Assuring the Quality of Laboratory Testing in Countries Fighting the HIV/AIDS Epidemic

1. Assuring the Quality of Laboratory Testing in Countries Fighting the HIV/AIDS Epidemic CDC November 29-30, 2000

2. Test Verification&Test Validation Niel T. Constantine, Ph. D. Professor of Pathology Director Clinical Immunology University of Maryland School of Medicine And Institute of Human Virology

3. Test Verification &Test Validation • Considerations when determining the utility of tests A. Protocols for Evaluation of Tests B. Reference Tests C. Algorithms D. Choice and Number of Samples E. Testing Conditions F. Resolution of Discordant Results G. Indicators of test performance

4. Considerations When Determining the Utility of Tests Protocols for Evaluations of Tests

5. Protocols for Evaluation of Tests • Essential to set guidelines. • Must be followed exactly. • Must outline all characteristics of samples and procedures. • Must describe detailed algorithm to follow for discordant results. • Must include QA/QC section.

6. Considerations When Determining the Utility of Tests Reference Tests

7. Reference Tests • Needed to fully characterize samples. • Choice depends on purpose of testing. • Concordance – against reference screening test. • Accuracy – against confirmatory test. • Must be careful about “pre-selected samples” to evaluate false positives. • Should be tests that are recognized by the scientific community.

8. Considerations When Determining the Utility of Tests Algorithms

9. UNAIDS and WHORecommended Alternative Algorithms • To maximize accuracy while minimizing cost • Depends on objectives of the test and the prevalence of infection

10. Table 2 UNAIDs and SHO reccommendations for HIV testing strategies Tableau 2 Recommandations de I’onusida et de I’OMS aux strategies according to test objective and prevalence of infection in the de depistage du VIH, en fonction de l’obectif du test et de la sample population prevalence de l’infection dans la population Objective of testing Prevalences of infections Testing strategy Objectif du dépistage Prévalences de l’infection Stratégie de dépistage Transfustion/transplant safety All Prevalences Sécurité des transfusions/transplantations Toutes prévalences  Surveillance >10%  10%  Clinical signs/symptoms of >30%  HIV Infection- Signnes Cliniques/symptôms de 30%  l’infection à VIHa Asymptomatic >10%  Asymptomatique 10%  aWorld Health Organizaion, Intenm proposal for a WHO staging system for HIV infection and desease (WER no.29, 1990, pp 221-228)- Organisation mondiale de la sante. Echelle provisoire OMS proposee pour la determinationdes strades de l’infecrtiono VIH et de la malodie (REN no 29, 1990. P.221-228)

12. Considerations When Determining the Utility of Tests Choice and Number of Samples

13. Choice and Number of Samples Samples: • Should represent population where test will be performed. • Same matrix of sample (e.g. plasma). • Must meet guidelines stated by manufacturer (e.g. not lipemic). • Avoid multiple freeze/thaw, etc. • Use “clean”samples. • Multiple aliquots if possible. • Must be well categorized.

14. Choice and Number of Samples Samples: • Should represent population where test will be performed. • Same matrix of sample (e.g. plasma). • Must meet guidelines stated by manufacturer (e.g. not lipemic). • Avoid multiple freeze/thaw, etc. • Use “clean”samples. • Multiple aliquots if possible. Numbers of Samples: • The more the better (min. 30 positives, 200 negatives). • Depends on purpose of testing (e.g. blood donors). • Include appropriate percent of variants. • Perform precision and reproducibility studies (lg. Volumes).

15. HIV Classification HIV Types HIV-1 HIV-2 M O Groups N ROD NIH2 ANT 70, MVP5180, VAU A, B, C, D, E, F, G, H, I, J Guidelines for Classification Types: HIV-1 and HIV-2 50% homology Subtypes/Groups: HIV-1 group M, N and O 60-70% homology Clades: HIV-1 Clades A-J >70% homology Clades

16. Considerations When Determining the Utility of Tests Testing Conditions

17. Testing Conditions • Must test under identical conditions. (e.g. same lab, equipment, day, tech). • Use non-expired kits that have been properly stored. • Follow manufacturer’s recommendations. • Sample integrity. • Test in a blinded fashion.

18. Considerations When Determining the Utility of Tests Resolution of Discordant Results

19. Resolution of Discordant Results • Check sample integrity, labeling, paperwork, and procedures. • Repeat by same technologist. • Repeat blindly by another technologist. • Repeat reference test blindly. • Repeat at different laboratory. • Determine true status by other means. • What parameters would these investigate?

20. Resolution of Discordant ResultsPossible Variants • Synthetic peptide tests • Specific Western blots • Specific IFAs • Combination tests • Dot blots • Immunoconcentration tests • Augmented blots and LIA • PCR - specific

21. Rapid Assay Evaluation Algorithm Rapid Assay + ELISA - Rapid Assay - ELISA + Discordant Results Repeat Rapid & ELISA Western Blot Assay (FDA Licensed) Negative Indeterminate Positive IFA (FDA Licensed) Resolved Negative Indeterminate Positive Sample Volume > 1 mL Sample Volume (<1 mL & >0.2 mL) Resolved Resolved P24 Ag Assay (FDA Licensed) RT-PCR Assay Negative Positive Inconclusive Ag Neutralization Negative Positive Positive Negative Inconclusive Resolved Resolved

22. Considerations When Determining the Utility of Tests Indicators of Test Performance

23. Indicators of the Value of a Diagnostic Assay • Sensitivity • Specificity • Test efficiency • Delta values • Predictive values

24. Sensitivity of Tests • Sensitivity (epidemiologic) • Sensitivity (analytical) • Low titer • Seroconversion • Dilutions

25. Indicators of the Value of a Diagnostic Assay Sensitivity = True Positives True Positives + False Negatives X 100% Specificity = True Negatives True Negatives + False Positives X 100%

26. Indicators of the Value of a Diagnostic Assay Positive Predictive = True Positives Value True Positives + False Positives X 100% Negative Predictive = True Negatives Value True Negatives +False Negatives X 100%

27. Predictive Values Assume: Test Sensitivity = 100% / Specificity = 99.5% Population #1, where the prevalence of infection is high (5%) • Population: 1000 sera tested 50 sera from infected individuals 950 sera from non-infected individuals • Test Results: 50 positives: 45 from the infected group 5 false pos from the non-infected group • Therefore, the positive predictive value is: PPV = 45 = 90% 45+5 • 9 out of 10 positive results will be from infected persons

28. Predictive Values Assume: Test Sensitivity = 100% / Specificity = 99.5% Population #2, where the prevalence of infection is low (0.7%) • Population: 1000 sera tested 7 sera from infected individuals 993 sera from non-infected individuals • Test Results: 7 positives: 2 from the infected group 5 false pos from the non-infected group • Therefore, the positive predictive value is: PPV = 2 = 28.6% 2+5

29. Predictive Values • Therefore, the same test that yields the same number of false-positives produces a different positive predictive value when testing two different populations

30. Predictive Values • Therefore, the same test that yields the same number of false-positives produces a different positive predictive value when testing two different populations. • The chance of a positive result being from a truly infected individual in the low prevalence population is only 28.6% (2 true positive detected by the test and 5 false-positives).

31. Predictive Values • Therefore, the same test that yields the same number of false-positives produces a different positive predictive value when testing two different populations. • The chance of a positive result being from a truly infected individual in the low prevalence population is only 28.6% (2 true positive detected by the test and 5 false-positives). • This indicates that a positive result by the test will be from an infectd individual in only one of four cases (a guess could yield better chance!).

32. Test Verification &Test Validation • Quality Assurance and Errors • A. Common Errors • B. Quality Assurance Needs • 1. Fundamentals of QA • 2. Quality Control • 3. Quality Assessment • 4. Equipment Issues • 5. 10 Key Issues for QA

33. Most Common Errors • Transcription • Carelessness • Procedures • Specimens • Environmental conditions • Pipettes and pipetting

34. Clerical Errors • Logging specimens • Aliquoting • Worksheets • Result printouts • Translating results • Computer entering • Reports • Supervisory Review

35. Specimen Problems • Insufficient volume for repeating • Hemolysis, lipemia, and bacterial contamination • Insufficient and inadequate labeling • Misidentified specimens • Frozen / Thawed (multiple)

36. Other Types of Errors • Kit Dependent Problems. • Technologist – dependent errors. • Inter-lot variations and Intra-lot variations. • Environmental problems. • Non repeatable results. • Inter-laboratory and Intra-laboratory variations. • Equipment problems.

37. Quality AssuranceFundamental for Quality Test Results • Record keeping • Monitoring laboratory staff • Vigilance in the laboratory • Verification of true positive and true negatives • Parallel testing of resubmitted samples • Reporting of results • Confidentiality • Interaction with physicians • Storage of specimens for follow-up testing • Laboratory efficiency • Total quality management

38. Components of Quality ControlRecord Keeping • Kit lot numbers (expiration and open dates). • Clearly label reagents with date opened or prepared (include open and expiration date) on each label. • Daily temperature monitoring and recording i.e. Incubators water baths, ambient. • Performance of controls and action taken when out-of-range. • Photograph or clear photocopies of Western blots. • Ratios of in-house controls to cut-off values.

39. Components of Quality ControlControls • Kit controls: Use as directed by the manufacturer. • In-house controls: preferably three levels to monitor variability between runs and lot numbers of kits. • Low positive – absorbance enough above cut-off that it should not be misclassified because of expected run-to-run variability. • High positive – well above the cut-off. • Negative – well below cut-off. • Storage of in-house control sera: • Dispense in aliquots sufficient for one week of use. • Freeze at -20°C in a non-self-defrosting freezer. • Thaw each aliquot once, store at 4 °C when not in use, do not refreeze and discard after 1 week.

40. Monitoring by External Controls Trend Shift

41. Quality Assessment Internal Quality Assessment • Known Reactors • Unknown Reactors • Blind Testing External Quality Assessment • Proficiency Panels • Blind Proficiency Panels

42. Equipment Issues Pipette Calibrations ESSENTIAL FOR ACCURACY • Frequency • At least every 6 months • Reasoning • 1l inaccuracy = 10% error (total volume of 10 l) • Controls – o.k., borderline specimens – loss of sensitivity

43. Quality Assurance: What Must Be Done?10 Key Issues • Detailed SOP with total compliance. • Supervising review of all paperwork. • Develop checklists for monitoring all activities. • Dev. Organizational schemes for processing, documentation, and assessment. • Monitor staff – blind proficiencies. • Neat and complete documentation of all results. • No deviation from procedures. • Maintain confidentiality. • Endorse safety measures. • Vigilance.

44. Test Verification &Test Validation III. Introduction of a New Test A. Selection B. Characteristics C. Approved versus Non-Approved tests D. Continual Monitoring

45. Selection • Availability • Appropriateness • Cost and bulk purchases • Shelf life and robustness • Storage • Publications and WHO evaluations • Regulations

46. Characteristics • Laboratory capabilities • Testing Purpose • Simplicity • Cost Concerns • Sample type • Test limitations • Test principles and antigens • Test indices

47. Approved VersusNon-approved Tests • Which can be used? • When approved tests are unavailable. • Validation of non-approved tests. • Documentation necessities and qualifications.

48. Continual Monitoring • Necessity to monitor new tests. • How long to monitor. • Methods of monitoring. • Looking for trends. • Changing tests – Parallel testing. • Documentation.

49. Test Verification &Test Validation IV. Special Considerations for Developing Countries A. Selection of Tests and algorithms B. Testing under non-optimal conditions. C. Best fit Strategies D. When Systems Fail

50. Special Considerations for Developing Countries Selection of Tests and Algorithms