening for HIV in blood donors), optimize sensitivity
Considerations in selection of cut-point
Implications of false positive results
burden on follow-up services
labeling effect
Implications of false negative results
Failure to intervene
Two Stage Screening
Efficient technique to address the problem of cutoff point.
By using the results of several screening tests together (usually two).
A less expensive and less expensive test is carried out first and those who screen positive are recalled for further testing with a more expensive or invasive test.
E.g. Test 1: Blood Sugar and Test 2: glucose Tolerance Test.
These test are administer either:parallel: The 2 tests done at the same time, in general it increases Sensitivity but lower Specificity:
+ve +ve
+ve - ve +ve -ve -ve} -ve
-ve +ve
B. In series: Test after test, in general it increases Specificity but lower Sensitivity
-ve +ve
+ve - ve -ve +ve +ve} +ve
-ve -ve
Ex: 2 screening (I and II)test for DM
Results DM No DM Total
+ve I, -ve II 35 1541 1576-ve I, +ve II 135 591 726
+ve for both 315 359 674
-ve for both 15 7009 7024
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Total 500 9500 10000
Parallel:
Sensitivity= 485/500 X 100 = 97%Specificity= 7009/9500 X 100 =73.7%
In Series:
Sensitivity= 315/500 X 100 = 63%Specificity= 9141/9500 X 100 =96.2%
The apparent effectiveness of screening can also be influenced by biases. This is a common problem in screening. This can be:
Volunteer Bias
Volunteers are systematically different.
More health conscious?
More preventive health care?
More risk factors?
Volunteers tend to be healthier and to have lower rates of morbidity and mortality, no matter what the hypothesis under study is.
Dont discard a study just because its done on volunteers. Take the test with a grain of salt because your actual patient population might not do as well as the volunteer population in the study.
Lead-time Bias: identifying a disease in its pre-clinical detectable period can artificially create the impression that screen populations do better than unscreened.
The apparently better survival that is observed for those screened is not because these patients are actually living longer, but instead because diagnosis is being made at an earlier point in the natural history of the disease
--a patient typically lives 2 years after a certain disease is clinically evident
--the screening test detects disease 3 years before disease is clinically evident
--if the patient lives 5 years after detection, this is really no better than before the screening test was available can phase-shift the disease
because of lead-time bias, it is necessary to look at disease-specific and age-specific death rates in screened and unscreened groups when assessing a screening intervention.
Time from diagnosis to death does not tell you if a screening test is effective. Instead, look for age adjusted mortality.
Detection bias. A potential artifact in epidemiologic data caused by the use of a particular diagnostic technique or type of equipment.
EX: cancer rates may vary in different regions or periods, not because of an actual difference in the incidence of the disease but because of different diagnostic technologies.
Length bias
Examples of Preventive Health Care Screening:
Breast self examination for early detection of breast cancer
Papanicolaou Testing:
Screening for breast cancer and cervical Cancer meets all screening test criteria. Both diseases are prevalent, serious, pre-clinical detectable period, treatable, early treatment is better than late
Al Kindy College of Medicine
Community Medicine Department Lab. 7Practical Lab. Of General Epidemiology
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