1. Positive NAAT test results for Neisseria gonorrhoeae do not require routine confirmatory testing Matthew R. Golden MD, MPH Center for AIDS & STD, University of WA Public Health - Seattle & King County

2. Objectives To demonstrate that NAAT for gonorrhea do not require universal confirmatory testing when used in low prevalence environments. Issues I will not argue Should low prevalence populations be screened Selective screening – currently do not exist PCR can be used in very low prevalence populations without confirmatory testing

3. Problems with an argument based on PPV Routine confirmatory testing is impractical Need for routine testing reflects a hyperbolic sense of risk, and excessive attention to relative rather than absolute risk Perceived need is based on notion that true test performance in a very low prevalence population can’t be known. It’s cynical. Maybe some tests are OK?

4. Approaches to confirmatory testing ApproachBarriers to implementation Barriers to interpretation Overall Test a new specimen +/- different test Patient needs to return Which test is correct? – helpful if both are positive - Good for usual circumstances - Culture is definitive - Having patients return is not practical Repeat test using a different test -Incompatible media - Need for labs to maintain >1 test or send out – turn around time Which test is correct? – helpful if positive Best option, but will be tough to implement unless the same testing platform is used Repeat same testEasyTwo positives still hard to interpret. Discrepant- Which test is correct? Easiest, but least definitive

5. Positive Predictive Value (%) Prevalence Positive predictive value is primarily a function of prevalence & specificity 1%

6. The absolute risk & number of false positives varies little with prevalence Prevalence 1% 4% 8% # false positives per 10,000 98 95 91 PPV 49% 80% 89% Assumes 95% sensitive test and 99% specific Absolute risk false positive 0.98/100 0.95/100 0.91/100

7. Are NAAT tests good enough? How good do they need to be? PPV >90% in a very low prevalence population (i.e. 0.5%)

8. Size, Specificity and Prevalence of Larges NAAT Studies Largest studySpecificity in largest study Lowest prevalence studied BDProbetec3,54499.33.6% Digene HC-II1,37098.56.3% Aptima1,48498.78.5% Specificity estimates are imprecise. Recent studies have avoided discrepant analysis, probably erring on the side of underestimating specificity

9. True Specificity (%) Number of specimens needed to define PPV >90% in a 0.5% prevalent population

10. # tested confirmatory testing design Specificity (%) Number of specimens needed to define PPV >90% in 0.5% prevalent population

11. PPV Aptima for N. gonorrhoeae in a low prevalence population 0/194 negative specimens tested positive for N. gonorrhoeae 4 Labs in WA state test 59,664 specimens 280 (0.5%) GC+ 265 Tested using alternative set rRNA primers 258 GC+ PPV= 97.4 (95% CI 95.1%-98.8%)

12. Limitations to Confirmatory Testing Using a NAAT for confirmatory testing assumes that the confirmatory NAAT is specific. If an organism other than N. gonorrhoeae has nucleic acid amplification sequences amplified by both tests, then a confirmatory NAAT results will not be valid. Routine confirmatory testing doesn’t solve this problem unless all the patients come back for culture. This is not practical and culture is somewhat less sensitive than NAATs, so interpreting results will still be difficult. There is still a need for judgment in ordering and interpreting tests

13. Conclusions Confirmatory testing is not indicated for all specimens that test positive for N. gonorrhoeae using NAATs in low prevalence populations Confirmatory testing is not practical Perceived need based on low threshold for absolute risk of false positive Assumes test performance cannot be defined Need for confirmation depends on the test Aptima performs well and that confirmatory testing is not needed. PCR does not perform adequately and confirmatory testing is needed. Data are inadequate to assess the need for confirmatory testing with SDA & Probetec – some data low positive SDA may be more likely to be false positive