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HIV-1
Drug Resistance Testing in Adults: Updated Recommendations
of an IAS-USA Panel
Recommendations
of the International AIDS Society USA (IAS-USA)
panel regarding HIV-1 drug resistance testing were published in
1998 and again in 2000. At the time of the most recent report, many
issues remained unclear with respect to the use of these assays
in various clinical situations.
These
included the relative merits of phenotypic and genotypic testing,
criteria to define the likelihood of clinical response, long-term
clinical benefits of testing, and the cost-effectiveness of resistance
testing as a routine part of patient monitoring. Numerous studies
have now addressed many of these issues.
Moreover,
data have emerged documenting the seriousness of the problem of
HIV-1 drug resistance in previously treated and untreated patient
populations.
This
new information emphasizes the need for better education on how
to use resistance testing and for updated guidelines on how to use
antiretroviral drug combinations most effectively to prevent or
treat drug resistance.
In
addition, subsequent studies have identified concepts not addressed
in previous reports. These
include the importance of hypersusceptibility in predicting response
to nonnucleoside reverse-transcriptase inhibitors (NNRTIs), the
impact of HIV-1 subtype and human leukocyte antigen type on patterns
of HIV-1 drug resistance, the extent of cross-resistance among antiretroviral
drugs, and the utility of ratios of trough level to IC50
in predicting response to antiretroviral regimens. These concepts
are more fully explored in the new report, which is published in
the July 1, 2003 issue of Clinical Infectious Diseases.
In
1997, the International AIDS SocietyUSA selected
a panel of experts to develop consensus recommendations on the potential
clinical role and limitations of drug resistance testing.
The
panel membership comprises physicians and scientists with expertise
in basic science, clinical research, and patient care related to
antiretroviral therapy and HIV drug resistance. Balance in perspective,
US and international clinical and research experience with different
assay methodologies, and a broad range of views on the roles and
limitations of drug resistance testing were considerations in the
selection of members.
For
its initial reports, the panel considered data from the published
literature and abstracts from relevant scientific conferences since
the recognition of HIV drug resistance in 1989. For this updated
report, the panel members reviewed newly available published and
presented information regarding HIV drug resistance since 2000.
Prospective
randomized trials have shown at least short-term virological benefits
for both genotypic and phenotypic resistance testing in a variety
of situations. Moreover, emerging data indicate that viral drug
resistance is a problem wherever treatment is used, and it may be
increasing in importance.
It
has also become clear that knowledge concerning patterns of resistance
and cross-resistance is critical to the development of successful
sequencing of antiretroviral regimens.
 Resistance
Testing Assays
There
are 2 general types of resistance testing assays: genotypic assays
(i.e., HIV gene sequencing to detect mutations that confer HIV drug
resistance) and phenotypic assays (i.e., drug susceptibility testing
of plasma virus).
Genotypic
testing to detect mutations associated with drug resistance may
be performed using assay kits or in-house techniques. There is a
high level of concordance (97.8%) between 2 commercial assay kits
when tests are performed by the same laboratory for detection of
resistance mutations.
In
80% of cases, discordance was due to differences in detection of
mixed wild-type and mutant populations by the 2 assays. Earlier
quality assurance evaluations have demonstrated under-diagnosis
of resistance mutations and inter-laboratory variation in the quality
of genotyping, independent of the technology used, especially when
mixtures of wild-type and mutant virus were present.
Performance
was related to the experience level of the laboratory, suggesting
that appropriate operator training, certification, and periodic
proficiency testing are essential for proper genotyping. Some regulatory
authorities now require such training.
Appropriate
interpretation of the results of HIV-1 drug resistance testing remains
a challenging problem for both phenotypic and genotypic assays.
Results of genotypic tests are interpreted by individual judgment
by consulting lists of drug resistance mutations or by computerized
rules-based algorithms that classify the virus as "susceptible,"
"possibly resistant," or "resistant" to each
antiretroviral agent.
The
construction of rules-based algorithms for interpretation of genotype
is a lengthy and difficult process that requires frequent updating.
Extensive variations exist among the different available algorithms
in the classification of expected drug activity. This variation
appears to be drug related and more important for the NRTIs and
PIs.
Differences
in how drug resistance is scored complicate comparisons among the
algorithms. Ideally, algorithms for interpretation of genotype should
be based on studies correlating the viral genotypic profile at baseline
with the virological response to treatment (e.g., a decrease in
the plasma HIV RNA level). The mutational profiles that predict
a lack of virological response have been developed only for a few
drugs.
An
alternative approach to interpretation of genotype is the "virtual"
phenotype, which uses genotypic data to determine the likely in
vitro drug susceptibility of a particular virus on the basis of
data from matching viruses in a large database of virus samples
with paired genotypic and phenotypic data.
Viruses
in the database with genotypes that match the test virus are identified,
and the average phenotype for all the available matches in the database
is calculated. With a sufficiently large database, there is a high
likelihood that a reasonable number of matches can be found for
most genotypes encountered in practice. The actual and virtual phenotypes
show excellent correlation for most drugs.
A
potential limitation of this approach is that the level of confidence
placed in the result depends on the number of matching genotypes
in the database and on selecting the appropriate codons to incorporate
into the search. Matches are based on positions pre-selected as
relevant for each drug, not the entire sequence. Correlation between
actual and virtual phenotype most likely will be weaker for newer
drugs or in cases in which there are fewer matches because of unusual
genotypes.
Results
of phenotypic testing usually are expressed as the fold-change in
susceptibility of the test sample compared with a laboratory control
isolate. Previously, cutoffs for defining "susceptible"
and "resistant" viruses were based on the inter-assay
variation of the controls (the "technical" cutoff). Testing
laboratories have shifted to the use of "biologic" cutoffs,
which are based on the normal distribution of susceptibility to
a given drug for wild-type isolates from therapy-naive individuals.
The
key question, however, is whether a patient is likely to respond
to a particular drug. Consequently, the most relevant approach for
interpreting the phenotype results is to define "clinical"
cutoffs by using data from clinical trials or cohort studies to
determine the change in susceptibility that results in a reduction
in virological response to the drug in question. To date, clinical
cutoffs have been defined for relatively few drugs (e.g., abacavir,
tenofovir, and lopinavir-ritonavir).
Discussion
Although
much has been learned regarding mutational interactions and their
effects on drug susceptibility, knowledge in this area is incomplete,
and further studies are essential. Defining clinical cutoffs to
determine viral resistance to individual drugs and drug combinations
is imperative to guide the appropriate interpretation of test results.
Evaluating
susceptibility patterns among nonclade B HIV isolates
should also be a high priority, because these viruses are the most
prevalent around the world. In addition, it will be important to
further define pharmacologic and virological interactions for individual
drugs and combinations and to evaluate how these interactions can
best be exploited to provide drug levels sufficient to inhibit partially
resistant viruses.
Given
the complexities of drug regimens, mutational interactions, and
resistance testing, expert interpretation of both genotypic and
phenotypic test results is highly recommended. Assessment of the
many clinical and biological factors that affect interpretation
of resistance test results (including the patient's previous treatment
history) requires the input of individuals experienced with antiretroviral
therapy and knowledgeable of drug resistance patterns.
These guidelines (Table 1) should help clinicians make appropriate
decisions on how best to incorporate drug resistance testing into
the management of HIV-infected individuals.
Summary
of clinical situations in which resistance testing is recommended
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Clinical
Setting
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Rationale / Comments
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Acute
or recent HIV infection
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Acute
infection1
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Detect
transmission of drug-resistant virus; change therapy to provide
optimal antiretroviral activity and preserve HIV-1  specific CD4+
cell helper responses.
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HIV
infection within previous 12 months (if known)
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Detect
transmission of drug-resistant virus, although this may not
always be possible with current tests.
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Suboptimal
HIV-1 RNA response to therapy
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Failure
to attain HIV-1 RNA level less than the detection limit by
8 12 weeks of
therapy may suggest preexistence of drug resistance.
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Before
initiation of antiretroviral therapy in established HIV infection2
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Patients
infected within previous 2 years and possibly longer
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Detect
prior transmission of drug-resistant HIV, although this may
not always be possible with current tests.
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First
regimen failure
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Document
drug(s) to which resistance has emerged; select a new regimen
of maximally active drugs. Possible poor regimen adherence
and pharmacologic factors responsible for resistance should
be assessed. See "Other" below.
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Multiple
regimen failure
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Guide
the selection of active drugs in the next regimen, excluding
drugs to which response is unlikely. Review of the cumulative
results of prior resistance results may be useful. See "Other"
below.
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Pregnancy,
if the mother has detectable plasma HIV-1 RNA level
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Optimize
the treatment regimen for the mother and prophylaxis for neonate.
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Other
general recommendations
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Plasma
samples to be tested for drug resistance should contain at
least 500 1000 HIV-1 RNA
copies/mL to ensure successful PCR amplification.
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Given
the absence of data from comparative trials, no one resistance
testing method is recommended over another. Phenotypic testing
may be particularly useful in complex cases with multiple
resistance mutations.
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In
patients in whom an antiretroviral regimen is failing (including
suboptimal virologic response as long as HIV RNA level is
greater than 500 1000 copies/mL,
to allow resistance testing), it is preferable that the blood
sample for resistance testing be obtained while the patient
is taking the failing regimen, if possible.
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Measures
of HIV replication capacity are under study but cannot be
generally recommended at this time because of lack of consensus
on how to optimally measure or how this information should
be incorporated into patient management.
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Resistance
testing should be performed by laboratories that have appropriate
operator training, certification, and periodic proficiency
assurance.
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Genotypic
and phenotypic test results should be interpreted by individuals
who are knowledgeable in antiretroviral therapy and drug resistance
patterns.
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Chart
from Hirsch and others. Clinical Infectious Diseases
37(1). July 1, 2003.
1
Therapy should not be delayed
for resistance testing results.
2 Inuntreated, established infection, wild-type
isolates may replace drug-resistant quasi
species over time.
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Source
MS Hirsch
and others. Antiretroviral Drug Resistance
Testing in Adults Infected
with Human Immunodeficiency Virus
Type 1: 2003 Recommendations
of an International AIDS-Society
USA Panel.
Clinical Infectious Diseases 37(1): 113-128. July 1, 2003.
Selected
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