Plasma human immunodeficiency virus 1 (HIV-1) RNA levels, plasma concentrations
of protease and nonnucleoside reverse transcriptase inhibitors, and suggested
minimum target trough concentration (as provided by drug manufacturers), for
each of the 10 patients. Data markers below the black dotted line indicate
undetectable levels of plasma HIV-1 RNA (<50 copies/mL). Patients were
sampled 36 times. For each sample, viral RNA was measured in 2 independent
laboratories. For each time point, the higher value was plotted. A total of
720 viral load measurements were expected (36 time points × 2
independent measurements × 10 patients). Of these, 713 were
collected (99.03%). Of planned assays for plasma drug concentration, 98.33%
were completed. M8 is the measurable active metabolite of nelfinavir. EFV
indicates efavirenz; LPV, lopinavir; NFV, nelfinavir; NVP, nevirapine; RTV,
ritonavir; SQV, saquinavir.
At all points other than those at which the plasma HIV-1 RNA level was
≥50 copies/mL, the viral load was undetectable. Up to 7 independent clones
were obtained at each time point. Note that no new mutations conferring drug
resistance appeared during the blips. All mutations detected during or within
30 days after blips were present at baseline (B) or were seen in plasma samples
taken prior to the blips. Baseline mutations were identified in either plasma
or resting CD4 cell reservoir samples (peripheral blood). The resting cell
reservoir was sampled only at baseline. “Prior ART exposure” refers
to other antiretroviral drugs the patient has taken that are not part of the
current regimen. ABC indicates abacavir; ADF, adefovir; APV, amprenavir; ART,
antiretroviral therapy; AZT, zidovudine; ddC, zalcitabine; ddI, didanosine;
d4T, stavudine; EFV, efavirenz; HAART, highly active antiretroviral therapy;
HIV, human immunodeficiency virus; IDV, indinavir; LPV, lopinavir; NFV, nelfinavir;
NNRTI, nonnucleoside reverse transcriptase inhibitor; NRTI, nucleoside reverse
transcriptase inhibitor; NVP, nevirapine; PI, protease inhibitor; RTV, ritonavir;
SQV, saquinavir; TDF, tenofovir disoproxil fumarate; 3TC, lamivudine; WT,
All reverse transcriptase (RT) sequences from patient 136 clustered
together, away from the reference sequence HXB2 and representative baseline
sequences from other study patients (top). Plasma sequences are coded by visit
number, with groups of 5 consecutive visits represented by a single symbol.
The resting cell reservoir was sampled only at baseline. The RT region could
not be amplified from the plasma of patient 140 (thus, there was no need to
assess cellular reservoir virus for comparison purposes). Genetic distance
from the most recent common ancestor (horizontal scale) is not greater for
blip sequences. The table on the right provides the genotype for each branch
of the tree (which represents all 9 study patients). Amino acid positions
in RT are shown at the top of the table (protease trees are less informative
because the gene is smaller and more conserved [thus, these trees are not
provided herein]; however, the protease trees showed no evidence for evolution
during blips and no new drug resistance mutations). The sequence of the reference
isolate HXB2 is indicated under the amino acid numbers. Positions associated
with resistance to the drugs the patient was taking (zidovudine, lamivudine,
and efavirenz) are shown in color. Representative polymorphisms (amino acid
substitutions not associated with drug resistance that distinguish this patient’s
virus population from other isolates) are also shown. No resistance mutations
were detected in this patient. The L→M and L→V substitutions at
position 210 are not associated with significant resistance to zidovudine.47 There were no missing data for this analysis except
as indicated above. AA indicates amino acid; AZT, zidovudine; EFV, efavirenz;
HIV, human immunodeficiency virus; 3TC, lamivudine.
Reverse transcriptase (RT) sequences were derived from virus from resting
CD4 cells (peripheral blood) and from virus in plasma samples. Plasma sequences
are coded by visit number, with groups of 5 consecutive visits represented
by a single symbol. The resting cell reservoir was sampled only at baseline.
Lines indicate genetic distance from the hub of the network. Distance is not
generally greater for blip sequences than for nonblip sequences. Generation
of network trees is described in the “Methods” section.
Customize your JAMA Network experience by selecting one or more topics from the list below.
Nettles RE, Kieffer TL, Kwon P, et al. Intermittent HIV-1 Viremia (Blips) and Drug Resistance in Patients Receiving HAART. JAMA. 2005;293(7):817–829. doi:10.1001/jama.293.7.817
Context Many patients infected with human immunodeficiency virus type 1 (HIV-1)
and receiving highly active antiretroviral therapy experience intermittent
episodes of detectable viremia (“blips”), which may raise concerns
about drug resistance, lead to costly repeat measurements of viral RNA, and
sometimes trigger alterations in therapy.
Objective To test the hypothesis that blips represent random biological and statistical
variation around mean steady-state HIV-1 RNA levels slightly below 50 copies/mL
rather than biologically significant elevations in viremia.
Design, Setting, and Patients Between June 19, 2003, and February 9, 2004, patients receiving therapy
underwent intensive sampling (every 2-3 days) over 3 to 4 months to define
the frequency, magnitude, and duration of blips and their association with
drug levels and other clinical variables. Blips were defined as HIV-1 RNA
measurements greater than or equal to 50 copies/mL preceded and followed by
measurements less than 50 copies/mL without a change in treatment. To determine
whether blips result from or lead to drug resistance, an ultrasensitive genotyping
assay was used to detect drug resistance mutations before, during, and after
blips. Patients were 10 HIV-1–infected asymptomatic adults recruited
by clinicians and followed up in the Moore Clinic at the Johns Hopkins Hospital.
Patients had suppression of viremia to below 50 copies/mL while receiving
a stable antiretroviral regimen for 6 months or longer.
Main Outcome Measures At each time point, plasma HIV-1 RNA levels were measured in 2 independent
laboratories and drug resistance mutations were analyzed by clonal sequencing.
Results With the intensive sampling, blips were detected in 9 of 10 patients.
Statistical analysis was consistent with random assay variation around a mean
viral load below 50 copies/mL. Blips were not concordant on independent testing
and had a short duration (median, <3 days) and low magnitude (median, 79
copies/mL). Blip frequency was not associated with demographic, clinical,
or treatment variables. Blips did not occur in relation to illness, vaccination,
or directly measured antiretroviral drug concentrations. Blips were marginally
associated (P = .08) with reported episodes
of nonadherence. Most importantly, in approximately 1000 independent clones
sequenced for both protease and reverse transcriptase, no new resistance mutations
were seen before, during, or shortly after blips.
Conclusion Most blips in this population appear to represent random biological
and statistical variation around mean HIV-1 levels below 50 copies/mL rather
than clinically significant elevations in viremia.
Treatment of human immunodeficiency virus type 1 (HIV-1) infection with
highly active antiretroviral therapy (HAART) can suppress viremia to below
the limit of detection of available clinical assays.1-3 The
current goal of antiretroviral therapy is suppression of viremia to below
50 copies/mL of HIV-1 RNA, the limit of detection of the most sensitive available
clinical assay.4,5 Suppression
to this level is necessary to prevent drug resistance, the major cause of
treatment failure.6,7 After achieving
suppression, many patients experience intermittent episodes of detectable
viremia (“blips”).8-16 Blips
may raise concern that resistance is developing and complicate management
by increasing patient anxiety, triggering costly repeat measurements of viral
load, and generating uncertainty regarding whether therapy should be altered.
The nature and significance of blips are unclear. Blips may result from
transiently reduced drug concentrations (due to suboptimal adherence, decreased
bioavailability, or increased clearance). They may also result from heightened
immune activation, as during vaccination or illness.17,18 Work
by Havlir et al8 and subsequent studies by
suggested that isolated blips are not associated with virological failure.
However, blips have been associated with an increased risk of clinical failure,13,19 viral evolution,20 and
slower decay of viral reservoirs.21 Of greatest
concern are reports of the evolution of drug resistance during blips.18,19,22
Dornadula et al23 provided insights into
the nature of blips by documenting continuous release of virions into the
plasma even in patients receiving HAART who had plasma virus levels below
the limit of detection of clinical assays. Using special methods, they found
a mean level of 15 to 20 copies/mL in these patients. Confirmation of ongoing
virus production came from direct cloning and genotyping of this low-level
plasma virus, which was shown to be generally devoid of new resistance mutations.24-26 Whether this low-level
viremia reflects release of virus from stable reservoirs,24-29 continuing
cycles of ongoing replication,21,30,31 or
both is unclear. Regardless of the mechanism, it is clear that HAART suppresses
viremia to a new steady state slightly below the clinical limit of detection.
Given that effective HAART regimens produce steady-state viremia slightly
below 50 copies/mL, we hypothesized that most blips represent random biological
and statistical variation around these steady-state levels rather than biologically
significant elevations in viremia. This hypothesis involves several predictions:
(1) Blip frequency will depend on the steady-state level in a given patient.
(2) The number of blips detected will depend on the number of measurements
made. (3) For steady-state levels at or below 20 copies/mL, paired measurements
on the same sample will rarely be concordantly positive, so that blips will
not be reproducible. (4) Similarly, consecutive measurements will rarely be
both positive, so that the apparent duration of blips will be short. (5) The
magnitude of blips will be low and clustered toward the detection limit since
they represent fluctuation around a mean below this limit. (6) Blips will
not generally correlate with adherence, drug levels, or intercurrent illnesses.
(7) Most importantly, genotypic analysis during and after a blip will generally
show no new resistance mutations.
To determine the clinical significance of blips, we tested these predictions
in a prospective study in which 10 patients with suppression of viremia while
receiving HAART underwent more intensive sampling than has been used in previous
studies. At each time point, plasma virus and antiretroviral drug levels were
determined, and genotypic resistance was analyzed using a method more sensitive
than commercial assays. The goal of the study was to provide new insights
into the nature and clinical significance of blips.
Between June 19, 2003, and February 9, 2004, we studied asymptomatic
HIV-1–infected adults who had achieved suppression of viremia to below
50 copies/mL while receiving a stable HAART regimen for 6 months or longer
and who were willing and able to make regular study visits required for the
study. A total of 13 patients were recruited by Moore Clinic clinicians at
the Johns Hopkins Hospital, where the patients were followed up. Three patients
subsequently decided not to participate, either because of the number of visits
required or frequent blood draws. Data from these 3 patients were not included
in the study. Prior antiretroviral exposure from the time of diagnosis to
study entry was ascertained by chart review and patient interview. Patients
were not excluded for a history of blips. Blips were defined as HIV-1 RNA
measurements greater than or equal to 50 copies/mL preceded by measurements
below 50 copies/mL and followed by a return to below 50 copies/mL without
a change in treatment.8 Volunteers donated
100 mL of blood for genotyping of the virus in the plasma and in the cellular
reservoir in resting CD4 cells. Beginning 1 month thereafter, participants
donated 17 mL of blood 3 times weekly (Monday, Wednesday, and Friday) for
36 total study visits. Due to holidays, most participants required more time
than the minimum 12 weeks to complete the 36 visits, with a mean of 3.3 gaps
in consecutive study visits per patient. However, in all cases the 36 visits
were completed by 127 days (mean, 99.4 days).
The protocol was approved by a Johns Hopkins institutional review board.
If participants expressed interest in the study and provided consent to their
clinician, they were contacted by a study investigator (R.E.N.) who discussed
the study design with the patient. If patients decided to participate, they
were provided with a written combined institutional review board/Health Insurance
Portability and Accountability Act informed consent form approved by the Johns
Hopkins University institutional review board. The features of the study were
then explained to the patient by an investigator (R.E.N.). Written informed
consent was obtained for all aspects of the study involving blood drawing
and analysis of personal health information from the patients or their medical
records. Because the patients are not identified in the study herein, written
informed consent for publication in a medical journal was not specifically
obtained. However, the consent form did indicate that health information obtained
in the course of the study would be used and/or given out as needed after
the study to develop new strategies for fighting HIV infection. These patients
were included in other reports having different research questions.32,33 Race/ethnicity was ascertained by
chart review and reflects the categorization entered by the clinicians caring
for the patients. Three participants were white and 7 were black. Race/ethnicity
was used in the study herein for description of the study cohort and to determine
whether blip frequency was greater in any particular racial/ethnic category.
Viral RNA was quantified using the ultrasensitive Roche Amplicor Monitor
System version 1.5 assay (Roche Molecular Systems Inc, Blanchburg, NJ), which
has a lower limit of quantification of 50 copies/mL. Assays were performed
in 2 independent laboratories: a Clinical Laboratory Improvement Amendments–certified
laboratory that performs this measurement for clinical management of a large
patient population and a research laboratory that has performed this assay
for numerous studies.24,34-37 Recommended
negative, low, and high RNA controls, as well as quantitation standards (Roche
Amplicor Monitor System version 1.5), were included in each assay. There were
no false-positive results on HIV-negative plasma in either laboratory. In
general, study visits for each patient occurred at the same time of day (typically
early morning), thus likely avoiding any effects of diurnal variation. There
is little evidence that diurnal variation has any significant role in viral
load. Diurnal variation in viral load has been evaluated in 2 reports38,39 and was not identified in either
To allow consistent amplification and sequencing of the small number
of viral genomes present in the plasma of patients receiving suppressive HAART
regimens, plasma virus was first pelleted by ultracentrifugation; reverse
transcriptase (RT) and protease genes were then separately analyzed by RT
polymerase chain reaction (PCR), cloning, and sequencing using a previously
described ultrasensitive genotyping method.25,26 Briefly,
blood was collected using an acid-citrate-dextrose anticoagulant, and the
plasma was separated on a Ficoll gradient and filtered or spun to remove any
contaminating cells. Plasma was then ultracentrifuged at 25 200g for 2 hours at 4°C to pellet the virions. The virions
were lysed under denaturing conditions, and the viral RNA was isolated using
a standard commercial silica-gel membrane–binding method (QIAamp Viral
RNA Minikit; Qiagen, Valencia, Calif). The isolated RNA was treated with DNase
I to ensure that amplified HIV-1 sequences were derived from viral RNA and
not from contaminating DNA. A complementary DNA fragment was synthesized from
viral RNA and amplified separately for both the protease and RT segments of
the pol gene using a commercial 1-step reverse transcriptase
PCR (Superscript II RNase H-Reverse Transcriptase with High Fidelity Platinum
Taq DNA Polymerase; Invitrogen Corp, Carlsbad, Calif). The first PCR product
was then diluted 1:4 and used in a nested reaction. The DNA products from
the outer PCR reaction were amplified using 0.5 units of High Fidelity Platinum
Taq DNA polymerase. The DNA from this PCR reaction was then separated on a
2% agarose gel, and the appropriately sized product was purified using the
QIAquick Gel Extraction Kit (Qiagen). Isolated DNA was then cloned using the
Zero Blunt TOPO PCR Cloning Kit (Invitrogen Corp) and sequenced using an ABI
PRISM 3700 DNA analyzer (Applied Biosystems, Foster City, Calif).
Virus persisting in the resting CD4 cell reservoir27,28,40 was
analyzed by limiting dilution PCR as described in detail elsewhere (P.K. and
R.F.S., unpublished data). Briefly, resting CD4 cells were purified from peripheral
blood as described27 and lysed. Based on initial
real-time PCR estimates of HIV-1 DNA levels, cellular DNA was diluted to approximately
0.5 HIV-1 DNA copies per reaction or fewer, which ensures clonal amplification
in at least 75% of the positive reactions. A nested PCR was then performed
using Platinum Pfx Polymerase (Invitrogen Corp). Polymerase chain reaction
products were separated on a 1.5% agarose gel, purified using the QIAquick
Gel Extraction Kit, and directly sequenced.
The independence of clones from the same patient was established as
previously described.26 Phylogenetic analysis
of clones revealed patient-specific clustering. Polymerase chain reaction
errors were cleansed using a novel algorithm to remove mutations seen only
in a single clone from a given patient.26 Phylogenetic
analyses were performed using NimbleTree version 2.6 (available from S.C.R.
at http://sray.med.som.jhmi.edu/) and PAUP* version 4b10.41 Trees were inferred using the neighbor-joining algorithm,42 and support for clustering was assessed using bootstrap
analysis.43 Network trees44 were
generated for the analysis of sequences using SplitsTree Version 4β12.45 The split decomposition method was used with Hamming
distance, and the maximum number of sequences was included while maintaining
goodness of fit at 100, as recommended by Wain-Hobson et al.44 In
the case of patient 136, this required the removal of only 1 plasma sequence,
a sequence from visit 11, which was not a visit in which a blip occurred.
This sequence was only 1 transition mutation away from the hub of the network.
Genetic diversity at each time point (theta) was assessed using a rank-sum
test according to the methods of Rozas et al.46 Sequences
were analyzed for drug resistant mutations using the Los Alamos47 and
At each time point, random drug levels were obtained for the protease
and nonnucleoside RT inhibitors using modified, validated, high-performance
liquid chromatography methods.49,50 For
lopinavir, ritonavir, and saquinavir, the mobile phase was 0.1% trifluoroacetic
acid, acetonitrile, and methanol (53:42:5). Analytes were separated isocratically
followed by a step gradient wash at 30°C using a reverse-phase Beckman
C18 column and detected at 220 nm (lopinavir) and at 239 nm (ritonavir and
saquinavir). The internal standard, A-86093.0, was supplied by Abbott Laboratories
(Abbott Park, Ill). Calibration standards ranged from 100 to 15 000 ng/mL
for lopinavir and ritonavir and from 87 to 13 121 ng/mL for saquinavir.
For nelfinavir, the nelfinavir active metabolite M8, and efavirenz, plasma
proteins were precipitated with acetonitrile and the supernatant was dried.
M8 levels were measured because M8 is the major metabolite of nelfinavir and
has equivalent virological activity. Samples were dissolved in mobile phase,
applied to a C18 reverse-phase column at 30°C, separated isocratically
in 0.1% trifluoroacetic acid (pH 5.0):acetonitrile:methanol (47:48:5), and
detected at 253 nm. Calibration standards ranged from 100 to 20 000 ng/mL.
For nevirapine, plasma samples were applied to a Waters HLB reverse-phase
cartridge, washed with an acid/base series, eluted, dried, and dissolved in
mobile phase (63% 25 mM phosphate buffer [pH 6.0] and 5.2 mM 1-butanesulfonic
acid, 21.5% methanol and 15.5% acetonitrile). Analytes were separated isocratically
followed by a step gradient wash at 30°C using a reverse-phase Supelco
LC-8 column and detected at 280 nm. Calibration standards ranged from 25 to
10 000 ng/mL. For all assays, quality control samples were interspersed
between unknown samples. Mean correlation coefficients for calibration curves
were greater than 0.998 (SD, 0.001). Although diurnal variation in antiretroviral
drug levels has been reported,51 plasma drug
levels should be most greatly affected by the time of last dose, the dosing
interval, differential absorption rates, and individual drug pharmacodynamics.
At each study visit, patients completed a questionnaire recording adherence,
the date and time of the last dose of each antiretroviral drug, recent vaccination,
and physical illness. No participant changed antiretroviral drugs during the
course of the study.
More than 99% of the expected viral load data were successfully collected.
A total of 720 viral load measurements were expected (36 time points × 2
independent measures × 10 patients). Of these, 713 were collected
(99.03%). For 5 of the missing viral load measurements, the other independent
assay at the same time point was successfully completed, and this value was
included in the study. At 1 time point, for patient 113, viral load measurements
were missing from both laboratories because venipuncture could not be performed
at that visit. All viral load calculations were made using 713 measurements
as the denominator. More than 98% (98.33%) of the planned assays for plasma
drug concentration were completed. The time points for which drug concentration
data were missing were excluded from all analyses of the correlation between
drug levels and blips.
Continuous variables were summarized as medians and ranges, and group
comparisons were made using the Wilcoxon rank-sum test. Dichotomous data were
summarized as frequencies and proportions, and groups were compared using
the Fisher exact test. The agreement between laboratories assaying the same
sample was calculated using the κ statistic.
The proportion of predicted RNA measurements greater than or equal to
a specified level (eg, 50 copies/mL) was estimated by the probability of obtaining
measurements above that level. We assumed that the distribution of the RNA
measurements was normal on the log10 scale, and the SD was based
on the coefficient of variation (CV) for 25 copies/mL (90%), the lowest viral
RNA measure for which a CV was reported in assay validation.52 The
CV supplied by the assay package insert52 was
not based on the log values. However, the CV equates to the SD on the natural
log scale and was converted to the log10 scale by dividing by 2.3026,53 resulting in the SD of 0.3909. This SD was slightly
greater than the SD of 0.25 calculated on the log10 scale for 50
copies/mL, which is the lowest level reported in the company’s earlier
version of the assay (Amplicor 1.0). In assessment of predicted blip characteristics
(assuming a constant viral load of 10, 20, or 30 copies/mL, distribution of
viral load measurements as normal on the log10 scale, and independence
of all assays), the same SD was used for all 3 levels. Because of the assumptions
made on the distribution of the viral loads and the reliance on the estimate
of the CV from the package insert, we did not perform formal comparisons of
the distributions of the observed and predicted blip sizes. Drug concentrations
were compared with therapeutic levels and dichotomized to any subtherapeutic
levels vs all therapeutic levels at each time point. These were cross-tabulated
with viral load (detectable vs not detectable) at the same time point. χ2 analysis was used to test for the association of blips with subtherapeutic
Analyses were performed using SAS version 9.0 (SAS Institute Inc, Cary,
NC). All reported P values are 2-sided, and P<.05 was considered significant. A 1-tailed test would
be more conservative when reporting negative results; however, for the analyses
herein, 2-tailed tests were preferred to limit type I error that can occur
when a number of tests are being performed. For the association of drug concentration
and blips, the 2-tailed P value was .22 and would
thus be .11 for a 1-tailed test. The only 2-tailed P value
between .05 and .10, for which the significance would be affected by performing
a 1-tailed test, is for the association of a blip within 7 days after self-reported
nonadherence. For this comparison, the P value of
.08 is reported herein and is considered marginally significant.
To analyze blips, we studied 10 patients receiving HAART who had stable
suppression of viremia to below 50 copies/mL (Table 1). The patients ranged in age from 39 to 59 years. Seven
were men and 3 were women; 7 were black and 3 were white. The study was carried
out between June 19, 2003, and February 9, 2004. Most patients had started
HAART after reaching low CD4 nadirs with high viral RNA levels. Some had received
prior nonsuppressive antiretroviral therapy, but all were eventually started
on a HAART regimen that produced prolonged suppression of viremia to below
50 copies/mL (median, 34 months; range, 11-79 months). With their current
regimens, 4 patients had blips detected during routine clinical care prior
to entry, and there were 6 total blips out of 125 prior viral RNA measurements
(4.8%). These blips were detected a mean of 15.7 months (range, 2-30 months)
before study entry, and in all cases viral loads returned to below 50 copies/mL
without a change in therapy. The median prior blip magnitude was 94 copies/mL
(range, 61-108). In these patients, viral load measurements were generally
performed every 3 months as part of routine clinical care and were not influenced
at all by participation in the study because these viral load measurements
predated study participation.
To capture as many blips as possible, we obtained plasma samples every
2 to 3 days for 3 to 4 months for duplicate HIV-1 RNA measurements in 2 independent
laboratories. The higher value was used because any value above 50 copies/mL
may be considered a blip by clinicians and we wanted to capture as many blips
as possible. All patients completed 36 study visits. Patients were permitted
to take breaks from the study protocol when the General Clinical Research
Center was closed for holidays and when patients requested time for out-of-town
travel. In general, we attempted to gather data in a “3-visit”
or “weekly” clustered fashion to minimize isolated study visits.
For study conclusions, it was considered more important to have a large number
of study visits clustered within a relatively short time vs having strictly
consecutive study visits. The mean and median times to completion of the 36
study visits were 99.4 days and 97.5 days, respectively (range, 88-127 days).
The minimum possible time to complete the study was 82 days. Mean and median
numbers of gaps in consecutive study visits were 3.3 and 3, respectively.
Blips were detected in 9 of 10 patients (Figure 1 and Table 1). Of
713 viral RNA measurements, 26 (3.6%) were above 50 copies/mL. Together these
constituted 18 total blips, with consecutive positive measurements counted
as a single blip. Patients experienced a median of 2 blips (range, 0-5). The
observed proportion of positive assay results was consistent with random variation
around a mean level of 10 to 20 copies/mL (Table
2). Nine blips were detected by one laboratory, 8 by the other laboratory,
and 1 by both. Thus, although there was no difference in the sensitivity of
assays used by the 2 laboratories, concordance was poor (κ=4.4%). This
result is expected if blips result from random variation around a mean substantially
below 50 copies/mL.
Frequent sampling also allowed us to better estimate the true duration
and magnitude of blips. Fifteen of 18 blips represented isolated measurements
above 50 copies/mL, with the subsequent measurement negative. Thus, the typical
blip was brief (median duration, 2.5 days; range, 2-11.5 days). Only 1 patient
(patient 154) experienced blips that persisted for more than 1 consecutive
study visit. Blips were low in magnitude (median, 79 copies/mL; range, 51-201
copies/mL), with a clustering of val ues toward the 50 copies/mL limit and
only 1 value above 200 copies/mL. Brief blips of low magnitude are also consistent
with the random-variation hypothesis.
Blip frequency was not associated with demographic parameters such as
sex, race, and age. There was no association with clinical parameters such
as CD4 cell nadir, CD4 cell count at entry, pretreatment viral load, duration
of infection, duration of virological suppression, and number of prior blips.
Blips were not associated with therapeutic variables such as the number of
drugs in the current regimen (Table 3).
Blips were not observed with intercurrent illnesses (pharyngitis/sinusitis,
cold/upper respiratory tract infection, gout flare, oral herpes outbreak,
or gastrointestinal tract upset), or influenza vaccination (given during the
study to 9 of 10 patients). Blips were marginally (P = .08)
associated with patient-reported nonadherence (Table 4).
To determine whether blips were temporally associated with decreased
drug concentrations, the protease inhibitor and nonnucleoside RT inhibitor
concentrations in plasma were measured at each time point in each patient
(Figure 1). Large intrapatient fluctuations
in drug concentrations were noted in some patients (patients 99, 136, and
148). Importantly, there was no association between low drug concentrations
and blips (P = .22 by χ2 test).
Most blips (78%) occurred when drug levels were above the suggested trough
concentrations (Figure 1).
Although plasma virus levels were below 50 copies/mL at most time points,
the protease and RT regions of plasma viral RNA were successfully amplified
and sequenced before, during, and after blips in 9 of the 10 patients (Figure 2). An average of 4 to 5 clones were obtained
per time point, for a total of 951 independent protease clones (830 in nonblip
samples, 121 in blip samples) and 1079 independent RT clones (916 in nonblip
samples, 163 in blip samples). As is shown in Figure 2, virus detected during blips did not have new drug resistance
mutations. The virus detected during blips was either wild type or had mutations
that were present in the baseline sampling of plasma and the cellular reservoir
or in plasma samples obtained at time points prior to the blip. These results
are compatible with the idea that there may be no accumulation of new drug
resistance mutations associated with blips.
Phylogenetic analysis and genotypic data for a representative patient
(136) are shown in Figure 3. Clones
obtained from the resting CD4 cell reservoir at baseline and from the 36 plasma
samples clustered together away from sequences from other patients. Virus
present during a blip was not phylogenetically distinct from nonblip samples,
indicating a lack of viral evolution during blips. Some blip sequences were
identical to sequences in the cellular reservoir. Phylogenetic analysis using
network trees44 also failed to show increased
divergence of blip sequences (Figure 4).
Analysis of genetic diversity (theta) at each time point did not show increased
diversity during blips. The median theta for all patients was 0.0051 (interquartile
range, 0.002-0.010) for nonblip visits and 0.0061 (interquartile range, 0.003-0.012)
for blip visits (P = .37). Most importantly,
no drug resistance mutations were detected in any of the sequences from this
patient, who had received no prior nonsuppressive therapy before starting
HAART (Figure 2 and Figure 3).
In contrast to patient 136, the remaining 8 patients had received prior
nonsuppressive therapy, and resistance mutations attributable to the nonsuppressive
therapy could be detected (Figure 2).
However, no new drug resistance mutations were seen in the 121 protease sequences
and the 163 RT sequences obtained during blips in this study. All blip sequences
were either wild type or contained mutations that were seen prior to the blip
(Figure 2). Blip samples did not have
a higher proportion of resistant clones. The degree of resistance was not
associated with blip magnitude or frequency. The patient with the blip of
greatest magnitude (patient 136) had only wild-type clones, and the patient
with the most frequent blips (patient 154) had only 1 major protease mutation
(I84V) and no RT mutations that would confer resistance to the current regimen.
The K103N mutation detected during 1 blip was selected by prior therapy with
efavirenz. During the study period, the patient was not receiving any drug
that would select for this mutation.
The genotypic analysis also suggested that blips do not lead to resistance.
New resistance mutations were not found immediately after blips. In 455 independent
protease sequences and 575 independent RT sequences obtained in the 30 days
following a blip, no new resistance mutations were detected. In 1 patient
(patient 99), the protease mutation M46I appeared 8 weeks after a blip and
then disappeared. Given the patient’s history of poor adherence and
prior exposure to multiple protease inhibitors, this is likely to be an archival
mutation not detected in baseline sampling. Taken together, these results
refute the notion that resistance arises during or immediately after blips.
Given that in adherent patients HAART decreases viremia to a new steady-state
level slightly below 50 copies/mL (eg, 15-20 copies/mL),23 we
hypothesized that normal biological and statistical variation would result
in occasional values above 50 copies/mL without a clinically significant elevation
in plasma HIV-1 RNA levels. Our analysis of the frequency, magnitude, reproducibility,
duration, clinical associations, and genotypic consequences of blips are all
consistent with this hypothesis.
With respect to frequency, blips were detected in a greater percentage
of the patients than in previous studies,8-13 probably
because of the intensive sampling used here. In previous studies, blips were
detected in 11% to 46% of patients.8-11,13 Since
the sampling interval we used (every 2-3 days) is on the same time scale as
the decay rate of virus-producing cells (t1/2, approximately 1
day),54 it is unlikely that significant elevations
in viremia were missed. Based on the statistical arguments presented above,
the number of blips detected is likely to be directly related to the frequency
of sampling. However, the fraction of positive viral RNA measurements will
be related to the patient’s steady-state level of viremia regardless
of sampling frequency. Blips occurred with a frequency (3.6% of measurements)
that was similar to that observed prior to entry (4.8%) and that was consistent
with random variation around a steady-state viral RNA level of 10 to 20 copies/mL
(Table 2). Of course, this steady-state
level will vary among patients, accounting for the variation in blip frequency
observed herein (0 blips in patient 140 and 5 blips in patient 154) and elsewhere.14,55
The intensive sampling used herein allowed a more precise definition
of blip duration. Most of the blips consisted of a single measurement preceded
and followed by measurements below 50 copies/mL. The short duration of most
blips documented herein is in contradistinction to longer estimates made with
mathematical models that infer the shape of blips from clinical data with
sparse sampling.14 The magnitude of observed
blips was low (median, 79 copies/mL), with clustering of values close to the
detection limit. This is consistent with the tail of a normal log10 distribution
centered around 20 copies/mL. Blip magnitude correlated poorly between laboratories.
The poor reproducibility of blips below 200 copies/mL has been noted previously.56 At a true viral RNA level of 20 copies/mL, any pair
of duplicate or consecutive measurements would rarely be concordantly positive
(probability = 2.2% [derived from data in Table 2]), consistent with the poor reproducibility (κ = 4.4%)
and short duration (median, 2.5 days) observed herein.
There was no association between blips and demographic, treatment, or
HIV-associated clinical factors. Furthermore, blips were unrelated to intercurrent
illnesses, vaccination, or decreases in antiretroviral drug concentrations.
Blips were marginally associated with self-reported nonadherence (P = .08). Again, these findings are consistent with the hypothesis
presented above. Recent work by Miller et al57 also
found no link between blips and nonadherence. Extensive analysis of drug concentrations
over time revealed wide intrapatient variation but no correlation between
drug concentrations and blips, raising concerns about the usefulness of therapeutic
drug monitoring in the management of patients experiencing blips.
Despite previous reports that blips represent resistant virus,18,19,22 our analysis of a
total of 951 and 1079 independent clones for the protease and RT regions,
respectively, failed to identify any new genotypic resistance before, during,
or immediately after blips. One potential explanation for the discrepancy
is that the extensive sampling used here allowed a more precise definition
of preexisting resistance so that the appearance of new mutations could be
more accurately assessed.
These findings provide an explanation for the work of Havlir et al8 and others9-11 demonstrating
that blips do not predict virological failure. We suggest that isolated low-level
positive viral RNA measurements may not be cause for clinical concern. Of
course, consistently detectable viremia can be associated with resistance,6,58,59 and further studies
will be needed to define when detectable viremia should trigger a change in
therapy. Given a steady-state level of 20 copies/mL, 96.4% of blips due to
random variation will fall below 200 copies/mL. Therefore, blips with a magnitude
of greater than 200 copies/mL or blips that are detected in at least 2 independent
or consecutive measurements may be more of a cause for concern.
In conclusion, among patients with suppression of viremia to below 50
copies/mL, most blips appear to represent normal biological and statistical
variation around mean levels that are below 50 copies/mL rather than clinically
significant elevations in the level of viral replication. These conclusions
are based on an intensive study of a small group of patients and may not be
representative of all patients. Thepatients studied had started therapy with
low CD4 cell counts and high viral load levels, and it will be important to
confirm these results in patients who start therapy earlier in the course
Corresponding Author: Robert F. Siliciano,
MD, PhD, Department of Medicine, Johns Hopkins University School of Medicine,
879 Broadway Research Bldg, 733 N Broadway, Baltimore, MD 21205 (email@example.com).
Author Contributions: Dr Siliciano had full
access to all of the data in the study and takes responsibility for the integrity
of the data and the accuracy of the data analyses.
Study concept and design: Nettles, Kieffer,
Quinn, Flexner, Carson, Ray, Siliciano.
Acquisition of data: Nettles, Kieffer, Kwon,
Monie, Han, Parsons, Cofrancesco, Quinn, Jackson, Flexner, Persaud, Siliciano.
Analysis and interpretation of data: Nettles,
Kieffer, Parsons, Gallant, Quinn, Jackson, Flexner, Carson, Ray, Persaud,
Drafting of the manuscript: Nettles, Kwon,
Parsons, Flexner, Carson, Ray, Siliciano.
Critical revision of the manuscript for important
intellectual content: Kieffer, Monie, Han, Cofrancesco, Gallant, Quinn,
Jackson, Flexner, Carson, Ray, Persaud, Siliciano.
Statistical analysis: Nettles, Quinn, Carson,
Obtained funding: Nettles, Carson, Siliciano.
Administrative, technical, or material support:
Kwon, Monie, Han, Parsons, Cofrancesco, Jackson, Flexner, Ray.
Study supervision: Kieffer, Flexner, Persaud,
Drs Nettles and Kieffer contributed equally to this article.
Financial Disclosures: Dr Nettles received
honoraria from Abbott. Dr Cofrancesco received a research grant from Agouron
Consultancies to study body composition in patients with HIV infection and
private research grants or funding from the Doris Duke Charitable Foundation;
was a consultant/advisor to Abbott, Gilead Sciences, GlaxoSmithKline, Ortho
Biotech, and Pfizer; received lecture sponsorship and honoraria for CME from
Agouron, Bristol-Myers Squibb, Gilead, GlaxoSmithKline, and Ortho Biotech;
received HIV viral load assays for study in Thailand from Roche; and received
research funding from the AACTG, CDC, and NIH. Dr Gallant received grant/research
support or honoraria from or was a consultant to Abbott Laboratories, Boehringer-Ingelheim,
Bristol-Myers Squibb, Gilead Sciences, GlaxoSmithKline, Roche Pharmaceuticals,
Tanox, Tibotec-Virco, Vertex, and ViroLogic. Dr Quinn is a government employee.
Dr Jackson received honoraria for lectures partially sponsored by Boehringer-Ingelheim
and Roche Diagnostics and received reagents and sponsored research funding
from Roche Molecular Systems for new assay evaluations. Dr Flexner was a consultant
to Merck and received research grants or honoraria from Abbott, Agouron/Pfizer,
Bristol-Myers Squibb, Gilead Sciences, GlaxoSmithKline, and Merck. Dr Carson
received government grant support including General Clinical Research Center
(NCRR), New Approaches to Brain Tumor Therapy (NCI), Atherosclerosis Risk
in Communities (NHLBI), and Study of Women with Congenital Adrenal Hyperplasia
(NIH). Dr Ray received honoraria for CME programs from Agouron Pharmaceuticals,
Bristol-Myers Squibb, GlaxoSmithKline, and Roche Laboratories. Dr Persaud
received research grants or funding from the Doris Duke Charitable Foundation
and the Elizabeth Glaser Pediatric AIDS Foundation, and grants or research
funding from NIH/NIAID-RO1. Dr Siliciano was a consultant for Schering-Plough
on an unrelated project and received research reagents from Merck for an unrelated
Funding/Support: Clinical studies were carried
out through the Johns Hopkins University School of Medicine General Clinical
Research Center, which was supported by NIH grant M01-RR00052 from the National
Center for Research Resources. Dr Nettles was supported by NIAID grants F32
AI056696 and K08 AI060367 and by a grant from Bristol-Myers Squibb. The experimental
work was supported by NIH grants AI43222 and AI51178 and a grant from the
Doris Duke Charitable Foundation and the Howard Hughes Medical Institute.
Role of the Sponsors: The funding agencies
had no role in any aspect of the design, execution, or publication of this
Previous Presentation: Preliminary data representing
some of the work described herein were presented as an abstract (651) at the
11th Conference on Retroviruses and Opportunistic Infections; February 8-11,
2004; San Francisco, Calif; and as an abstract (H1134) at the 44th Interscience
Conference on Antimicrobial Agents and Chemotherapy; October 30-November 2,
2004; Washington, DC.
Acknowledgment: We acknowledge James Johnson
for assistance with drug concentration measurements.
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