HIV Incidence Assays: Current Status and the Way Forward

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HIV Incidence AssaysCurrent Status and the Way
Forward
Improving lives, knowledge, and understanding
IAS 2009 Cape Town, South Africa 21 July 2009
Timothy Mastro, MD Family Health International
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Presentation Outline

• Why measure HIV incidence?
• HIV incidence assays - how did we get where we
  are today?
• New insights developments
• The way forward

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At this stage of the epidemic
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Why Determine HIV Incidence?

• Characterize the epidemic in a population
• Monitor changes over time
• Identify important sub-populations for
  interventions
• Assess impact of programs
• Identify populations for HIV intervention trials
• Endpoint of intervention trials
• Identify individuals for interventions
• Prioritization
• Interrupt transmission

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Standard Methods for Incidence Determination are
Unsatisfactory

• Indirect methods repeat cross-sectional
  measurements modeling
• Prospective follow-up is expensive and
  unrepresentative
• Enrollment in cohorts leads to behavior change
• Back calculation methods not timely or reliable

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HIV Incidence Using Early Diagnostic Tests
seroconversion
Response
RNA Ab-
P24 Ab -
Brookmeyer, Quinn. Am J Epi 1995
RNA
Ab
infection
p24
Detection limit
days
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Development of Assays for Serologic Testing
Algorithms for Recent HIV Seroconversion
(STARHS)orRecent Infection Testing Algorithms
(RITA)
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July 1998
Abbott EIA 3A11 assay sensitive/less-sensitive
(detuned)
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Recent Infection Testing Algorithm (RITA)
seroconversion
RITA duration
Response
Antibody cutoff Quantity (LS-EIA) Proportion
(BED) Avidity Isotype Specificity of Ag
RNA
Ab
infection
p24
Detection limit
days
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RITA and Misclassification
Mis-Classified
Long-standing
SOD
Cutoff
Misclassified Recent
Mean
Days
170 days
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HIV Incidence and RITACross-Sectional Surveys
F1 x N(recent)
Incidence
X 100
N(neg) F1 x N(recent)
F1 365/RITA duration
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HIV Incidence and RITACross-Sectional Surveys
Survey size 1000 HIV-seropositive 100
(10) Recent on incidence assay 10 RITA
duration 170 days 2.15 x 10 Incidence
x 100 2.33 per year 900 21.5
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RITA and Misclassification
Mis-Classified
Long-standing
SOD
Cutoff
Misclassified Recent
Mean
Days
170 days
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-BED competitive capture EIA -Indirectly measures
HIV-IgG as a proportion of total IgG
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127 days
181 days
171 days
167 days
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(No Transcript)
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UNAIDS Reference Group Statement on Use of the
BED Assay for HIV Incidence Estimation, Dec. 2005

• Reviewed data from multiple studies from Africa,
  Asia and lab validation studies
• suggests that the current BED-based method
  overestimates incidence.
• incidence of a third to a half of prevalence.
• appears 2-3 times higher thanother methods
• recommends that at present the BED-assay not be
  used for routine surveillance applications.

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2006
Proposed adjustments for false-recent
misclassification.
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2008
Proposed determination and use of a factor
epsilon ( e ) to correct for misclassification of
long-standing infections as recent.
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Challenges to Using Antibody Maturation to
Identify Recent Infection

• Variable immune response among individuals
• Antibody response related to viral level
• Variability by HIV-1 subtypes
• False-recent status
• Elite controllers (low viral levels)
• Accumulate in population
• ART use (low viral levels)
• Advanced HIV disease (AIDS)

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Assay Calibration and Validation

• Requires large numbers of well-characterized
  seroconversion panels
• Various populations and sub-populations
• Geographic, transmission modes, etc.
• Various HIV-1 subtypes
• Early and long-standing infections
• Co-infections (TB, malaria)
• Such specimens arent readily available in
  sufficient volume in a central location

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SAMJ March 2007
Use of the BED assay on dried blood spot
specimens from a national household HIV survey to
estimate HIV incidence. Adjusted incidence
estimates reflected the underlying transmission
dynamics in South Africa.
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August 2008
Representative household survey 18,525 with
blood specimens HIV prevalence 6.4 HIV
incidence 2.6 (BED unadjusted) HIV
incidence 1.8 (BED adjusted)
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RITA Assays

• Detuned assays
• Abbott 3A11 - unavailable
• bioMérieux Vironostika HIV-1 unavailable
• BED-Capture EIA, (Calypte)
• Avidity assays
• Run on Abbott AxSYM
• Run on Ortho Vitros analyzer
• IDE-V3 assay
• IgG3 anti-HIV
• Inno-LIA HIV adaptation

Murphy G, Parry JV. Eurosurveillance. 2008
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New Insights andDevelopments
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Perspectives on HIV Incidence Assays and Uses
Biologists
Epidemiologists
Program Implementers
Assay Developers - Industry
Funders
Statisticians
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Meeting of Experts Chapel Hill, North
Carolina 13-14 May 2009
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Key IssuesChapel Hill Meeting, May 2009

• Need to clarify terminology
• Review of market assessment
• Explore new biomarkers
• Establish optimal specifications and requirements
• Identify critical path to advance assays
• Industry perspectives
• Define the infrastructure and specimens required
  for assay validation

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Innovations in Incidence Estimation Methods

• A new paradigm for incidence estimation from
  cross-sectional data. T.A. McWalter and A.
  Welte, SACEMA
• IAS-2009 MOPDB-105
• URL for Assay Based Incidence Estimation
  spreadsheet
• http//www0.sun.ac.za/sacema/collaboration/ABIE/

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X
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False Incident BED vs. Avidity Individuals
Infected gt365 Days and on ARVCanadian Cohort
N73
BED
Avidity
Less false recent infections with Avidity
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Chronically Infected Virally Suppressed Subjects
on ARVs (VL lt 400 cps/ml)
Classified Incident
ARV therapy has less effect on avidity
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Algorithm for Incidence TestingRakai 2002
HIV EIA WB
8488
Avidity Assay
315
319
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Issues to Address and the Way Forward
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Summary

• Current HIV incidence assays are imperfect tools
• False-recent misclassification is a problem
• Guidance on use is evolving
• Market forces are not driving assay development
• Multi-test algorithms have promise
• We know how to evaluate assays, but the required
  specimens are not readily available
• Mathematical issues are being resolved

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What Needs to be Done

• WHO Technical WG on HIV Incidence Assays
• www.who.int/diagnostics_laboratory/links/hiv_incid
  ence_assay
• Guidance on assay use
• Solidify consensus on mathematical issues
• Define the assay development pathway
• Define and assemble specimens for assays
  calibration and validation
• Engage industry on assay development

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Lets make sure the glass is filled
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Acknowlegements

• Oliver Laeyendecker
• Sue Eshleman
• Bharat Parekh
• Bernie Branson
• Andrea Kim
• Connie Sexton
• Mary Lynn Baniecki
• Karine Dube
• Megan Averill
• Renee Ridzon
• Bill Rodriguez
• Christine Rousseau

• Mike Busch
• Chris Pilcher
• John Kaldor
• Txema Garcia-Calleja
• Gaby Vercauteren
• Thomas Rehle
• Alex Welte
• Tom McWalter
• Tim Hallett
• Mike Cohen
• Joanne Micallef
• Gary Murphy

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Evolving Guidance on Use of the BED Assay

• Office of the US Global AIDS Coordinator, Nov.
  2006
• Use with appropriate adjustments and expert
  consultation
• Sentinel or population-based surveillance
• Evaluation of HIV prevention interventions
• Case-based surveillance
• Only under certain circumstances
• More recent guidance
• Carefully consider populations and uses
• Determine use of ART
• Determine CD4 counts
• Expert consultation on samples sizes
• Use adjustments for misclassification
• Dont conduct incidence testing if above cant be
  assured

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CDC Statement on Use of BED for STARHS in
Surveillance in the United States, 2006-2007

• BED in combination with the appropriate estimator
  is the preferred method to estimate HIV incidence
  in the US
• Estimator attempts to eliminate bias due to
  sampling method. Testing probability is
  accounted for in estimates
• To be used in case-based surveillance where
  clinical and epidemiologic information is
  available
• US system able to identify persons with AIDS or
  on ART HIV-1 subtype B accounts for 95 of
  infections
• Additional data on false recent rates will
  improve accuracy