1. Principles of Epidemiology E
Screening
Principles of Epidemiology E

2. Principles Underlying Screening Programs
Validity – the ability to predict who has the disease and who does not
Sensitivity – the ability of a test to correctly identify those who have the 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

3. Principles Underlying Screening Programs (cont.)
An ideal screening test would be 100% sensitive and 100% specific – that is there would be no false positives and no false negatives
In practice these are usually inversely related
It is possible to vary the sensitivity and specificity by varying the level at which the test is considered positive

4. Calculating Measures of Validity
True Diagnosis
Test Result
Disease
No Disease
Total a b
a+b
Positive
Negative
Sensitivity = a/(a+c); the probability of having a positive test if you are positive
Specificity = d/(b+d); the probability of having a negative test if you are negative
Positive Predictive Value = a/(a+b); the probability of having the disease if you test positive
Negative Predictive Value = d/(c+d); the probability of not having the disease if you test negative
Prevalence = (a+c)/(a+b+c+d)
Accuracy (efficiency of test) = (a+d)/(a+b+c+d) c d
c+d
Total
a+c
b+d
a+b+c+d

5. Note the Following Screening Relationships
Specificity + false positive rate = 1
d/(b+d) + b/(b+d) = 1
If the specificity is increased, the false positive rate is decreased
If the specificity is decreased, the false positive rate is increased
Sensitivity + false negative rate = 1
a/(a+c) + c/(a+c) = 1
If the sensitivity is increased, the false negative rate is decreased
If the sensitivity is decreased, the false negative rate is increased

6. Interrelationship Between Sensitivity and Specificity

7. Sensitivity and Specificity of a Blood Glucose Level
Sensitivity and Specificity of a Blood Glucose Level of 110 mg/100 ml for Presumptive Determination of Diabetes Status
Blood Glucose Level
(mg/100 ml)
Diabetics
(Percent)
Nondiabetics
(Percent)
All those with level over 110 mg/100 ml are classified as diabetics
92.9
(true positives)
51.6
(false positives)
All those with level under 110 mg/100 ml are classified as nondiabetics
7.1
(false negatives)
48.4
(true negatives)
100.0
100.0

8. Adjusting Sensitivity and Specificity by Adjusting Cut Points

9. 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 specificity
If you are screening to prevent transmission of a preventable disease (such as screening for HIV in blood donors), optimize sensitivity

10. Remember….
Sensitivity and specificity are functions of the screening test
If you use a given screening test on a low prevalence population, you will have a low positive predictive value and potentially many false positives

11. Principles Underlying Screening Programs
Reliability – the ability of a test to give consistent results when performed more than once on the same individual under the same conditions
Variation in the method due to variability of test chemicals or fluctuation in the item measured (e.g., diurnal variation in body temperature or in relation to meals)
Standardize fluctuating variables
Use standards in laboratory tests, run multiple samples whenever possible
Observer variation
Train observers
Use more than one observer and have them check each other

12. Principles Underlying Screening Programs
Yield – the amount of previously unrecognized disease that is diagnosed and brought to treatment as a result of the screening program
Sensitivity
You must detect a sufficient population of disease to be useful
Prevalence of unrecognized disease
Screen high risk populations
Frequency of screening
Screening on a one time basis does not allow for the natural history of the disease, differences in individual risk, or differences in onset
Diseases have lead time
Participation and follow-up
Tests unacceptable to those targeted for screening will not be utilized

13. Conditions for Establishing Screening Programs
The condition should be an important health problem
There should be an accepted treatment for patients with recognized disease
If there is no treatment, it is premature to institute screening
Facilities for diagnosis and treatment should be available
It is unethical to screen without providing possibilities for follow-up
There should be a recognizable latent or early symptomatic stage
If early detection does not improve survival, there is no benefit from screening

14. Conditions for Establishing Screening Programs (cont.)
There should be a suitable test for examination, with sufficient sensitivity and specificity to be of use in identifying new cases
The test should be acceptable to the population
The natural history of the condition, including development from latent to declared disease, should be adequately understood
There should be an agreed-upon policy concerning whom to treat as patients

15. Conditions for Establishing Screening Programs (cont.)
The cost of case-finding should be economically balanced in relation to possible expenditure on medical care as a whole
Case-finding should be in a continuing process and not a one-time project

16. Biases in Screening Referral Bias (volunteer bias) Length Bias
Screening selectively identifies those with a long preclinical and clinical phase (i.e., those who would have a better prognosis regardless of the screening program)

17. Biases in Screening (cont.)
Lead Time Bias
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

18. Biases in Screening (cont.)
Overdiagnosis Bias (a misclassification bias)
Enthusiasm for a new screening program may result in a higher rate of false positives and give false impression of increased rates of diagnosis and detection
Also, false positives would result in unrealistically favorable outcomes in persons thought to have the disease

19. Dis -
Dis +
Prv 5%
Sn70%
Sp80%
2250
1900
35o
Test+
7750
7600
150
Test -
10000
9500
500
Test 1
Dis -
Dis +
Prv 5%
Sn90%
Sp90%
505
190
315
Test+
1745
1710 35
Test -
2250
1900
350
Test 2

20. Dis -
Dis +
Prv 20%
Sn80%
Sp60%
480
320
160
Test+
520 40
Test -
1000
800
200
Test 1
Dis -
Dis +
Prv 20%
Sn90%
Sp90%
260 80
180
Test+
740
720 20
Test -
1000
800
200
Test 2