CDC/APHL HIV Diagnostics Conference 5-7 Dec 07Page 1 Usefulness of a Secondary EIA Screen in a Low HIV Prevalence Population Robert J. OConnell, MD FACP

CDC/APHL HIV Diagnostics Conference 5-7 Dec 07 Page 1

Usefulness of a Secondary EIA Screen in a Low HIV Prevalence

Population

Robert J. O’Connell, MD FACP

Chief, Department of Laboratory Diagnostics and MonitoringDivision of Retrovirology

Walter Reed Army Institute of Research


Acknowledgements/Disclaimer

WRAIR:SA PeelCT BautistaKN MartinNL MichaelMEDCOM:DR DeuterViromed:DL KirklandR Sundararajan

USCG:EG SchwartzMEPCOM:KP DallenBioRad Laboratories:K Shriver

The views expressed do not necessarily reflect those of the US Army, or the Department of Defense. Use of trade names is for identification only and does not imply endorsement by the US government

Proposed Testing Strategies for Laboratory HIV Testing Facilities

Positive for HIV-1 antibodies

A1 (+) A1 (-)

Repeat A1 (in duplicate)

A1 (++ or - +)

B1 HIV-1 WB or HIV-1 IFA

A1 (- -)

Negative for HIV-1 antibodies†

Inconclusive for HIV-1 antibodies; request redraw in 2-4 weeks; requires medical follow-up for further evaluation and testing †∞

Negative for HIV-1 antibodies†

A1 EIA (HIV-1)

Strategy 1. HIV-1 EIA/WB/NAAT

B2 Individual HIV-1 NAAT(option for initial plasma submissions)

Positive for HIV-1 antibodies and HIV-1 RNA

Positive Negative Indeterminate

Negative* Positive**

* HIV-1 RNA not detected, however, a WB or IFA should be performed to confirm the absence of HIV-1 antibodies. Medical follow-up for further evaluation and testing may be required.** It may be necessary to repeat a positive NAAT for confirmation† If window period infection is suspected, refer to Acute HIV Infection Testing, Strategy 4 ∞ If HIV-2 infection is suspected, refer to HIV-2 Testing, Strategy 5

OR


US Army HIV Diagnostic Algorithm

Genetic Systems rLAV

(+) (-)

Negative for HIV-1 antibodies

Vironostika HIV-1 Microelisa

(- -)

Genetic Systems HIV-1 WB

(- +) or (+ +)


Methods

• Division of Human Subjects Protection: assent to this de-identified analysis and presentation

• Test results 2002-2007(June) used to calculate number and percent of initially reactive that were not repeat reactive

• Final WB was the gold standard • Indeterminate WB’s excluded from analysis• Test results from 2007 were used for ROC

analysis


Results: Composition of Test SubjectsN = 6,236,874

ARMY 55%

USCG 1%

MEPS 32%

USAR 3%

USANG 9%

MEPS: Military Entrance Processing Station; USAR, U.S. Army Reserve; USANG, U.S. Army National Guard; and USCG, U.S. Coast Guard


Results

Samples screened 6,236,874

rLAV Reactive 16,415

Vironostika Repeat Reactive 4,142

WB Indeterminate (excluded) 650

WB Positive 4,009

Overall HIV-1 seroprevalence 0.06%


Results Overall

rLAV Vironostika in Duplicate

Samples Screened

6,236,874 16,415

Prevalence of WB+ samples

0.06% 24.4%

Positive Likelihood Ratio

502.41 93.28

Positive predictive value

24.42%

(23.77-25.09)

96.79%

(96.21-97.31)

16415

4142 4009

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

Initial React Repeat React WB Positive

Second Screen Yields 98.9% Reduction in unnecessary

WB’s


HIV-1 Prevalence by Force Component

P-value < 0.001


HIV-1 Prevalence by Year

P-value for trend < 0.001


rLAV-Positive Predictive Value (95% CI)by Force Component

HIV-prevalence 0.07% 0.03% 0.06% 0.10% 0.05% 0.06%

Pos

itiv

e P

redi

ctiv

e V

alue

(%

)

P-value < 0.001


rLAV-Positive Predictive Value (95% CI)by Year

HIV-prevalence 0.06% 0.06% 0.06% 0.06% 0.07% 0.08%


Pos

itiv

e P

redi

ctiv

e V

alue

(%

)


rLAV-Positive Likelihood Ratio by Year

0

100

200

300

400

500

600

700

800

900

2002 2003 2004 2005 2006 2007



Repeat React-Positive Predictive Value (95% CI)by Force Component

Pos

itiv

e P

redi

ctiv

e V

alue

(%

)

P-value = 0.073


Repeat React-Positive Predictive Value (95% CI)by Year

Pos

itiv

e P

redi

ctiv

e V

alue

(%

)

P-value for Trend = 0.972


Repeat Reactive Positive Likelihood Ratio by Year

0

20

40

60

80

100

120

140

2002 2003 2004 2005 2006 2007

P-value for trend = 0.972


rLAV-ROC analysis

Cut-off-pointLR+

(95% CI)

PPV

(95% CI)

>= 1 (reference)12.3

(11.3-13.3)

32.0

(28.6-35.5)

>= 287.2

(69.1-110.1)

77.0

(71.7-81.5)

>= 3254.4

(170.7-379.4)

90.7

(86.3-93.8)

>= 3.79**407.1

(245.6-674.9)

94.0

(90.1-96.5)

>= 4506.7

(287.9-891.9)

95.1

(91.4-97.3)

** cut-off-point estimated by ROC analysis

2007 data only, N=512,776


Vironostika-ROC analysis

Cut-off-pointLR+

(95% CI)

PPV

(95% CI)

>= 1 (reference)227.2

(155.9-330.9)

89.7

(85.2-93.0)

>= 21022.2

(459.4-2274.4)

97.5

(94.4-99.0)

>= 2.821533.2

(575.6-4084)

98.3

(95.5-99.5)

>= 42035.6

(656.7-6310.2)

98.7

(96.0-99.7)

>= 52727.2

(681.7-10910.5)

99.1

(96.3-99.8)

** cut-off-point estimated by ROC analysis

2007 data only, N=735, 16 (2.18%) discordant, all discordant are negative by WB


Discussion

• rLAV PPV driven by low prevalence• Unnecessary confirmatory testing driven by

screening PPV• What is the effect of using two different EIA’s for

primary and secondary screening?• Limitations: analysis of clinical testing data

– Vironostika production ceased– Unknown what % of rLAV reactive/Vironostika (-/-)

would have been WB positive but should be very small given high Vironostika sensitivity

– WB is an imperfect gold standard


Discussion – Cont’d

• Two-tier approach for initial screen?: – high s/coconfirmatory test– lower s/cosecondary screen

• Increasing rLAV PPV probably multifactorial:– Slight increase in seroprevalence– Slight increase in specificity based on manufacture’s

risk analysis of recombinant production and plate coating

• Performance of secondary screen in duplicate the same as in singleton.


Conclusion

Secondary EIA screening substantially reduces the number of unnecessary confirmatory tests required, and should continue to be the standard for laboratory based testing algorithms in low HIV prevalence populations.

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CDC/APHL HIV Diagnostics Conference 5-7 Dec 07Page 1 Usefulness of a Secondary EIA Screen in a Low HIV Prevalence Population Robert J. OConnell, MD FACP