Download Basics of HIV Resistance and Testing

Basics of HIV Resistance
and Testing
Jorge Villacian, MD
Virco
TREAT Asia Annual Network meeting
Bangkok, Thailand
11 October 2009
Overview
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Review basic concepts on Resistance
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Determine how resistance tests work and are
interpreted
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When should resistance tests be used?
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What is the relevance of the Resistance
phenomenon and what do we know about
resistance to new classes?
Overview
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Review basic concepts on Resistance
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Determine how resistance tests work and are
interpreted
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When should resistance tests be used?
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What is the relevance of the Resistance
phenomenon and what do we know about
resistance to new classes?
What is Resistance?
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The reduced susceptibility of a patient’s viral
isolate to suppression by an antiviral drug
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A change that improves viral replication in the
presence of an inhibitor
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The point at which an ARV agent can no
longer effectively inhibit viral reproduction
HIV-1: Replicative Cycle
Wild Type Virus
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Non-mutant, drugsusceptible virus
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No previous effect from
medication
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Reference virus
Quaisi-Species
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Viral isolates are composed
of various groups of virus
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Wild Type (Sensitive)
Mutated (Resistant)
Mutated (Non-resistant)
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Acquired resistance
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Selective pressure from
current medication
Selective Drug Pressure
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EFV
Drug pressure drives selective
forces for genetic changes in
the viral genome
Mutations arising under ART
allow virus to escape from the
inhibitory effect of the drug
Mutations that develop are
associated with ARV agents
being administered
“Minority variants” — <20% of
population
FTC
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TDF
ATRIPLA
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Increasing amount of
resistant mutations are able
to develop
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No longer minority variants
EFV
Ongoing replication under
selective pressure…
FTC
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TDF
Selective Drug Pressure
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Ongoing replication under
selective pressure…
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Increasing amount of resistant
mutations are able to develop
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What happens if ARVs are
discontinued?
EFV
FTC
TDF
Selective Drug Pressure
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EFV
FTC
TDF
Selective Drug Pressure
In absence of ARV pressure,
resistant clones are “overgrown”
with Wild Type virus and fade to
“undetectable”
Resistance is a genetic
characteristic, so it is “archived”
and can be re-expressed rapidly
Absence of resistance on RT
does NOT guarantee
susceptibility!
Clinical history is critical
Archived Resistance
Overview
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Review basic concepts on Resistance
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Determine how resistance tests work and are
interpreted
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When should resistance tests be used?
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What is the relevance of the Resistance
phenomenon and what do we know about
resistance to new classes?
Types of Resistance Tests
and a Few Examples
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Genotype
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Phenotype
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TruGENER (Siemens)
Antivirogram® (Virco)
PhenoSense™ (Monogram)
Calculated Phenotype:
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Virco®TYPE HIV-1 (Virco)
HIV Resistance Testing Assays
RESISTANCE
• The (in)ability of HIV to replicate in the presence of Antiretroviral Drugs
• Caused by changes in relevant parts of the virus genome (mutations)
Genotyping
Assay
Calculated
Phenotyping Assay
Conventional
Phenotyping Assay
• Indirect measure of the
viral susceptibility to
Antiretroviral Drugs
• Correlative database,
frequently updated
with GT and PT
• Based on sequence
(mutations) of relevant
parts of the viral
genome
• PT fold change of
virus is calculated
from mutations in GT,
with interpretation
supported by clinical
outcomes data base
• Direct measure of the
ability of the virus to
grow in the presence
of antiretrovirals
• Requires interpretation
of sequence
information
• QUALITATIVE
• QUANTITATIVE
• Compared to
laboratory reference
strain
• QUANTITATIVE
GENOTYPE
Genotypic assays step by step
PLASMA
(> 200 µl)
Viral Gag/PR/RT gene isolation
total RNA
extraction
cDNA
RT
Gag/PR/RT GENES
(amplicon)
PCR
PATIENT
TCGATGTAC
Interpretation
-- Translate into aminoacids
-- Compare wild type vs sample
-- Identify mutational patterns (rules,
expert opinion, etc.)
Automatic
sequencing
Target genome regions
P7/P1
P1/P6
RT
PRO
GAG
polymerase
INT
IN
RNaseH
560
1
Affymetrix
Bayer
Celera
ViroLogic
Virco
242
300
330
303
400
www.iasusa.org
Mutations Selected by nRTIs
Abacavir
Didanosine
Emtricitabine
Lamivudine
Stavudine
Tenofovir
Zidovudine
Interpreting Resistance
from Genotypic Reports
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Single mutation can confer resistance
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M184 (3TC)
D30N (NFV)
I50L (ATV)
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Pairs of mutations
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Multiple or stairwise accumulation of
mutations
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LPV/r
DRV/r
AZT (NAMs)
ETR
Multi-NRTI mutations: K65R, Q151M
Advantages and Disadvantages
of Genotype Testing
Advantages
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Rapid turnaround
(1-2 weeks)
Less expensive
Widely available
More sensitive than
conventional phenotype
for detecting mixtures of
resistant and wild-type
virus
Disadvantages
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Indirect measure of
resistance
Relevance of some
mutations unclear
Complex mutational
patterns may be difficult
to interpret
No standardized
algorithms for
interpretation of
sequences
PHENOTYPE
Conventional Phenotype
Testing
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Measures laboratory susceptibility of an HIV
isolate to a given drug
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Measures the concentration of drug needed
to inhibit the replication of a patient's virus
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Degree of resistance is quantified
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Compares the fold-change in drug
concentration required to inhibit the
replication of the patient's virus compared to a
representative, wild type, sensitive virus
isolate
Phenotypic Susceptibility: Relationship
Between Drug Concentration and Viral
Inhibition
Inhibition of Virus Replication (%)
100
Wild-type
Resistant
Fold Change = 10
Fold resistance
50
IC50 100uM
IC50 10uM
0
Wild-type IC50
=10uM
Resistant IC50
=100uM
Drug Concentration
= 10
Numbers need to be interpreted
according to cut-points: Biological
cut offs
# samples
BCO = 97.5th percentile
Wild‐type distribution
1
28
10
1.7
Fold‐change 100
Advantages and Disadvantages of
Conventional Phenotype Testing
Advantages
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z
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Provides direct and
quantitative measure of
resistance
Often uses clinical cutoffs
(CCO) derived from
clinical cohorts to define
spectrum of resistance
Indicates which drugs
may have partial activity
Can assess interactions
among mutations
Disadvantages
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Clinical cut-offs not
defined for some agents
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Complex technology with
longer turnaround (~ 3
wks)
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More expensive than
genotyping
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Limited laboratories
perform testing
VIRTUAL
PHENOTYPE
Correlative and Clinical Outcomes
Databases*
• Routine clinical testing
• Clinical trials
• Research collaborations
Genotypic
data >314,000
Phenotypic
data >86,000
Correlative database >53,000 G/Ps
Nucleotide
sequence
(…AAGTC
TCCGCAT
GCATA…)
VirtualPhenotype™-LM engine
Calculated
fold change
values in
IC50
Clinical Outcomes Database
>21,000 patients or
>8,800 Treatment Change Episodes
Clinical
Cut-Offs
*Status July 07
Creating the Phenotype from
the Genotype
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Define mutations/pairs which impact the Fold
Change for each drug
Two factors in Virco G/P database:
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The “Weight”: How much this mutation/pair changes
the phenotypic Fold Change
The “Direction”: Does this mutation/pair lead to more
resistance or more drug susceptibility?
Each mutation (single and pairs) analyzed for these
two factors
A total “score” is created from the sum of these
factors Æ the calculated “fold change”
FC Assessment: Example of Tipranavir PI
Mutation Analysis
3I, 10I, 14R, 19I, 24I, 37N, 41K, 46I, 53Y, 54V, 55R, 63P, 64V, 71V, 82T, 84V
10C & 33F 13A & 47V
10F
13V & 15V
10F & 47V 13V & 34Q
10F & 54M 13V & 36I
10F & 58E 13V & 43S
10F & 82C 13V & 71L
10F & 82F 13V & 71V
10F & 82L 13V & 82F
10F & 84A 13V & 84V
10F & 84V
14T
10I & 13A 15V & 43I
10I & 33M 15V & 95F
10I & 82F
16A
10I & 82I
18H
10V
20R & 35D
10V & 34A 20R & 53L
10V & 84V 20R & 70E
10V & 88D 20T & 33F
10Y & 13V 20T & 41K
12S & 69K 20T & 53L
Decrease in FC
20T & 73T 33I & 35G
35N
20T & 84V 33I & 36I 35N & 43T
20V
33I & 82A 35N & 70E
22V
33I & 95F 35N & 82F
24F & 60E
33V
36A
24I
33V & 43T 36I & 83D
24I & 33F 33V & 54V 36I & 84V
24I & 50V
34D
36L & 53L
24I & 82T 34D & 58E 36L & 84V
30N
34N & 82A 36V & 82F
30N & 50V 34Q & 36I 36V & 84V
30N & 88D 34Q & 54V 38W
33.1Q
35D
41K
33F
35D & 36I 41K & 54V
33F & 36L 35D & 36V 41T & 70E
33F & 48A 35D & 54M 43I & 55R
33F & 50V 35D & 54V 43Q & 73T
33F & 60E 35D & 84V
43T
33F & 66L 35D & 89V 43T & 82F
33F & 82F
35G
43T & 82T
43T & 85L
45I
45Q
45V
46L
46L & 48M
46L & 50L
46L & 80I
46L & 82L
46L & 84V
47V
47V & 54M
47V & 54V
47V & 69K
47V & 82A
47V & 82I
47V & 84V
48A
48E
48M
48Q
48S
48V
48V & 54A
48V & 54S
48V & 54V
48V & 71V
48V & 82A
48V & 84V
50L
50V
50V & 58E
50V & 70E
50V & 76V
53L
53L & 82F
53L & 82I
54A
54A & 82A
54A & 82F
54A & 84V
54L
54L & 76V
54L & 82A
54L & 82S
54M
54M & 83D
54M & 88D
54S
54S & 74S
54S & 82A
54S & 84V
54T & 82T
54V & 84V
55R
55R & 60E
55R & 95F
58E
58E & 80I
58E & 89V
60E
82L
60E & 71V
82S
60E & 82A
82T
60E & 95V
83D
66V
83D & 84V
69K
84A
71V & 73T
84V
71V & 74E
85V
74A
88D
74P
88G
74P & 82S
88S
74P & 84V
89M
74S
89V & 95L
76V
90M
79S
91P
82C
95F
82C & 95F
95V
82F & 89V
82G
82I & 89V
Increase in FC
FC Assessment: Example of Tipranavir
Mutation Analysis: Defining FoldChange
PI Mutations Detected and Evaluated
3I, 10I, 14R, 19I, 24I, 37N, 41K, 46I, 53Y, 54V, 55R, 63P, 64V, 71V, 82T, 84V
Mutations
24I
41K
55R
82T
84V
24I & 82T
41K & 54V
54V & 84V
Intercept (no mutations)
Resistance Weight Factor: weight and direction
for mutations which impact TPV
Linear Models DB0704 implemented on DEC18, 2007
RWF
-0.18198
-0.06075
0.05418
0.36480
0.16181
-0.10545
0.03803
0.20493
-0.06039
Log(FC) = 0.415
FC = 100.415 = 2.6
Types of Cut-Offs
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Biological Cut-Offs (BCO)
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Define what is resistant and non-resistant based
on how a patient’s virus responds to a drug
in vitro
Clinical Cut-Offs (CCO)
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Define what is resistant and non-resistant based
on how a patient’s virus responds to a drug in vivo
34
Example Report
Advantages and Disadvantages of
Calculated Phenotype Testing
Advantages
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Require less interpretation
of complex genotypes
Less expensive, quicker
than conventional
phenotyping
Assess impact of
interactions between
mutations
Equivalent virologic
outcomes in clinical trials to
conventional phenotyping
Available from many
reference labs
Rapid turnaround
Disadvantages
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z
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Not an actual measured
phenotype; a calculated
phenotype based on
genotypic information
Reliability will depend on
the accuracy of the
genotype
Only one source but widely
distributed through many
labs that perform
genotyping
Slightly more expensive
than genotype alone
Overview
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Review basic concepts on Resistance
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Determine how resistance tests work and are
interpreted
z
When should resistance tests be used?
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What is the relevance of the Resistance
phenomenon and what do we know about
resistance to new classes?
When to Use Resistance
Testing
IAS-USA[1]
DHHS[2]
European[3]
Primary/acute
Recommend
Recommend
Recommend
Postexposure
prophylaxis
--
--
Recommend*
Chronic, Rx
naive
Recommend
Recommend
Recommend
Failure
Recommend
Recommend
Recommend
Pregnancy
Recommend
Recommend
Recommend
--
Recommend
Recommend
*Test source patient especially if treated with antiretroviral drugs.
Pediatric
1. Hirsch MS, et al. Clin Infect Dis. 2008;47:266-285.
2. November 2008 DHHS Guidelines. Available at: http://www.aidsinfo.nih.gov.
Accessed November 10, 2008.
3. EACS Guidelines Version 3. Available at: http://www.eacs.eu/guide/index.htm.
Accessed October 24, 2008.
Limitations of Resistance
Testing
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High cost compared with other tests routinely
used in HIV care
Cannot be reliably performed when HIV RNA
<500-1,000 copies
May not be able to detect minority
populations of resistant virus (<20%)
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Especially common after drug discontinuation
Resistant strains in viral reservoirs are not
detected
Which Resistance Test and
When?
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The utility of phenotypic resistance
information increases with treatment
experience/mutations complexity
Phenotypic Information
Genotypic Information
Treatment Experience/Mutational Complexity
When To Use Resistance Testing
Naïve Patients / Starting Therapy
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If resistance mutations are not detected, it is
still possible that the patient has been
infected with a drug-resistant strain
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The lack of drug pressure can cause the wildtype strain to dominate and minor resistant
species may not be detected
When To Use Resistance Testing
On Therapy
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Virologic failure: assist in selecting active
drugs for next regimen
Suboptimal viral load reduction
Perform while patient is taking ARV agents or
immediately after discontinuing therapy
(within 4 weeks)
All pregnant women prior to initiation of
therapy and for those entering pregnancy
with detectable viremia while on therapy
DHHS Treatment Guidelines, January 29, 2008.
Resistance Testing in Clinical
Practice
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Genotype preferred for
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Treatment naive: acute or chronic infection
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Early virologic failure
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Patient no longer receiving therapy
Phenotype or combined phenotype/genotype
preferred for
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High-level resistance to NRTIs or PIs on genotype
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Multiple regimen failure with limited treatment options
Virtual phenotype also used in settings where
phenotypic testing would be preferred
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Virtual phenotype is a type of complex interpretation of genotype
data, intended to predict phenotypic response
Overview
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Review basic concepts on Resistance
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Determine how resistance tests work and are
interpreted
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When should resistance tests be used?
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What is the relevance of the Resistance
phenomenon and what do we know about
resistance to new classes?
Resistance is associated with
worse clinical outcomes
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In multivariable analyses, patients with drug resistance mutations to ≥ 2 classes
during first 2 years of HAART at significantly higher risk of AIDS progression or
death
Definition of Resistance
Adjusted RH (95%
CI)
P Value
Drug-class resistance mutations
ƒ
≥1 NRTI mutation
1.52 (1.14-2.03)
.004
ƒ
≥1 NNRTI mutation
1.95 (1.28-2.95)
.002
ƒ
≥1 PI mutation (major and minor)
1.50 (1.14-1.97)
.004
ƒ
≥1 PI mutation (major only)
1.79 (1.28-2.50)
.0007
Cumulative drug-class resistance
(major and minor PI mutations counted)
ƒ
Virologic failure with no resistance
1.32 (0.57-3.06)
.52
ƒ
Single-class resistance
1.03 (0.65-1.63)
.90
ƒ
Double-class resistance
1.55 (1.15-2.08)
.004
1.80 (1.20-2.70)
.005
ƒ Triple-class resistance
Cozzi-Lepri
A, et al. AIDS. 2008;22:2187-2198.
Summary of Key Conclusions
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Emergence of drug resistance within 2 years of
initiating HAART in EuroSIDA cohort associated with
long-term clinical outcomes
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z
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55% increased risk of new AIDS events or death among
individuals who developed double-class resistance
80% increased risk of new AIDS events or death among
individuals who developed triple-class resistance
Mechanism driving association unknown
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Possibly due to suboptimal adherence or direct effect of
resistance
Cozzi-Lepri A, et al. AIDS. 2008;22:2187-2198.
Resistance Scoring
● Genotypic susceptibility
score = sum of genotypic
resistance scores for each
drug in regimen
■ Based on rule-based
algorithms using predefined
drug-resistance mutations
● Phenotypic susceptibility
score = sum of phenotypic
resistance scores for each
drug in regimen
■ Based on FC in susceptibility
of test sample relative to
control (wild-type) isolate
Š 1.0: susceptible
Š 1: susceptible
Š 0.5: possibly resistant
Š 0: resistant
Š 0: resistant
Š Between 0 and 1: partially
susceptible
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Focus on Number of Active
Agents
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DHHS antiretroviral guidelines: ≥ 2, preferably 3, fully active agents
in new regimen
Highest rate of virologic suppression in patients receiving
investigational drug plus OBR containing ≥ 1 other active agent[1-4]
Trend toward greater benefit with 3 vs 2 fully active agents[1-4]
z
z
z
z
Not statistically significant
Must also consider potential drug-drug interactions, adverse events, pill
burden, absence of future options
Contribution of “partially active” agents (eg, 3TC) difficult to calculate
No added benefit from using 4 vs 3 fully active agents
1. Cooper DA, et al. N Engl J Med. 2008;359:355-365. 2. Haubrich R, et al. CROI 2008.
Abstract 790. 3. Johnson M, et al. CROI 2008. Abstract 791. 4. Nelson M. CROI 2007.
Abstract 104aLB.
BENCHMRK-1 & -2: HIV-1 RNA <
50 c/mL at Week 48, Overall and
by GSS
Subgroup
n
Total
443
228
GSS:
0
112
65
1
166
92
2
109
47
≥3
49
21
RAL
Patients (%)
Placebo
64
34
45
3
67
37
77
62
71
52
0
20
Cooper DA, et al. N Engl J Med. 2008;359:355-365.
40
60
80
100
DUET-1 and -2: HIV-1 RNA < 50
c/mL at Week 48, by Active Agents
in OBR
100
Placebo (n = 604)
76
80
0
1
≥2
No. of Active Agents in OBR by PSS
(DRV Considered Active if FC < 40)
Haubrich R, et al. CROI 2008. Abstract 790.
Johnson M, et al. CROI 2008. Abstract 791.
187/305
51/196
0
121/203
0
26
0/35
20
33
229/300
60
40
61
60
12/36
Patients With HIV-1 RNA
< 50 copies/mL at Week 48 (%)
ETR (n = 599)
BENCHMRK 1 & 2: RAL
Resistance at Virologic Failure
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492 patients treated with RAL
105 (23%) had virologic failure
Genotype available at baseline and after
virologic failure for 94 patients
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68% (64/94) had genotypic evidence of RAL
resistance
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Nearly all (62/64) had mutations at position 143, 148,
and/or 155
Cooper DA, et al. N Engl J Med. 2008;359:355-365.
Integrase Inhibitor CrossResistance
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In RAL study, resistance to ELV with mutations at positions 148 and
155[1]
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Patterns associated with high-level resistance to both RAL and ELV
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G140S/Q148H
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G140S/Q148R
In ELV study, mean decrease in susceptibility[2]
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To ELV: > 151-fold (range: 1.02- to 301-fold)
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To RAL: > 28-fold (range: 0.78- to > 256-fold)
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No significant short-term virologic response to RAL in 2 patients
switched from ELV/RTV to RAL following failure[3]
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Cross-resistance is a clear issue with first-generation of agents
1. Hazuda DJ, et al. HIV Resistance Workshop 2007. Abstract 8. 2. McColl DJ, et al.
HIV Resistance Workshop 2007. Abstract 9. 3. DeJesus E, et al. IAS 2007. Abstract
TUPEB032.
Phenotypic Biological Cutoff
for RAL
Host
Conclusions
Bug
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Drug
The resistance phenomenon is a relevant factor
in choosing antiretroviral treatment regimens
Knowledge of the different methods to detect
resistance is important in order to correctly
interpret their results
Resistance has been demonstrated in new drug
classes and cross-resistance may be a limiting
factor in the future
Resistance is one of the multiple factors that
influence treatment response