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Results from the LA rapid testing study: What can they tell us about proposed point of care strategies? Kevin Delaney, MPH Division of HIV/AIDS Prevention.

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Presentation on theme: "Results from the LA rapid testing study: What can they tell us about proposed point of care strategies? Kevin Delaney, MPH Division of HIV/AIDS Prevention."— Presentation transcript:

1 Results from the LA rapid testing study: What can they tell us about proposed point of care strategies? Kevin Delaney, MPH Division of HIV/AIDS Prevention Behavioral and Clinical Surveillance Branch Diagnostics Applications Team

2 Thank You (So Far…) LA County STD Peter Kerndt Apurva Uniyal Staff at LAGLC/Altamed DHAP/OD Bernie Branson BCSB Steve Etheridge Dawn Gnesda Duncan Mackellar Patrick Sullivan QSDM Debra Hansen Serum Bank Dollene Hemmerlein Lab Branch Debra Candal Trudy Dobbs Tom Folks Tim Granade Susan Kennedy Steve McDougal Michelle Owen

3 Outline Original study methods Problematic specimens Comparing strategies Why prevalence matters

4 Original Study Objectives Describe the performance of individual rapid tests –Sensitivity, specificity and predictive value Evaluate the performance of combinations of rapid tests –Particular focus on tests designed for use at point of care Foster discussion of a point of care diagnostic algorithm

5 Testing –Specimens from participants were tested with all 6 FDA approved rapid tests –Serum also tested with EIA and Western blot: Vironostika HIV-1 Microelisa system Genetic Systems HIV-1 Western Blot –Samples of both serum and plasma retained for future testing Tested at CDC with both Genprobe Aptima and Biorad HIV1/2 + O EIA Original Study Methods

6 Analysis –Sensitivity, specificity and predictive value for individual tests and combinations used in POC strategies: Performed in Sequence First two tests performed in Parallel Second and third must agree to be considered positive Proposed strategies 1, 2, 3 and 4 Original Study Methods

7 Line List of “Multiply Discordant” Specimens (n=8) – Including CDC results IDLA res AptimaBioradOQ-oOQ-bSp-bSp-plUG-bUg-plCo-bMS-plRe-pl 1 NPP X 3NNNNPNPN 4 NNNPPNNNNPNN 6 NNNNNNPNNNPN 9 NNNNNNNNNNPP 10 PNP X 3NNNNNPPN 11 PPP X 3NPPPNNPP 13 PPP X 3PPPNPNPN 15 PPP X 3PPPNPNPP

8 Line List of Western blot IND Specimens (n=6) – Including CDC results IDAptimaBioradOQ-oOQ-bSp-bSp-plUG-bUg-plCo-bMS-plRe-pl 16NNNNNNNNPN 17NNPPNNPPPPP 18PP X 3NNNNNNNN 19PP X 3NNNNNNNN 20NP X 3PPPPPPPP 21PP X 3PPPPPPPP

9 Comparing Strategies Bootstrap resampling –Random selection of individuals with replacement –Random selection of a test combination –1100 theoretical combinations of test and specimen type –Excluded: Combinations of the same test used on the same (n=290) Or different (n=200) specimen types Combinations that used the two Clearview tests together (n=152) Combinations with a CLIA moderate complexity test followed by a CLIA-waived test (n=232) Combinations in which Oraquick performed on oral fluid was used as the second or third test (n=21) –51 two-test and 154 three-test potential combinations

10 Comparing Strategies Bootstrap resampling –Includes variability introduced by individual test combinations e.g. starting with OMT vs. starting with blood “bad batch” of tests with low specificity –and problematic specimens e.g. likely specimen mix “specific non-specific” reactions with antigens –Medians and bootstrap confidence intervals reported

11 Comparing Strategies Diagnostic likelihood –The “relative risk” of being infected given that you test: Positive (PLHR)= sensitivity/(1-specificity) Negative (NLHR)= (1-sensitivity)/specificity Good test performance PLHR > 10 and NLHR <.1 Combining with prevalence will give Positive (PLHR) or Negative (NLHR) predictive value

12 Compare algorithms – Diagnostic Likelihoods = Remember these tests are GOOD! scenario Nlhr 2.5% Nlhr 50% Nlhr 97.5% Plhr 2.5% Plhr 50% Plhr 97.5% AUC 2.5% AUC 50% AUC 97.5% one test (Strategy 1) 0 0.013288 0.030633390777 3870 0.983600.993200.99949 Two different Rapids (Strategy 2) 0 0.014778 0.036810 3774 Inf. 0.981930.992681.00000 Two Oraquicks (Strategy 3).004149864 0.017471 0.03745013854226Inf.0.981210.991190.99784 Strategy 4+ (allow +,-,- = not infected) 0 0.014634 0.034216 3341 Inf. 0.983120.992721.00000 Parallel screening 0 0.006536 0.024004 3074 Inf. 0.990180.997331.00000 3 Tests must agree 0 0.016393 0.038674Inf. 0.980540.991711.00000

13 Sensitivity 1-Specificity ROC Curves for various POC Algorithms

14 Compare algorithms – Predictive Value (prevalence ≈ 5%) scenario Ppv 2.5% Ppv 50% Ppv 97.5% Npv 2.5% Npv 50% Npv 97.5% one test (Strategy 1) 0.951810.97566 0.99490 0.998510.999251.00000 Two different Rapids (Strategy 2) 0.993381.00000 0.998500.999261.00000 Two Oraquicks (Strategy 3) 0.985020.995481.000000.998190.999090.99977 Strategy 4+ (allow +,-,- = not infected) 0.99402 1.00000 0.998080.999151.00000 Parallel screening 0.992601.00000 0.998760.999681.00000 3 Tests must agree 1.00000 0.998090.999161.00000

15 Compare algorithms – Further testing; Incorrect results scenario Ind 2.5% Ind 50% Ind 97.5% Fn 2.5% Fn 50% Fn 97.5% Fp 2.5% Fp 50% Fp 97.5% one test (Strategy 1) 0 00 0 3 61510 Two different Rapids (Strategy 2) 0 210 0 3 60 0 1 Two Oraquicks (Strategy 3) 0131 4 80 1 3 Strategy 4+ (allow +,-,- = not infected) 000 0 3 7001 Parallel screening 0000 1 4001 3 Tests must agree 1 411 0 3 7000 Remember, these numbers won’t change for a given number of tests

16 Prevalence affects predictive value, if you have false positives… Predictive value positive – Single test Prevalence

17 The percentage of specimens going to the lab (red line) will increase as prevalence goes down Predictive value positive – Single test Percentage of tests that will require lab follow-up in strategies 2 and 4 Prevalence

18 In the worst case (Positive diagnostic likelihood ~ 400) @.1% prevalence 70% of specimens would still require laboratory follow-up Predictive value positive – Single test Percentage of tests that will require lab follow-up in strategies 2 and 4 Prevalence

19 Compare algorithms – Further testing; Incorrect results scenario Ind 2.5% Ind 50% Ind 97.5% Fn 2.5% Fn 50% Fn 97.5% Fp 2.5% Fp 50% Fp 97.5% one test (Strategy 1) 0 00 0 3 61510 Two different Rapids (Strategy 2) 0 210 0 3 60 0 1 Two Oraquicks (Strategy 3) 0131 4 80 1 3 Strategy 4+ (allow +,-,- = not infected) 000 0 3 7001 Parallel screening 0000 1 4001 3 Tests must agree 1 411 0 3 7000 But in that case that’s still less than 20 specimens per 4000 tested…

20 Specificity of a single rapid test >99% –At low prevalence, the proportion of positive tests that are false positive increases. –Adding a second test resolved nearly all false positives correctly –There will likely always be some problematic specimens no testing strategy can fix Summary

21 All testing strategies perform exceptionally well –In low prevalence settings a POC strategy that resolves all false positives without lab intervention may be necessary –In high prevalence settings the sensitivity of the first test and the option to test for acute infection should be considered Summary

22 Sensitivity of all rapid tests was high –Comparable to current EIAs –Negative predictive value suggests < 2 false negatives/10,000 negatives tested @ 1% prevalence –Important to consider “realized sensitivity” Summary

23 Results – Sensitivity of a single test TestSpecimen typeTrue Pos False neg Sensitivity (95% CI) OraquickOral fluid280598.2 (95.9-99.4) Whole blood277199.6 (98.0-100) UnigoldWhole blood173597.2 (93.6-99.1) Plasma247896.8 (93.7-98.6) CompleteWhole blood2130100 (98.6-100) Stat-pakWhole blood246299.2 (97.1-99.9) Plasma246498.4 (95.9-99.6) MultispotPlasma252199.6 (97.8-100) RevealPlasma278398.9 (96.8-99.8)

24 Results – Specificity of a single test TestSpecimen typeTrue Neg False Pos Specificity (95% CI) OraquickOral fluid54732100 (99.9-100 ) Whole blood54661100 (99.9-100 ) UnigoldWhole blood3591299.9 (99.8-100 ) Plasma47472100 (99.9-100 ) CompleteWhole blood4202299.9 (99.8-100 ) Stat-pakWhole blood47711100 (99.9-100 ) Plasma47632100 (99.9-100 ) MultispotPlasma48353399.3 (99.0-99.5) RevealPlasma5478699.9 (99.8-100 )

25 PV+ Results – Predictive value positive, single rapid test Prevalence

26 Initial Rapid Test Screen 2 nd Rapid test Screen Third Rapid Test “Tie- Breaker” Confirmed Positive Confirmed Negative Negative Positive Negative Positive Sequential Antibody Screening Algorithm

27 Initial two tests 3 rd Rapid test Confirmed Positive Confirmed Negative Negative/ Negative Either positive Positive Negative Parallel Antibody Screening Algorithm

28 Initial Rapid Test Screen Rapid Tests 2 and 3 Indeterminate Confirmed Positive Confirmed Negative Negative PositiveBoth Positive 1 of 2 Negative WHO Sequential Antibody Screening Algorithm (2 nd and 3 rd tests must agree) Both Negative

29 Results – 3 tests Sequential TestsAlgorithm Results 1 st test 2 nd test 3 rd test True Positive False Negative True Negative False Positive Clia-Waived OQ-bSP-bUG-b222142890 OQ-oUG-bSP-b151442890 SP-bOQ-bUG-b221242890 SP-bUG-bOQ-b153242890 CompleteOQ-bUG-b161030921 Clia- Moderate Complexity OQ-bUG-plMS-PL222142890 SP-bMS-PLRe-PL221242890 MS-PLRe-PLUG-PL221242872

30 Results – 3 tests 1 st two in parallel TestsAlgorithm Results 1 st test 2 nd test 3 rd test True Positive False Negative True Negative False Positive Clia-Waived OQ-bSP-bUG-b222142890 OQ-oUG-bSP-b153242890 SP-bOQ-bUG-b222142890 SP-bUG-bOQ-b154142890 CompleteOQ-bUG-b161030921 Clia- Moderate Complexity OQ-bUG-plMS-PL222142890 SP-bMS-PLRe-PL221242890 MS-PLRe-PLUG-PL221242872

31 Results – 3 tests Sequential All must agree TestsAlgorithm Results 1 st test 2 nd test 3 rd test Further Testing True Positive False Negative True Negative False Positive Clia-Waived OQ-bSP-bUG-b222142890 OQ-oUG-bSP-b151442890 SP-bOQ-bUG-b221242890 SP-bUG-bOQ-b153242890 CompleteOQ-bUG-b1161030920 Clia- Moderate Complexity OQ-bUG-plMS-PL222142890 SP-bMS-PLRe-PL221242890 MS-PLRe-PLUG-PL2221242870

32 Results – 2 tests Sequential TestsAlgorithm Results 1 st test 2 nd test Further testing True Positive False Negative True Negative False Positive Clia-Waived OQ-bSP-b 2221142880 OQ-oUG-b 4149442870 SP-bOQ-b 1221242880 SP-bUG-b 4150242880 CompleteOQ-b 1161030911 Clia- Moderate Complexity OQ-bUG-pl 8215142880 SP-bMS-PL 2220242880 MS-PLRe-PL35219142561

33 Results – 2 tests - A1 Oral / Blood TestsAlgorithm results 1 st test 2 nd test 3 rd test Further testing True Positive False Negative True Negative False Positive Clia-Waived OQ-oSP-bOQ-b2218442880 OQ-oUG-bOQ-b4148442880 OQ-oCompleteOQ-b1160142871

34 Results – 3 tests Sequential, +-- not conclusive? TestsAlgorithm Results 1 st test 2 nd test 3 rd test True Positive False Negative True Negative False Positive Clia-Waived OQ-bSP-bUG-b222142890 OQ-oUG-bSP-b151442890 SP-bOQ-bUG-b221242890 SP-bUG-bOQ-b153242890 CompleteOQ-bUG-b161030921 Clia- Moderate Complexity OQ-bUG-plMS-PL222142890 SP-bMS-PLRe-PL221242890 MS-PLRe-PLUG-PL221242872

35 Results – 3 tests - A1 Oral / Blood TestsAlgorithm results 1 st test 2 nd test 3 rd /4 th test Further testing True Positive False Negative True Negative False Positive Clia-Waived OQ-oSP-bOQ-b / UG-b 1219442880 OQ-oUG-bOQ-b / SP-b 1151442880 OQ-oCompleteOQ-b / UG-b 1160142871 OQ-oCompleteOQ-b / SP-b 1160142871

36 Location –Two clinics in Los Angeles, CA Participants –Persons of unknown serostatus seeking HIV testing –Persons known to be HIV positive Original Study Methods

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