A randomized comparison of second-line lopinavir/ritonavir
monotherapy vs. tenofovir/lamivudine/lopinavir/ritonavir in
patients failing NNRTI-regimens: the HIV STAR study
Torsak Bunupuradah, Ploenchan Chetchotisakd, Jintanat Ananworanich, Warangkana Munsakul, Supunnee Jirajariyavej, Pacharee Kantipong, Wisit Prasithsirikul, Somnuek Sungkanuparph, Chureeratana Bowonwatanuwong,Virat Klinbuayaem, Stephen J. Kerr, Jiratchaya Sophonphan, Sorakij Bhakeecheep, Bernard Hirschel, Kiat Ruxrungtham, the HIV STAR Study Group Antiviral Therapy 2012, 17:10.3851/IMP2222 Submission date 19th April 2012 Acceptance date 26th April 2012 Publication date 2nd July 2012 For information about publishing your article in Antiviral Therapy go to http://www.intmedpress.com/index.cfm?pid=12
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Publication: Antiviral Therapy; Type: Original article
DOI: 10.3851/IMP2222
A randomized comparison of second-line lopinavir/ritonavir monotherapy vs. tenofovir/lamivudine/lopinavir/ritonavir in patients failing NNRTI-regimens: the HIV STAR study Authors
Torsak Bunupuradah1*, Ploenchan Chetchotisakd2*, Jintanat Ananworanich1,3,4, Warangkana Munsakul5, Supunnee Jirajariyavej6, Pacharee Kantipong7, Wisit Prasithsirikul8, Somnuek Sungkanuparph9, Chureeratana Bowonwatanuwong10,Virat Klinbuayaem11, Stephen J. Kerr1,12, Jiratchaya Sophonphan1, Sorakij Bhakeecheep13, Bernard Hirschel14**, Kiat Ruxrungtham1,4** the HIV STAR Study Group
Affiliations
1 HIV-NAT, the Thai Red Cross AIDS Research Centre, Bangkok, Thailand
2 KhonKaen University, KhonKaen, Thailand
3 SEARCH, the Thai Red Cross AIDS Research Centre, Bangkok, Thailand
4 Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
5 Faculty of Medicine, Vajira Hospital, University of Bangkok Metropolitan Administration, Thailand
Running head: LPV/r monotherapy or with TDF/3TC in NNRTI-based failure
Keywords: second-line antiretroviral therapy, lopinavir/ritonavir monotherapy, Thailand, HIV STAR study
Supported by: the Thai National Health Security Office; the Swiss cohort study; and the National Research Council of Thailand
Role of the funding source: The Thai National Health Security Office, the Swiss cohort study, and the National Research Council of Thailand funded the study. The sponsors and investigators contributed to study concept and design, interpretation of data, preparation and review of the manuscript, and final approval of the
Publication: Antiviral Therapy; Type: Original article
DOI: 10.3851/IMP2222
paper for publication. KR and TB had full access to the data and took responsibility for the integrity of the data and the accuracy of the data analyses.
Word count abstract 265, text 3,861 words, 3 tables, 3 figures, 38 references
The study results were presented in part as a late breaker poster presentation (poster number 584) at the18th
Conference on Retroviruses and Opportunistic Infections 2011, February 28 to March 2, 2011, Boston, USA.
Financial disclosure and Conflict of interest
PC has received speaker honorarium or educational grant from Abbott, Bristol-Myers Squibb, Janssen-Cilag, GlaxoSmithKline, MSD, IDS and Roche. JA has received speakers’ fees or honorarium from Roche, Gilead, ViiV, and Abbott. SS has received speakers’ fees or honorarium from Gilead, Pfizer, Tibotec and Abbott. DAC has received research funding or speaker honoraria from Abbott, Gilead, ViiV Healthcare, Janssen-Cilag, Bristol-Myers Squibb and Merck Sharp & Dohme.BH has received travel grants, and speaker fees from Janssen, Gilead, and MSD. KR has received speaker honoraria or educational grant support from Abbott, Gilead, Bristol-Myers Squibb, Merck, Roche, Jensen-Cilag, GlaxoSmithKline, Tibotec, and The Governmental pharmaceutical organization. KR has also received a Professional Researcher Strengthening Grant from the National Science and Technology Development Agency, BIOTEC, Ministry of Science and Technology; and The National Research University Project of CHE and the Ratchadaphiseksomphot Endowment Fund (HR1161A), and Thai Research fund (TRF) Senior Research Scholar. Others declare no conflict of interest and that member of their immediate families do not have a financial interest in or arrangement with any commercial organization that may have a direct interest in the subject matter of this article.
Abstract
Background
Data informing the use of boosted-protease inhibitor monotherapy as second-line treatment are limited. There are also no randomized trials addressing treatment options after failing first-line non-nucleoside reverse transcriptase inhibitor (NNRTI)-regimens.
Methods
HIV-infected subjects 18years, with HIV-RNA1,000copies/mL while using NNRTI+2NRTIs, and naïve to PI were randomized to LPV/r 400/100 mg twice daily (mono-LPV/r) or tenofovir once daily +lamivudine twice daily +LPV/r 400/100 mg twice daily (TDF/3TC/LPV/r) at 9 sites in Thailand. The primary outcome was time-weighted area under curve (TWAUC) change in HIV-RNA over 48 weeks. A priori hypothesis was that the LPV monotherapy arm would be considered non-inferior if
the upper 95% confidence limit in TWAUC mean difference was 0.5log10copies/mL.
Results
The intention-to-treat population comprised 195 patients (mono-LPV/r n =98 and TDF/3TC/LPV/r n =97); male 58%, baseline mean (SD) age of 38(7) years, CD4 count of 204(135) cells/mm3, and HIV-RNA of 4.1(0.6)log10copies/mL. The majority had HIV-1 recombinant CRF01_AE infection, and thymidine analog mutation (TAM)-2 mutations were 3 times more common than TAM-1.
At 48 weeks, the difference in TWAUC HIV-RNA between arms was 0.15 (95% CI -0.04 to 0.33) log10copies/mL, consistent with our definition of non-inferiority. However, the proportion with HIV-RNA<50copies/mL was significantly lower in the mono-LPV/r
arm: 61% vs. 83% (ITT, p<0.01). Baseline HIV-RNA5log10copies/mL (p<0.001) and mono-LPV/r use (p=0.003) were predictors of virologic failure. Baseline genotypic
sensitivity scores 2 and TAM-2 were associated with better virologic control in subjects treated with the TDF-containing regimen.
Publication: Antiviral Therapy; Type: Original article
DOI: 10.3851/IMP2222
Conclusion
In PI-naïve patients failing NNRTI-based first-line HAART, mono-LPV/r had a significantly lower proportion of patients with HIV-RNA<50 copies/mL compared to the TDF/3TC/LPV/r treatment. Thus, mono-LPV/r should not be recommended as a second-line option.
Accepted 26 April 2012, published online 2 July 2012
Background
Non-nucleoside reverse transcriptase inhibitor (NNRTI)-based highly active antiretroviral therapy (HAART) is
recommended as first-line therapy [1,2]. The rate of virologic failure of NNRTI-based HAART ranges from 38-
44% [3]. In patients with treatment failure, ritonavir-boosted protease inhibitor (bPI) in combination with 2
nucleoside reverse transcriptase inhibitors (NRTIs) selected on the basis of a drug resistance test is
recommended as second-line therapy [1,2]. However, HIV-RNA testing is not routinely accessible in resource
limited settings, and by the time clinical or immunological failure is identified, patients generally have
extensive NNRTI and NRTI mutations [4,5]. In these settings, it is unknown whether using NRTIs plus a bPI is
beneficial, compared to treating with bPI alone. Moreover, the long term mitochondrial and organ-specific
toxicities of NRTIs, and increased costs of combination therapy, are a concern [6].
Mono bPI therapy has been studied in treatment naïve or adults who are virologically well suppressed
[7–9]. Lopinavir/ritonavir monotherapy (mono-LPV/r) has been the most investigated bPI because of its co-
formulation with ritonavir, and its high genetic barrier to resistance [10]. Six randomized controlled trials of
mono-LPV/r versus LPV/r-based HAART, including 5 conducted in virologically suppressed patients where
mono-LPV/r was used as maintenance therapy and one that was conducted in antiretroviral therapy naïve
patients with HIV-RNA<100,000 copies/ml. These studies showed that the risk of virologic failure was greater
with mono-LPV/r compared to LPV/r-based HAART; 33.2% vs. 22.9% [pooled odds ratio 1.48 (95%
confidence interval 1.02–2.13, P =0.037] [10]. Episodes of low level HIV viremia defined as HIV-RNA 50-500
copies/mL were more common in patients receiving mono-LPV/r compared to those on LPV/r-based HAART,
but low level viremia could be controlled after intensification with 2NRTIs [7,10,11].
There are limited data describing mono-PI as a second-line therapy in HIV-infected adults failing first-
line NNRTI-based HAART. If mono-LPV/r can be used as second-line therapy, it could reduce pill burden,
NRTI side effects, drug interactions, medication cost, and the need for genotyping, while preserving future
treatment options. Bartlett et al. reported a single-arm, pilot study of mono-LPV/r following virologic failure of
first-line NNRTI-based regimens (ACTG5230) which showed promising preliminary activity of second-line
mono-LPV/r with CD4 rise and HIV-RNA <400 copies/ml at week 24 in 87% of the 122 enrolled subjects [12].
However, ACTG5230 was an uncontrolled study with a short-term follow up period, and the success rate at a
lower cut-off of 50 copies/ml has not been reported. Here, we report an open-labeled randomized multicenter
non-inferiority study of mono-LPV/r versus tenofovir/lamivudine/LPV/r (TDF/3TC/LPV/r) as second-line
therapy in HIV-infected adults failing NNRTI-based HAART.
Methods
Publication: Antiviral Therapy; Type: Original article
DOI: 10.3851/IMP2222
Participants and Randomization
From May 2008 to November 2009, Thai adults failing first-line NNRTI-based regimens from 9 hospitals were
enrolled in an open-labeled multicentre randomized trial, the HIV STAR study (The HIV Second-line Therapy
Anti-Retroviral study in patients who failed NNRTI-based regimens, clinical trial.gov identification number
NCT00627055). Subjects were eligible if they were HIV-infected adults aged 18years, who had been treated
with NNRTI-based HAART for at least 6 months, had HIV-RNA 1,000copies/mL, and had never used PIs.
Exclusion criteria were active opportunistic infection at screening, pregnancy, positive hepatitis B antigen
(HBsAg), alanine aminotransferase (ALT) 200U/L, and creatinine clearance <60 c.c./min by the Cockroft-
Gault equation. Study subjects were also not allowed to take oral medication that interferes with the
pharmacokinetics of LPV/r, including rifampicin, rifabutin, phenobarbital, phenytoin, carbamazepine,
dexamethasone, ketoconazole, and clarithromycin.
At enrolment, subjects were randomized to mono-LPV/r vs. TDF/3TC/LPV/r. The randomizations were
managed centrally by an independent biostatistician using a minimization scheme with a programme written in
SAS Version 9.1 (SAS Corporation, Cary, NC), and were stratified by site, baseline HIV-RNA < or
5log10copies/mL and baseline CD4 <or 100 cells/mm3. The dosages were LPV/r 400mg/100mg orally every
12 hours, TDF 300 mg orally every 24 hours and 3TC 150 mg orally every 12 hours or 3TC 300mg orally
every 24 hours. The formulations of LPV/r were soft gel capsules LPV/r (Kaletra®, 133/33mg) and/or LPV/r
tablet (Matrix®, 200/50 mg).
Clinical assessment
The weight (kg), height (cm), CD4%, CD4 cells count, HIV-RNA, and ALT were assessed at week 0 then
every 12 weeks until 48 weeks. HIV-RNA was performed centrally at the HIV-NAT laboratory in Bangkok,
Thailand by the CobasAmpliprep/TaqMan HIV-l Viral load assay (Roche Molecular Systems, Inc., Branchburg,
NJ, 08876 USA). Genotypic resistance tests using an in-house method validated for HIV clade A/E were
performed centrally at the Vaccine and Cellular Immunology laboratory, Faculty of Medicine, Chulalongkorn
University in Bangkok [13] which has participated in the TAQAS (TreatAsia Quality Assurance Scheme) since
2006 [14]. Resistance testing was performed in subjects with HIV-RNA>1000copies/mL. Mutations were
defined according to the Stanford Interpretation system (http://.hivdb.stanford.edu). Multi-NRTI mutations were
defined per IAS-USA list of mutations as having4thymidine analog mutations (TAMs) or Q151M complex or
69insertion [15]. The thymidine analog mutations (TAMs) were M41L, D67N, K70R, L210W, T215F/Y, and
K219E/Q. Two exclusive pathways of TAMs have been well described: TAM-1 profile which includes M41L,
L210W, and T215F/Y, and TAM-2 including D67N, K70R, and K219E/Q. The patterns of TAMs and its impact
on viralogical control when TDF was included in the regimen were analyzed [16]. The genotypic sensitivity
score (GSS) is based on the Stanford resistance algorithm analytical results (http://.hivdb.stanford.edu). For
TDF, potential low level resistance and low level resistance were considered as susceptible to TDF, whereas
other levels were considered as resistant. Clinical and laboratory adverse events were graded by the Division
of AIDS grading table December 2004 [17]. Adherence was evaluated at every visit by self-reported visual
analogue scale [18].
Publication: Antiviral Therapy; Type: Original article
DOI: 10.3851/IMP2222
Every 24 weeks, fasting lipids and glucose, and creatinine were performed. Estimated creatinine
clearance was calculated by the Cockroft-Gault equation [19]. An independent Data Safety and Monitoring
Board (DSMB) reviewed the overall quality of the trial and data from two interim analyses. The first analysis
occurred when 60 participants had reached week 24. Stopping criteria were based on virologic failure,
resistance and safety data. The DSMB recommended a second interim analysis to occur when 100 subjects
(50 in each arm) had reached week 24. At both reviews, the DSMB recommended continuing the study. The
protocol was approved by the Thai Ministry of Public Health and local ethics committees. All subjects gave
informed consent.
Primary endpoint, definitions and patient management
The primary endpoint was time-weighted area under the curve (TWAUC) mean change of log HIV-RNA from
baseline to week 48 by treatment arm. The secondary endpoints were proportion with undetectable HIV-RNA
at levels<50, and <400 copies/mL, at weeks 24 and 48. At 24 weeks, if the HIV-RNA was 400copies/mL,
the patients returned within 4 weeks to receive adherence counseling and a repeat HIV-RNA. At this visit, the
patients in the mono-LPV/r arm had TDF/3TC added while waiting for the result of repeated HIV-RNA. If the
repeated HIV-RNA was <50copies/mL, patients stopped TDF/3TC and continued mono-LPV/r. If the repeated
HIV-RNA was 50copies/mL, the mono-LPV/r patients were instructed to continue TDF/3TC/LPV/r. The failing
patients in the TDF/3TC/LPV/r arm had treatment modifications based on standard of care. Resistance assay
was performed for samples with HIV-RNA 1,000copies/mL.
Statistical procedures
Sample size calculations were based on the TWAUC mean change in log10HIV-RNA [20]. A priori we defined
non-inferiority as the upper 95% confidence limit in TWAUC mean difference 0.5 log10 copies/mL. Assuming
the between patient variability corresponded to a standard deviation of 1.0 log10, and no difference between
treatment arms, a sample size of 85 patients per arm would give a 90% chance that the 2-sided 95%
confidence interval had an upper limit below 0.5 log10. Fifteen additional patients per arm were recruited to
compensate for losses to follow-up. The TWAUC mean change from baseline HIV-RNA to week 48 was
calculated for each patient as the area under curve change from baseline to each follow-up HIV-RNA
measure, averaged over the patient’s total duration of follow-up. Comparison of time-weighted change
between treatment arms was made by calculating difference between means, the corresponding 95%
confidence interval (95%CI), and t test–derived P values. The intention-to-treat (ITT) population was defined
as randomly assigned participants who received at least 1 study medication dose and attended at least one
follow-up visit. There was no extrapolation of data for the primary end point. For continuous safety endpoints
in ITT analysis, a last observation carried forward approach was adopted. In ITT analyses comparing the
proportion of patients with undetectable HIV-RNA, those with missing data, and those who had changes to
their randomised regimen because of virologic failure were imputed as failures. Per protocol (PP) analyses
were conducted for primary and secondary endpoints, and in these analyses participants were censored when
the randomised therapy was ceased. Absolute differences in proportions were assessed using 95%CI, and
chi-square-derived P values. Predictors of virologic failure were assessed with logistic regression. A stepwise
backwards approach was used to develop a multivariate model, starting with covariates with p<0.2 in
Publication: Antiviral Therapy; Type: Original article
DOI: 10.3851/IMP2222
univariate models and retaining those with p<0.05 in the final model. All analyses were undertaken using
STATA 11 (StataCorp, College Station, Texas, USA).
Results
Two hundred HIV-infected adults were randomized, 100 to each of the two arms. Five were excluded from the
ITT analysis because they did not return at week 0 (Figure 1). The demographic characteristics were similar
between arms as shown in Table 1, but the mono-LPV/r showed a higher proportion of males. At screening,
180 (92%) used 3TC, 123 (63%) used stavudine, 45 (23%) used zidovudine, and 9 (5%) used TDF.
Nevirapine and efavirenz were used in 167 (86%) and 28 (14%), respectively.
Primary outcome
For 195 patients in the ITT population, the mean (SD) reductions in TWAUC were 1.74 (0.64)logs for the
mono-LPV/r arm and 1.89 (0.65) logs for the TDF/3TC/LPV/r arm, an absolute difference of 0.15 (95% CI -
0.04 to 0.33) logs. Thus the mean difference in TWAUC in HIV-RNA between the arms was consistent with
our definition of non-inferiority in both the ITT and PP populations (Table 2). Because of gender imbalance in
the treatment arms and a sight imbalance in the proportion of patients with baseline multidrug resistance, we
conducted further adjusted analyses which did not change the interpretation of the primary endpoint (Table 2).
Secondary outcomes
The proportion of patients with HIV-RNA<400 copies/mL in the mono-LPV/r arm was 74.5% vs. 85.6% in the
TDF/3TC/LPV/r arm (absolute difference -11.1%, 95%CI -22.2 to 0, p=0.053). However, significantly lower
proportions of patients in the mono-LPV/r arm compared to the TDF/3TC/LPV/r arm had HIV-RNA<200
(69.4% vs. 85.6%, absolute difference -16.2%, 95% CI -27.7 to -4.7, p=0.01) and <50 copies/mL(61.2% vs.
82.5%, absolute difference -22.2%, 95% CI -33.5 to -9.0, p<0.01). The proportion of patients in different HIV-
RNA strata over 48 weeks is presented in Figure 2.
Analyses by pre-specified subgroups
Randomization was stratified by baseline CD4 at a cutpoint of 100 cells/mm3, and by baseline HIV-RNA at a
cutpoint of 5 log copies/mL. The proportion with HIV-RNA <50 copies/mL in the LPV/r arm vs. the
TDF/3TC/LPV/r arm in the 5 log strata were 1/9 (11%) and 6/10 (60%) respectively [OR 12.0 (95%CI 1.1 –
136.8], and in the < 5log strata were 63/89 (71%) and 74/87 (85%) respectively [OR 2.3 (95%CI 1.1 –4.9)].
The proportion of patients with HIV-RNA <50 copies/mL in the mono-LPV/r arm vs. the TDF/3TC/LPV/r arm in
the CD4<100 cells/mm3 strata were 11/20 (55%) and 16/24 (67%) respectively [OR 1.64 (95%CI 0.5 – 5.6)]
and in the CD4 100 cells/mm3 strata were 53/78 (68%) and 64/73 (88%) respectively [OR 3.4 (95%CI 1.4 –
7.8). All were based on ITT analysis.
Analyses by patterns of baseline resistance: TAM-1, TAM-2 and Genotypic sensitivity score (GSS)
Based on the pol sequences, the majority (96%) of patients had recombinant CRF01_AE infection and 4%
were CRF01_B. Almost all had 3TC-resistance-associated mutations (M184V/I), and approximately one-third
Publication: Antiviral Therapy; Type: Original article
DOI: 10.3851/IMP2222
had multi-NRTI resistance (Table 1). None had a 69 insertion. Forty-five (23%) had TDF-resistance (including
patients with K65R, any TAM-1 and/or 3 TAM-1).
Baseline NRTI-associated mutations, baseline GSS and the proportion with HIV-RNA<50 copies/ml at
week 48 are shown in Figures 3A and 3B. Approximately half (51%) of the patients were found carrying any
TAMs mutation, but TAM-2 profiles were more common than TAM-1 (47.7% vs 16.4%; 3:1 ratio). Similarly, a
higher proportion of patients (approximately 3-fold) carried all 3 mutations of TAM-2 compared with 3 TAM-1
mutations (16.9% vs. 5.1%, respectively).
As shown in Figure 3B, in the TDF/3TC/LPV/r-treated group, patients with baseline GSS of at least 2
had a higher percentage of undetectable HIV-RNA (<50 copies/ml) than those with GSS =1 (83.3% vs 79%,
respectively). This within arm difference was not statistically different, but it was significant when compared to
the mono-LPV/r arm (an undetectable rate of 65.3%, p <0.05). TAM-2 (either any mutation, or with all 3
mutants) were associated with better virologic control in subjects treated with the TDF-containing regimen
(Figure 3A).
Predictors of virologic failure
By multivariate logistic regression analysis, HIV-RNA 5log10copies/mL at time of NNRTI-based HAART
failure (OR 7.87, 95% CI 2.73-22.68, p<0.001) and mono-LPV/r treatment (OR3.09, 95% CI 1.46-6.55,
p=0.003) were independently associated with virologic failure. Gender, age, CDC clinical classification,
duration of NNRTI-based HAART before enrolment, and baseline hemoglobin, CD4 count and adherence
during the study evaluated by visual analog scale had no significant association with virologic failure.
None of the patients in the TDF/3TC/LPV/r-arm had changed their HAART during the study period.
Seventeen in the mono-LPV/r arm with protocol-defined virologic failure had TDF/3TC added. Nine (53%), 4
(23.5%), and 4 (23.5%) of these patients had HIV-RNA< 50, 50-1,000, and 1,000copies/mL after 24 weeks
of adding TDF/3TC. These patients continued TDF/3TC/LPV/r until their last visit in this study. Resistance
tests were performed in 17 patients failing mono-LPV/r, and major PI mutations (M46I/L, I50V, and V82A)
were detected in 3 patients. The last HIV-RNA results of these 3 patients after adding TDF/3TC were 40, 405,
and 166,355 copies/mL. No major PI mutation was found in 3 patients in the TDF/3TC/LPV/r arm who had
virologic failure.
Clinical, immunologic and metabolic treatment outcomes
One death was reported in each arm. A woman in the mono-LPV/r arm died at home from an unknown cause
at week 24; her last CD4 count was 105 cells/mm3 and HIV-RNA was <50copies/mL. A man in the
TDF/3TC/LPV/r arm died from lymphoma at week 36; his last CD4 count was 28 cells/mm3 and HIV-RNA was
<50copies/mL. No other patients experienced CDC category C events. The treatment outcomes at week 48
are shown in Table 3. There were no differences except for subjects in mono-LPV/r arm having significantly
higher body weight, total cholesterol, triglycerides, and creatinine clearance than those in TDF/3TC/LPV/r
arm. Both arms had a median adherence of 100% over the duration of the study. CD4 counts increased
significantly from baseline in both arms.
Publication: Antiviral Therapy; Type: Original article
DOI: 10.3851/IMP2222
There were 18 grade 3-4 adverse events in 10 patients that were at least possibly related to the study
drugs (7 events in 7 patients in the mono-LPV/r-arm and 11 events in 3 patients in TDF/3TC/LPV/r-arm). They
occurred at a median follow-up time of 23 (IQR 6-47) weeks. Serious adverse events were reported in 2
patients in the mono-LPV/r arm (elevated triglycerides) and 7 patients in TDF/3TC/LPV/r- arm (elevated
Among patients who had failed 2NRTIs+NNRTI but were PI naïve, by our pre-determined primary endpoint
and criteria, the mono-LPV/r arm was non-inferior to the TDF/3TC/LPV/r arm. However, mono-LPV/r was
significantly poorer than the TDF/3TC/LPV/r arm by the secondary virologic endpoint. Patients in the mono-
LPV/r arm were more likely to have HIV viremia between 50-200 copies/mL than when LPV/r was combined
with 2 NRTIs. This observation is similar to results from previous mono-LPV/r studies [10]. When 2NRTIs
were added to mono-LPV/r in failing patients, a difference in proportions of patients achieving HIV-RNA <50
copies/mL between the two arms remained. It is interesting that in the TDF/3TC/LPV/r arm, of which almost all
patients had 3TC-resistance, one-third had multi-NRTI resistance and one-fifth had TDF-resistance (including
patients with K65R, any TAM1 and/or 3 TAM1), over 80% achieved virologic suppression <50copies/mL, and
this was significantly higher than that in the mono-LPV/r arm (61 vs. 83%, respectively; p<0.01). Our finding
supports the use of TDF/3TC/LPV/r in patients who failed first-line NNRTI-based HAART and did not have
significant TDF resistance.
Mono-LPV/r regimen may have some benefits. The improvement of CD4 and HIV-RNA after switching
to second-line mono-LPV/r had been reported from ACTG5230 [12]. However, the ACTG study reported a
short follow-up period of 24 weeks and the HIV-RNA cutoff was 400 copies/ml. Our study did not demonstrate
a difference between arms using this HIV-RNA cutoff threshold, but did show inferior virologic suppression
with the ultrasensitive assay (50 copies/ml threshold). In our study, improvement of CD4 count and the CDC
progression during 48 weeks was comparable between arms. Moreover, our study found a small but
statistically significant elevation in calculated creatinine clearance in patients treated with TDF. In some
guidelines, mono-LPV/r is an option for patients who cannot tolerate NRTIs or who need treatment
simplification [21,22]. However, this is not consistent among guidelines [23,24]. Our study demonstrates that
mono-LPV/r as a second-line option should be used with caution, particularly in settings where close HIV-RNA
monitoring is not available. Around half of our patients who failed the mono-LPV/r regimen, suppressed their
HIV viremia after TDF/3TC was added, similar to results from previous HAART- naïve studies [10]. This is
likely due to the low proportion of our patients with TDF resistance. Of those who failed, 3/17 patients in the
mono-LPV/r arm and none in the LPV/r-HAART arm developed major PI mutations.
Boosted PI can cause long term metabolic side effects. Dyslipidaemia was common in both arms, but
significant increases in triglycerides and total cholesterol were noted in patients in the mono-LPV/r arm
compared to those in the LPV/r-HAART arm. It is possible that that persistent HIV-RNA viremia in the mono-
LPV/r arm contributed to ongoing inflammation resulting in increased lipid levels [25] or TDF may interact with
bPI regimens to influence lipid levels [26]. In addition, TDF had been reported to decrease lipids levels in
healthy volunteers [27]. Long term metabolic effects in this population should be monitored.
Publication: Antiviral Therapy; Type: Original article
DOI: 10.3851/IMP2222
The predictors of mono-LPV/r failure had been reported by other groups. In trials using mono-LPV/r
as the maintenance therapy, lower baseline hemoglobin [28], CD4 count [29] and adherence [28,29] were
predictors of mono-LPV/r failure. However, these predictors could not be compared directly to our study
because of the different scenario of maintenance therapy in those studies vs. salvage therapy in ours. Our
study showed that higher baseline HIV-RNA and mono-LPV/r treatment predicted virologic failure. NNRTI
have a long terminal half life and the enzymatic induction persists for a few weeks after cessation. Therefore,
possible low levels of LPV/r within the first few weeks after switching from NNRTIs could occur from the drug
interactions between LPV/r and NNRTI, a factor possibly contributing to treatment failure especially in the
mono-LPV/r group. Patients in both arms had high adherence rates, evaluated by visual analog scale. This
finding supports published data showing equal or superior adherence and outcome in patients from resource-
limited settings compared to those from richer settings [30].
Our study found that TDF/3TC/LPV/r was superior to mono-LPV/r in patients who failed d4T or
AZT/3TC/NNRTI even though almost all subjects had 3TC resistance (M184V/I), and one-third had multi-drug
resistance NRTI mutations. Possible explanations are that TDF was active in suppressing HIV in most of the
patients, the M184V mutation reduced the replicating capacity of HIV [31], and mono-LPV/r had insufficient
potency in suppressing viremia in patients with high HIV-RNA. Baseline GSS analyses (Figure 3B)
demonstrated that at least 2 active ARTs in the second-line regimen provided the better efficacy for virologic
control. Regarding TAMs, 2 pathways including TAM-1 (mutations 41L, 210W and 215Y) and TAM-2 (67N,
70R and 219E/Q) have been confirmed by a number of studies [16,32,33]. In HIV-1 subtype B, both
zidovudine (AZT) and stavudine (d4T) were associated with TAM-1 more commonly than the TAM-2 pathway
[33,34]. However, non-B subtypes may show differences in this regard. A report from Thailand where HIV-1
subtype CRF01_AE is the most predominant subtype (like most South-East Asian Countries) has found TAM-
2 but not TAM-1 to be more common in patients, the majority of whom had failed d4T-containing NNRTI-
based regimens [35]. More importantly, in regard to its susceptibility to TDF, TAM-1 (T215Y and L210W in
particular) but not TAM-2 shows more cross resistance to TDF [36]. In this study of which the majority of
patients were infected with HIV-1 recombinant CRF01_AE and treated with d4T, TAM-2 (either any or all 3)
was approximately 3 times more common than TAM-1 profile. Thus, patients carrying TAM-2 responded
significantly better to TDF-containing second-line ART compared to those carrying TAM-1. This may not be
applicable to other settings where subtype B predominate. Therefore resistance testing should be performed
at the time of treatment failure whenever possible, and if not, the active nucleosides might be prematurely
discarded.
In term of ethical considerations in conducting this study, we initiated this study because published
data showing extensive NRTI resistance in Thais failing first line NRTI/NNRTI regimens casted doubt on the
usefulness of available NRTIs in the next regimen [4,5,37]. In addition, the infrastructure for routine
genotyping to guide NRTI selection for second-line regimens was not in place in the Thai public health
system. This study reflects the reality in many resource-limited settings and tested the efficacy of LPV/r with or
without 2NRTI, devoid of genotyping for NRTI selection. Our study illustrating TDF/3TC/LPV/r to be effective
in most patients failing first-line regimen supports the scaling up of such second-line regimens in settings
without genotyping. More importantly, this study was monitored closely by a data safety monitoring board to
ensure patients' safety and protection.
Publication: Antiviral Therapy; Type: Original article
DOI: 10.3851/IMP2222
Our study had some limitations. First, due to feasibility constraints our study was designed using a
primary end point of TWAUC, not the more stringent design of ITT-TLOVR algorithm at week 48 with a
predefined noninferiority margin (delta) of 12%. Second, the high virologic suppression rate we report in
patients treated with TDF/3TC/LPV/r may not be applicable to those with a much more extensive duration of
NNRTI-based failure. Third, this study is based on a population predominantly infected HIV-1 recombinant
CRF01_AE, which was found to preferentially use TAM-2 not TAM1 as its thymidine-analog resistance
pathway, thus the results might not be directly applicable to subtype B settings. The strength of this study is
that it is a randomized trial of mono-LPV/r as a second-line treatment in patients failing NRTI/NNRTI first-line.
Another second-line mono-LPV/r from Africa is ongoing [38].
In conclusion, LPV/r monotherapy should not be recommended as a second-line regimen, and if
used, should be used with caution, particularly in settings where close HIV-RNA monitoring is not available.
This study supports the efficacy of second-line TDF/3TC/LPV/r-based regimen particularly in patients whom
their viruses remained sensitive to TDF. In settings where more new classes are accessible, the second-line
antiretroviral option is to switch to a 3 fully active antiretroviral combination guided by a genotypic HIV
resistance test.
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Funding: The Thai National Health Security Office, the Swiss cohort study, and the National Research Council of Thailand
Acknowledgements
HIV STAR (The HIV Second-line Therapy AntiRetroviral study in patients who failed NNRTI-based regimens; clinical trial.gov number NCT00627055) was supported by grants from the Thai National Health Security Office (NHSO), Swiss cohort study, and the National Research Council of Thailand (NRCT). The antiretrovirals and laboratory monitoring were provided by NHSO. We are grateful to the patients for their participation in this study. We thank the Program for HIV Prevention and Treatment (PHPT) laboratory for facilitating laboratory testing and sample shipment of study sites in the North of Thailand. We thank the HIV STAR Data Safety Monitoring board (DSMB) and the HIV STAR study team for their dedication to this study.
HIV STAR Data Safety Monitoring board (DSMB)
Daniel R. Kuritzkes, M.D; Section of Retroviral Therapeutics, Brigham and Women’s Hospital and Division of
AIDS, Harvard Medical School, Boston, MA, USA
Chaiwat Ungsedhapand, M.D; Clinical Research Manager/Medical Monitor, Family Health
International, Asia Pacific Regional Office, Bangkok, Thailand
Pradapmook, Sirikul Chanmano, Kanlaya Charoentonpuban, Stephen Kerr, Jiratchaya Wongsabut
Consultants
Publication: Antiviral Therapy; Type: Original article
DOI: 10.3851/IMP2222
David A Cooper; Kirby Institute for Infection and Immunity in Society, University of New South Wales, Sydney,
Australia
Praphan Phanuphak; HIV-NAT, the Thai Red Cross AIDS Research Centre, Bangkok
List of tables and figures
Table 1. Baseline characteristics Table 2. Mean difference in TWAUC between treatment arms Table 3. Changes in parameters over 48 weeks
Figure 1. Patient disposition diagram
Note: PI: protease inhibitor, SAE: serious adverse event, ITT: intention to treat analysis, PP: per protocol analysis, mono-LPV/r: lopinavir/ritonavir monotherapy, TDF/3TC/LPV/r; tenefovir plus lamivudine plus lopinavir/ritonavir
Figure 2. Percentage of patients in each HIV-RNA stratum by study week
Figure 3: Baseline nucleoside-analog resistance-associated mutations (3A) and baseline genotyoic sensitivity score (GSS, fig. 3B) and its impact on the virologic control ourcomes at week 48
Table 1. Baseline characteristics Mono-LPV/r-arm TDF/3TC/LPV/r-arm Total N = 98 N =97 N =195 Age (years) 36.8 (6.8) 38.2 (6.9) 37.5 (6.9) n(%) male 66(67%) 47(48%) 113(58%) Weight (kg) 59.2(10.6) 57.7(10.4) 58.3 (10.7) Height (cm) 164.1 (7.90) 161.6 (7.7) 162.8 (7.9) % CDC clinical classification A:B:C 25:20:55% 22:24:54% 23:22:55% % nevirapine:efavirenz 88:12 % 84:16 % 86:14 % Duration of NNRTI-based HAART before enrollment (years) 1.8(1.1-4.0) 2.3(1.2-4.0) 2.2(1.2-4.0) Baseline CD4 count (cells/mm3) 194(123) 211(134) 203.5 (134.7) n(%) of patients with baseline CD4 count <100 cells/mm3 20(20.4%) 24(24.7%) 44(22.6%) Baseline HIV-RNA (log10 copies/mL) 4.1(0.6) 4.1(0.6) 4.1 (0.6) n(%) patients with baseline HIV-RNA ≥5log10 copies/mL 9(9.2%) 10(10.3%) 19(9.7%) n(%) of patients with M184V/I 82(83.7%) 78(80.4%) 160(82.1%) n(%) K65R 6(6.1%) 7(7.2%) 13(6.7%) n(%) ≥ 3 TAMs 31(31.6%) 25(25.8%) 56(28.7%) n(%) multi NRTI resistance 13(13.3%) 21(21.6%) 34(17.5%) Note: data are presented as mean (SD), median (IQR) or n(%) CDC; Centre for Disease Control and Prevention, TAMs; thymidine analog mutations, NNRTI; non nucleoside reverse transcriptase inhibitor, NRTI; nucleoside reverse transcriptase inhibitor, HAART; highly active antiretroviral therapy Multi-NRTI mutations were defined as having thymidine analog mutations (TAMs) ≥ 4 or Q151M complex. No 69insertion complex was found in this study.
Table 2. Mean difference in TWAUC between treatment arms.
TWAUC: time-weighted area under curve (TWAUC) change in HIV-RNA over 48 weeks ITT: intention-to-treat, PP: per protocol Multi-NRTI mutations were defined as having thymidine analog mutations (TAMs) ≥ 4 or Q151M complex. No 69insertion complex was found in this study.
Population Unadjusted Adjusted for gender Adjusted for gender and baseline
multi NRTI resistance
ITT 0.15 (-0.04 to 0.33); P=0.12
0.15 (-0.04 to 0.34); P=0.13
0.16 (-0.03 to 0.35); P=0.09
PP 0.14(-0.05 to 0.32); P=0.15
0.13(-0.06 to 0.32); P=0.17
0.15(-0.04 to 0.34); P=0.12
Table 3. Changes of parameters over 48 weeks Week 0 Change from Week 0 to week 48 Mean difference in
week 48 change scores between arms (95%CI)
P Mono-LPV/r TDF/3TC/LPV/r Mono-LPV/r TDF/3TC/LPV/r
Body weight, kg 59.2(10.6) 57.7(10.4) 1.8(4.3) -0.5(5.0) 2.3(0.9 to 3.6) <0.01 CD4 count, cells/mm3 194(123) 211(134) 137(110) 114(117) 23(-9.4 to 56.9) 0.16 ALT, IU/L 44.5(27.8) 37.1(21.9) -10.2(39.76) -11.3(21.91) 1.1(-8.4 to 10.5) 0.83 Creatinine, mg/dL 0.92(0.19) 0.88(0.18) 0.01(0.14) 0.05(0.19) -0.04 (-0.09 to 0.01) 0.12 CrCl by CG (mL/min) 93(22) 88(23) 1.2(15.9) -4.5(16.8) 5.7 (0.9 to 10.5) 0.02 Total cholesterol, mg/dl
The data are presented asmean (SD) ALT: alanine transferase, CrCl by CG: creatinine clearance calculated by Cockroft-Gault equation, HDL: high density lipoprotei
