Validity and Reliability of Analytical Tests

1. Validity and Reliability of Analytical Tests

2. Analytical Tests include both: • Screening Tests • Diagnostic Tests

3. Two Important Objectives To distinguish between people in the population who have the diseases and those who do not To determine how good the test is in separating populations of people with and without the disease in question?

4. Epidemiological Surveillancevs.Screening

5. Epidemiological Surveillance • What is it? • Why do it?

6. Epidemiological Surveillance • Definition - ongoing & systematic collection, analysis & interpretation of data related to health, disease & conditions • Two types • Passive Surveillance – uses available data or reporting from health care provider or regional health officer • Active Surveillance – periodic field visits to health care facilities to identify new cases • The present approach is the survey

7. Epidemiological Surveillance • Why do it? • Can help discover and control the transmission of infectious diseases • Prevention and control programs can be planned and implemented

8. Screening • Definition - use of quick and simple testing procedures to identify and separate persons: • who have a disease from those that do not OR • who are apparently (appear to be) well, but who may be at risk of a disease, from those who probably don’t have the disease.

9. Terms Related to Screening Tests • Validity - relates to accuracy (correctness) • Reliability - repeatability • Yield - the # of tests that can be done in a time period

10. Terms Related to Screening Tests (cont’d) • Sensitivity - ability of a test to identify those who have disease • Specificity - ability of a test to exclude those who don’t have disease

11. Terms Related to Screening Tests (cont’d) • Tests with dichotomous results – tests that give either positive or negative results • Tests of continuous variables – tests that do not yield obvious “positive” or “negative” results, but require a cutoff level to be established as criteria for distinguishing between “positive” and “negative” groups

12. An important public health consideration, particularly in screening free-living populations, is:How good is the test at identifying people with the disease and without the disease?In other words:If we screen a population, what proportion of people who have the disease will be correctly identified?

14. True positives True positives + false negatives True positives All persons with the disease Sensitivity = = X 100 = TP TP + FN

15. True negatives True negatives+ false positives True negatives All persons without the disease Specificity = = X 100 = TN TN + FP

16. FN FN + TP X 100 Percent false negatives = % of people with the disease who were not detected by the test

17. FP FP + TN X 100 Percent false positives = % of people without the disease who were incorrectly labeled by the test as having the disease

18. In the clinical setting, a more important question is:If the test results are positive (or negative) in a given patient, what is the probability that this patient has (or does not have) the disease?In other words:What proportion of patients who test positive (or negative) actually have (or do not have) the disease in question?

19. Predictive Value True Positives TP + FP Pos. PV = X 100 = % Neg. PV = X 100 = % True Negatives TN + FN

20. Biologic Variation of Human Populations & Diagnostic Issues

21. Distribution of Tuberculin Reactions Bimodal Distribution Easy to distinguish between exposed group and those not exposed.

22. Distribution of Systolic Blood Pressure Unimodal Distribution With continuous variables, a cutoff level must be established to separate the hypertensive group. Could choose based on statistics, but better to base on biologic considerations.

23. Effects of Choosing Different Cutoff Levels for Diabetes Diagnosis in Population with 50% Prevalence Pseudo-Real World Real World

24. The major issue with deciding to set a cutoff high or low is the problem of false positives and false negatives.

25. Possible Groups with Dichotomous Test True Disease Status is Known, as with dichotomous tests.

26. Grouping All Positives and All Negatives True Disease Status is Unknown, as with continuous variables. Artificial Cutoff

27. Use of Multiple Screening Tests Sequential (Two-stage) Testing Simultaneous Testing

28. Hypothetical Two-Stage Screening Only Pos. Test 1 are given Test 2

29. Hypothetical Two-Stage Screening(cont.) Sensitivity = 90% Specificity = 90% TEST 2 (Glucose Tolerance Test) Net Sensitivity = 315/500 = 63% Net Specificity = 7600 + 1710 = 98% 9500

30. Predictive Value

31. Prevalence & Predictive Value Positive As prevalence increases, positive predictive value increases.

32. Note: Test has 95% sensitivity and 95% specificity Prevalence & Predictive Value

33. Specificity & Predictive Value As specificity increases, positive predictive value increases. As sensitivity increases, positive predictive value also increases, but to a much lesser extent.

34. Specificity & Predictive Value As specificity increases, positive predictive value increases.

35. Results reliable but NOT valid Results reliable and valid Reliability (Repeatability) of Tests