Abstract
Background
Dual therapy (DT) with boosted protease inhibitors (bPIs) plus lamivudine has been shown to be superior to bPI monotherapy in virologically suppressed patients despite previous selection of the lamivudine resistance M184V mutation. We compared the virological efficacy of lamivudine-based DT in patients with and without a history of M184V detection.
Methods
We retrospectively analyzed patients with HIV-RNA ≤50 copies/mL switching to DT with at least 1 previous resistance genotype in the ARCA database. Time to virological failure (VF; HIV-RNA ≥200 copies/mL or 2 consecutive HIV-RNA >50 copies/mL) and to treatment discontinuation (TD) was analyzed by survival analysis.
Results
Four hundred thirty-six patients switching to lamivudine plus bPIs (70%) or integrase inhibitors (30%) were included. Patients with M184V (n = 87) were older, had lower nadir CD4+ cell count, longer duration of antiretroviral therapy and of virologic suppression, and higher rate of hepatitis C virus infection compared with patients without M184V. The 3-year probability of remaining free from VF was 91.9% (95% confidence interval [CI], 86.6–97.2) without M184V and 87.8% (95% CI, 78.4–97.2) with M184V (P = .323). The time to TD did not differ between groups. Multivariate analysis adjusting for baseline variables differing between groups also did not detect M184V as being associated with VF or TD; however, the 3-year probability of remaining free of viral blips (isolated HIV-RNA 51–199 copies/mL) was 79.8% (95% CI, 67.8%–91.8%) with M184V vs 90.1% (95% CI, 84.0%–96.2%) without M184V (P = .016).
Conclusions
Previous selection of M184V did not increase the risk of VF or TD with lamivudine-based DT but was associated with a higher probability of viral blips.
Keywords: dual therapy, integrase inhibitors, lamivudine, M184V, NRTI mutations
Combination antiretroviral therapy (ART) has radically changed the clinical course of HIV disease, reducing AIDS-related morbidity and mortality [1]. The disease has become chronic and requires life-long treatment, raising issues of treatment tolerability, toxicity, and adherence. Thus, several strategies of ART regimen simplification have been considered. Dual therapies (DTs) have been explored in a significant number of randomized clinical trials and are increasingly being used as maintenance therapy, particularly in some European countries. Lamivudine is the companion drug for many of the dual regimens investigated so far [2–7]. A meta-analysis of randomized trials showed a noninferior risk of virological failure with lamivudine plus boosted protease inhibitor (bPI) as compared with continuation of the 3-drug regimen [8]. Interestingly, the ANRS12286/MOBIDIP trial showed the superiority of DT with lamivudine plus bPI as compared with bPI monotherapy in a population of patients virologically suppressed on a second-line regimen of 2NRTI plus bPI, carrying the M184V mutation in many cases [9].
The M184V mutation is associated with high-level in vitro resistance to lamivudine but also with reduced viral replication capacity [10]. Previous selection of M184V may impact clinical decisions to implement lamivudine-containing DT, yet a direct comparison of efficacy in patients harboring or not harboring the M184V mutation has not been performed. This study aimed at comparing the virological efficacy of lamivudine-based maintenance DT in clinical practice patients with suppressed viral load, with (M184V+) or without (M184V-) a history of M184V detection.
METHODS
Patients Selection Criteria and Virological Characteristics
This is a retrospective observational study performed using the Antiviral Response Cohort Analysis (ARCA) database, which contains data on HIV resistance and antiretroviral therapy from >40 000 patients in Italy [11]. The study was performed in accordance with the ethical standards of the 1964 Declaration of Helsinki and later amendments. All patients signed an informed consent for use of their clinical and laboratory data in aggregated and anonymous form. Access to the database and data analyses were regulated by local institutional ethics committees and by Italian and European privacy legislation. The ARCA database was queried to retrieve the data of HIV-1-infected patients with (i) age ≥18 years, (ii) HIV-RNA ≤50 copies/mL on any ART regimen, (iii) subsequently switching to DT (lamivudine plus bPI or plus integrase inhibitor [INI]) for any reason, (iv) with at least 1 previous genotype, (v) with at least 1 virological and clinical follow-up after switching to DT. The occurrence of M184V was assessed using historical genotypic resistance tests (hGRTs); that is, any detection of this mutation in any previous resistance test was scored as positive. In a sensitivity analysis, only the most recent resistance genotype before baseline was considered. Patients treated with bPI monotherapy were selected with the same inclusion criteria (i–ii and iv–v) and were used as an additional control group.
A genotypic sensitivity score (GSS) was derived for each drug accompanying lamivudine (for the DT group) or for each monotherapy, based on the hGRT according to the AntiRetroScan 2.0 genotypic interpretation system, as detailed elsewhere [12]. Briefly, a GSS of 0 was assigned if the system interpreted “no activity,” 0.25 if “minimal activity,” 0.50 if “partial activity,” 0.75 if “good activity,” and 1 if “complete activity” [11]. For INI therapies without INI sequences available before BL, GSS was assigned as 1.
End Points and Statistical Analysis
The primary objective of the study was to compare time to virological failure and time to treatment discontinuation between the M184V- and M184V+ groups. Secondary objectives were to compare time to virological blips between the 2 groups and time to virological failure between the DT group (overall and with M184V+) and the bPI monotherapy group. Virological failure was defined as HIV-RNA >50 copies/mL in 2 consecutive determinations or ≥200 copies/mL in a single determination. Treatment discontinuation was defined as discontinuation of current DT for any reason or loss to follow-up. Viral blips were defined as a single HIV-RNA between 51 and 199 copies/mL preceded and followed by ≤50 copies/mL measurements.
Differences between groups were investigated by the Student t test and chi-square analysis. Standard survival analyses with Kaplan-Meier curves were used to analyze time to virological failure, time to treatment discontinuation, and time to viral blip. Patients were followed from baseline (ie, start of DT) to the study outcomes, last available follow-up, or February 28, 2017, whichever occurred first. For the time to viral blip analysis, patients with virological failure were excluded. Predictors were investigated by univariate Cox regression; variables showing a significant association at univariate analysis and those variables for which the 2 groups differed at baseline were evaluated in multivariable models. P values of less than .05 were considered significant.
We performed sensitivity analyses considering M184V only in the last available genotypic resistance tests and a different definition of virological failure (HIV-RNA >50 copies/mL in 2 consecutive determinations or a single determination ≥1000 copies/mL) and of virological blips (single HIV-RNA between 51 and 999 copies/mL not confirmed at the subsequent determination).
All analyses were executed using the SPSS v.22.0 software package.
RESULTS
Patients
A total of 436 patients starting lamivudine-based DT were selected, of which 349 (80%) did not have the M184V mutation and 87 (20%) did have the M184V mutation, according to the hGRT (patients’ baseline characteristics in Table 1). DTs started at baseline were lamivudine plus bPI (70%; lopinavir/r [10%], atazanavir/r [24%], darunavir/r [36%]) and lamivudine plus INI (30%; dolutegravir [29%], raltegravir [1%]).
Table 1.
Baseline Characteristics of Patients Starting Lamivudine-Based Dual Therapies According to M184V Detection in the Historical Genotypic Resistance Test
| M184V- (n = 349) | M184V+ (n = 87) | P | |
|---|---|---|---|
| Age, ya | 46 (39–53) | 52 (48–57) | <.001 |
| Male sex | 257 (72) | 53 (61) | .019 |
| Caucasians | 308 (88) | 84 (97) | .077 |
| Risk factor | |||
| Sexual | 225 (64) | 56 (64) | .001 |
| IDU | 40 (11) | 21 (24) | |
| Other/unknown | 84 (24) | 10 (11) | |
| HCV infection | 62 (18) | 24 (28) | <.001 |
| HBsAg+ | 12 (3) | 2 (2) | .001 |
| Previous AIDS events | 40 (12) | 16 (18) | .084 |
| HIV-RNA at zenith, cp/mLa | 104 750 (35 807–329 250) | 107 910 (27 000–252 900) | .416 |
| Years from HIV diagnosisa | 7.8 (3.8–13.7) | 19.2 (16.1–23.0) | <.001 |
| Years from first ART initiationa | 5.6 (2.8–10.0) | 16.6 (12.8–18.9) | <.001 |
| Duration of viral suppression, ya | 3.8 (2.2–6.4) | 6.6 (3.7–8.9) | <.001 |
| Lines of ARTa | 4 (3–6) | 8 (7–13) | <.001 |
| Nadir CD4+, cells/µLa | 224 (81–313) | 147 (57–199) | <.001 |
| Current CD4+, cells/µLa | 620 (453–780) | 632 (409–922) | .131 |
| Type of DT | |||
| Lamivudine + bPI | 242 (69) | 64 (74) | .441 |
| Lamivudine + bDRV | 122 (35) | 33 (38) | |
| Lamivudine + bLPV | 34 (10) | 11 (13) | |
| Lamivudine + bATV | 86 (24) | 20 (23) | |
| Lamivudine + INI | 107 (31) | 23 (26) | |
| Lamivudine + DTG | 105 (30) | 21 (24) | |
| Lamivudine + RAL | 2 (1) | 2 (2) | |
| Pre-BL ART | |||
| 2NRTI + PI | 176 (50) | 44 (51) | .081 |
| 2NRTI + INI | 26 (7) | 7 (8) | |
| 2NRTI + NNRTI | 45 (13) | 3 (3) | |
| DT | 79 (23) | 23 (26) | |
| Other | 23 (7) | 10 (12) | |
| Calendar yeara | 2014 (2013–2015) | 2014 (2012–2015) | .121 |
| GSS of the 2nd drugb | 0.99 (0.07) | 0.91 (0.20) | <.001 |
| Major PI resistance mutationsc | 13 (4) | 30 (34) | <.001 |
Abbreviation: ART, antiretroviral therapy; ATV, atazanavir; BL, baseline; bPI, boosted protease inhibitors; DRV, darunavir; DT, dual therapy; lamivudine, lamivudine; DTG, dolutegravir; GSS, genotypic sensitivity score; IDU, injective drug users; INI, integrase inhibitor; HBsAg, hepatitis B surface antigen; HCV, hepatitis C virus; LPV, lopinavir; NNRTI, non-nucleoside reverse-transcriptase inhibitors; NRTI, nucleoside reverse-transcriptase inhibitors; RAL, raltegravir.
Values are expressed as n (%) except for amedian (IQR) and bmean (SD). Significant P values (<.05) are in bold.
cAt least 1 major PI resistance mutation at the hystorical genotype according to Stanford hivdb [22].
Virological Failure and its Predictors
Main Results
In the DT group, during 693 person-years of follow-up (PYFU; median follow-up, 1.3 years; interquartile range [IQR], 0.7–2.5), 24 virological failures were detected: 7 during 139 PYFU in M184V+ patients (incidence, 5.1; 95% confidence interval [CI], 2.2%–9.9% per 100 PYFU) and 17 during 554 PYFU in M184V- patients (incidence, 3.1; 95% CI, 1.8%–4.8% per 100 PYFU). Virological failures were 4 on lamivudine plus atazanavir/r and 3 on lamivudine plus darunavir/r in the M184V+ group, 7 on lamivudine plus atazanavir/r, 5 on lamivudine plus darunavir/r, 3 on lamivudine plus lopinavir/r, and 2 on lamivudine plus dolutegravir in the M184V- group. GRT after virological failure was available only for 8 patients, all in lamivudine +bPI (Supplementary Table 1).
The estimated probability of remaining free from virological failure was comparable in the 2 groups: at 1 year 95.1% (95% CI, 89.6–100.6) in M184V+ and 96.2% (95% CI, 93.9–98.6) in M184V- patients; at 3 years 87.8% (95% CI, 78.4–97.2) in M184V+ and 91.9% (95% CI, 86.6–97.2) in M184V- patients (P = .323) (Figure 1A).
Figure 1.
a: Estimated probability of being free from virological failure (VF) with dual therapy (M184V groups based on the hGRT). b: Estimated probability of being free from virological failure (VF) in the overall population of dual therapy and in patients with shorter time of viral suppression (M184V groups based on the hGRT). c: Estimated probability of being free from treatment discontinuation (TD) with dual therapy (M184V groups based on the hGRT). d: Estimated probability of being free from virological blips (VB) with dual therapy (M184V groups based on the hGRT).
Subanalyses
In a sensitivity analysis, where only a subset of 85 patients were classified in the M184V+ group based on the last available genotypic resistance test, almost identical virological outcomes were observed (Supplementary Figure 1A).
At a further sensitivity analysis using the more stringent definition of virological failure, as defined in the “Methods” and according to the hGRT, the probabilities of remaining free from virological failure in M184V+ and M184V- were similar (Supplementary Figure 1B).
To minimize the difference in duration of viral suppression before baseline between the groups, an analysis selecting patients with viral suppression of equal to or less than 6.6 years (the median duration of viral suppression in the M184V+ group) was performed (n = 308: 265 in the M184V- group and 43 in the M184V+ group). In this subset, the 1- and 3-year probabilities of remaining free from virological failure were, respectively, 94.4% (95% CI, 87.0–101.8) and 82.9% (95% CI, 67.2–98.6) in the M184V+ group and 97.3% (95% CI, 95.1–99.5) and 92.5% (95% CI, 86.8–98.2) in the M184V- group (P = .080). In an additional analysis selecting patients with equal to or less than 3 years of viral suppression, the respective 1- and 3-year probabilities of remaining free from virological failure were 100.0% and 67.7% in the M184V+ group and 97.3% an 96.2% in the M184V- group (P = .002) (Figure 1B). A sensitivity analysis considering only patients with more than 1 year of viral suppression showed similar results. No differences in virological failure were detected when DT with lamivudine + bPI was compared with lamivudine + INI (Supplementary Figure 1C).
When compared with the bPI monotherapy group (patients’ baseline characteristics are in Supplementary Table 2), DT performed better; the 3-year estimated probabilities of remaining free from virological failure were 74.7% (95% CI, 65.9–92.3) with monotherapy and 91.1 % (95% CI, 86.4–95.8) with DT (P < .001). Even DT with previous detection of M184V performed better than bPI monotherapy: 87.8% (95% CI, 78.4–97.2) vs 74.7% (95% CI, 65.9–92.3), but without a statistically significant difference (P = .099). At Cox regression analysis, adjusting for hepatitis C virus (HCV) serostatus, duration of viral suppression, M184V status, and GSS of the regimen, being on a DT regimen (adjusted hazard ratio [aHR], 0.33; 95% CI, 0.14–0.81; P = .015) was independently associated with a lower risk of virological failure, whereas HBsAg positivity predicted a higher risk of virological failure (aHR, 2.96; 96% CI, 1.17–7.45; P = .022).
In the DT group, at univariate analysis, being HBsAg-positive, a longer history of ART, a higher HIV-RNA at zenith, and a lower GSS of the accompanying drug (bPI or INI) resulted in an association with greater risk of virological failure (Table 2). In a multivariate model adjusting for virological factors (duration of viral suppression, HIV-RNA at zenith, M184V, GSS of the accompanying drug), only higher HIV-RNA at zenith and lower GSS of the accompanying drug, but not M184V, were independently associated with virological failure, whereas another model including HBsAg status, time of viral suppression, age, sex, HIV-RNA at zenith, M184V, and GSS of the accompanying drug showed an independent association between HBsAg positivity and virological failure and confirmed that lower GSS is probably linked to virological failure (Table 2). A sensitivity analysis excluding patients previously exposed to INI without INI sequences available before baseline (n = 398) showed similar results (not shown).
Table 2.
Predictors of Virological Failure With Lamivudine-Based Dual Therapies
| Univariate Analysis | Multivariable Analysis 1 | Multivariable Analysis 2 | ||||
|---|---|---|---|---|---|---|
| Variables | HR (95% CI) | P Value | aHR (95% CI) | P Value | aHR (95% CI) | P Value |
| M184V in hGRT | 1.56 (0.64–3.76) | .327 | 1.23 (0.46–3.31) | .684 | 1.11 (0.38–3.23) | .847 |
| Type of DT (PI vs INI) | 0.42 (0.10–1.85) | .251 | ||||
| Age (+10 y) | 1.17 (0.83–1.65) | .381 | 1.11 (0.73–1.69) | .625 | ||
| Gender (male vs female) | 0.66 (0.29–1.50) | .320 | 0.61 (0.25–1.51) | .284 | ||
| Ethnicity (Caucasian vs other) | 0.60 (0.14–2.54) | .483 | ||||
| Risk factor (ref. sexual) | ||||||
| IDU | 2.40 (0.85–6.75) | .098 | ||||
| Other/unknown | 1.51 (0.57–4.02) | .411 | ||||
| HCV infection (ref. absent) | ||||||
| Present | 1.85 (0.78–4.37) | .163 | ||||
| Unknown | 0.16 (0.02–1.19) | .073 | ||||
| HBsAg (ref. negative) | ||||||
| Positive | 8.85 (2.25–31.5) | .001 | 12.53 (2.15–72.96) | .005 | ||
| Unknown | 0.50 (0.15–1.71) | .269 | 1.67 (0.46–5.96) | .437 | ||
| Previous AIDS-defining events | 1.34 (0.46–3.93) | .594 | ||||
| Time from first ART initiation (+1 y) | 1.07 (1.01–1.13) | .032 | ||||
| Duration of virological suppression before baseline (+1 y) | 0.97 (0.86–1.16) | .965 | 0.95 (0.81–1.1) | .949 | 0.92 (0.79–1.08) | .306 |
| Baseline CD4+ counts (+100 cells/µL) | 0.99 (0.86–1.14) | .922 | ||||
| Nadir CD4+ counts (+100 cells/µL) | 0.86 (0.64–1.16) | .319 | ||||
| Zenith HIV-RNA (+1 log10 copies/mL) | 1.91 (1.06–3.42) | .030 | 1.91 (1.05–3.49) | .035 | 1.61 (0.89–2.91) | .116 |
| GSS of the 2nd drug (+0.5) | 0.36 (0.16–0.84) | .018 | 0.41 (0.16–1.03) | .058 | 0.41 (0.15–1.19) | .082 |
Abbreviations: aHR, adjusted hazard ratio; ART, combined antiretroviral therapy; DT, dual therapy; GSS, genotypic sensitivity score; HBsAg, hepatitis B surface antigen; HCV, hepatitis C virus; hGRT, historical genotype resistance test; HR, hazard ratio; IDU, injective drug users; INI, integrase inhibitor, PI, protease inhibitors. Significant P values (<.05) are in bold.
Treatment Discontinuation and its Predictors
During an overall 724 PYFU, 36 treatment discontinuations occurred in the M184V+ group during 153 PYFU, and 131 in the M184V- group during 571 PYFU (incidence, 23.5 and 22.9 per 100 PYFU, respectively; P = .332). Causes of treatment discontinuation were toxicity (55 in the M184V- group and 10 in the M184V+ group), virological failure (5 and 3, respectively), further simplification (23 and 6), and other (48 and 17). The estimated probabilities of remaining free from treatment discontinuation were also similar in the 2 groups: at 1 year 84.9% (95% CI, 80.8–89.0) in the M184V- and 83.3% (95% CI, 74.4–91.7) in the M814V+ group; at 3 years 44.6% (95% CI, 37.2–53.0) in the M184V- group and 48.8% (95% CI, 32.9–64.7) in the M184V+ group (P = .847) (Figure 1C). At a sensitivity analysis considering the last available genotypic resistance test, similar results were obtained (not shown). The only predictor of treatment discontinuation at univariate analysis was HBsAg positivity (HR, 2.42; 95% CI, 1.06–5.54; P = .037), which was confirmed in a multivariate model (aHR, 2.28; 95% CI, 0.99–5.27; P = .053) adjusting for duration of viral suppression, age, sex, and M184V status.
Viral Blips and Their Predictors
Main Analysis
Viral blips occurred in 10 of 80 (13%) M184V+ patients during 112 PYFU and 18 of 332 (5%) M184V- patients during 502 PYFU. The estimated probabilities of remaining free of viral blips were lower in patients with previous detection of M184V: at 1 year 85.9% (95% CI, 76.7–95.1) vs 96.4% (95% CI, 94.2–98.6) and at 3 years 79.8% (95% CI, 67.8–91.8) vs 90.1% (95% CI, 84.0–96.2) in the M184V- group (P = .016) (Figure 1D).
Subanalyses
At the sensitivity analysis considering the last available genotypic resistance test for M184V status classification, similar results were obtained (Supplementary Figure 1D).
In the subset of patients with viral suppression of ≤6.6 years, the difference in the 3-year probability of remaining free of blips was even larger (M184V+ group: 69.4%; 95% CI, 50.6–88.2; M184V- group: 91.1%; 95% CI, 84.8–97.4; P < .001).
At a further sensitivity analysis using a broader definition of viral blip (51–999 cp/mL; see the “Methods”), these occurred in 20 of 335 (6%) M184V- and 13 of 83 (16%) M184V+ patients (based on the hGRT classification). The 3-year estimated probabilities of remaining free from viral blips were similar to the ones in the main analysis (Supplementary Figure 1E).
At multivariable Cox regression analysis, HCV infection and presence of M184V at hGRT were independently associated with a higher risk of viral blips (Table 3). In a different model also adjusting for baseline variables that were different between the 2 M184V groups (age, duration of viral suppression, CD4 at nadir, GSS of the accompanying drug), HCV infection (aHR, 2.96; 95% CI, 1.21–7.24; P = .017) and M184V at hGRT (aHR, 2.55; 95% CI, 0.98–6.62; P = .052) were confirmed as independently associated with viral blips.
Table 3.
Predictors of Viral Blips With Lamivudine-Based Dual Therapies
| Univariate Analysis | Multivariable Analysis | |||
|---|---|---|---|---|
| Variables | HR (95% CI) | P Value | aHR (95% CI) | P Value |
| M184V in hGRT | 2.51 (1.15–5.44) | .020 | 2.45 (1.09–5.53) | .030 |
| Type of DT (PI vs INI) | 0.56 (0.19–1.63) | .284 | ||
| Age (+10 y) | ||||
| Gender (male vs female) | 1.79 (0.68–4.70) | .241 | ||
| Ethnicity (Caucasian vs other) | 1.38 (0.18–10.20) | .751 | ||
| Risk factor (ref. sexual) | ||||
| IDU | 1.57 (0.53–4.68) | .420 | ||
| Other/unknown | 1.20 (0.54–3.14) | .558 | ||
| HCV infection (ref. absent) | ||||
| Present | 2.89 (1.21–6.87) | .017 | 2.71 (1.14–6.48) | .025 |
| Unknown | 1.28 (0.50–3.25) | .607 | 1.57 (0.60–4.09) | .361 |
| HBsAg (ref. negative) | ||||
| Positive | 0.00 (0.00–0.01) | .975 | ||
| Unknown | 1.17 (0.50–2.75) | .725 | ||
| Previous AIDS-defining events | 1.08 (0.38–3.13) | .883 | ||
| Time from first ART initiation (+1 y) | 1.04 (0.98–1.10) | .188 | ||
| Time of virological suppression (+1 y) | 1.02 (0.90–1.16) | .753 | ||
| Baseline CD4+ (+100 cells/µL) | 1.07 (0.95–1.21) | .233 | ||
| Nadir CD4+ (+100 cells/µL) | 0.95 (0.73–1.22) | .671 | ||
| Log zenith HIV-RNA | 1.10 (0.66–1.82) | .721 | ||
| GSS of the 2nd drug (+0.5) | 0.29 (0.08–1.56) | .113 | ||
Abbreviations: aHR, adjusted hazard ratio; ART, combined antiretroviral therapy; DT, dual therapy; GSS, genotypic sensitivity score; HBsAg, hepatitis B surface antigen; HCV, hepatitis C virus; hGRT, historical genotype resistance test; HR, hazard ratio; IDU, injective drug users; INI, integrase inhibitor, PI, protease inhibitors. Significant P values (<.05) are in bold.
DISCUSSION
Several randomized studies have shown noninferiority of lamivudine with bPI in virologically suppressed individuals, with respect to triple therapy [2–5]. DT with lamivudine and dolutegravir was also effective in a single-arm prospective study [6]. However, these studies excluded patients with previous resistance to the study drugs. Here we show that a previous selection of the M184V mutation has no major impact on the virological efficacy of lamivudine-based DT as a maintenance regimen. This finding was consistent throughout several sensitivity analyses using different classifications of M184V detection and virological failure. Multivariable analysis adjusting for factors differing between the M184V-positive and -negative groups at DT initiation confirmed the lack of association of this substitution with virological failure. DTs were also more effective than bPI monotherapies, independently from M184V. Moreover, we found no impact of previous M184V detection of the durability of lamivudine-based DT.
This is the first study directly comparing the efficacy of lamivudine-based DT in patients with or without previous detection of the M184V substitution. The ANRS12286/Mobidip trial demonstrated superior virological efficacy of lamivudine plus bPI over bPI monotherapy in patients on an undetectable viral load on bPI-based second-line therapy. In that study, all patients had a previous virological failure on a NNRTI-based firstline therapy, and their viruses harbored multiple mutations (97% had M184V, 59% at least 1 and 27% at least 3 thymidine analogue mutations) [9]. Our study confirms the efficacy of lamivudine-based DT in patients previously selecting the M184V mutation, despite relevant differences between the 2 studies in term of design, resource setting, population characteristics, and virological failure definition. In line with Mobidip, we also show lower rates of virologic failure with DT than with bPI monotherapy, even in patients harboring M184V, even though only the comparison between DT overall vs monotherapy reached statistical significance, not the one between DT with previous selection of the M184V vs monotherapy, probably due to the limited sample size. It has to be highlighted that the chosen comparator was PI monotherapy, not triple therapy, to test whether the lamivudine-based DT in patients carrying M184V could be considered “functional” monotherapy.
Observational studies with small sample size and short follow-up also support the view that past M184V has no impact on the efficacy of lamivudine plus dolutegravir. In a prospective study of 27 patients, 8 carried the M184V mutation in their hGRT, and none of them experienced virological failure in the first year of DT [7], whereas in a cohort of 36 patients switching to this dual regimen, 3 had a prior detection of M184V, and none of these experienced virological failure [13].
One possible explanation for the absence of a major negative impact of the prior M184V mutation on the efficacy of lamivudine-based DT could be its association with decreased viral fitness and with lower replication capacity, lowering the probability of virus rebound [10, 14, 15]. Moreover, recent in vitro studies indicated a protective role of M184V against the selection of dolutegravir resistance mutations, further explaining the lack of impact of this mutation on the efficacy of lamivudine plus dolutegravir [16]. Interestingly, in our cohort, 21 patients on lamivudine plus dolutegravir carried M184V, and none failed after a median follow-up of 10 months, whereas dolutegravir maintenance monotherapy studies have shown measurable failure rates during follow-up of similar duration [17, 18].
Although the main results did not show a significant role for M184V, some sensitivity analyses suggested an effect on treatment efficacy. In particular, in patients with a shorter duration of viral suppression before simplification to DT, the group with previous detection of M184V showed higher hazards of virological failure, and the gap of efficacy between the groups increased when reducing the duration of suppression, particularly below 3 years. This trend is compatible with a progressive decline of the impact of M184V with increasing time since the mutation was last detected. Although the concept of a time-dependent effect likely applies to any resistance mutation (ie, the longer the time the mutation has been not detected, the lower its impact on virological outcome), the declining effect could be faster for those variants with impaired replication, such as M184V. The size of the viral reservoir progressively decreases during the initial 3–4 years of suppressive ART and tends to plateau thereafter [19]. Longer duration of viral suppression could disproportionally reduce the size of the reservoir of replication-impaired viruses because of reduced probability to reseed the reservoir in the context of residual replication under suppressive therapy [20, 21]. Measuring the dynamics of M184V HIV-DNA relative to total HIV-DNA levels over time under suppressive therapy would be required to test this hypothesis. Although the mechanism underlying the time-dependent effect of M184V remains to be clarified, simplification to lamivudine-based DT appears safer in patients carrying M184V who have been fully virologically suppressed for a longer period.
The higher rate of viral blips in patients with past M184V confirms that previous selection of M184V has some negative effect on maintaining complete viral suppression. However, this negative effect was probably mitigated by the activity of the drug accompanying lamivudine. In line with this hypothesis, the GSS of the accompanying drug played a key role in predicting virological failure, together with the higher HIV-RNA zenith. These findings suggest that maintenance DT should be carefully selected based on prior virological history.
Finally, we found an expected negative impact of hepatitis B virus (HBV) co-infection on virological efficacy and durability, as HBsAg is a relative contraindication to lamivudine-containing DT, given lamivudine-limited anti-HBV activity and low genetic barrier to HBV resistance. Even if switching HBsAg+ patients to a regimen without tenofovir is not recommended, it could be partially explained by clinical practice mistakes or by the use of other HBV-active medications (eg, entecavir in patients with contraindications to tenofovir), but these data unfortunately were not available in the database.
This study presents some limitations. Due to its retrospective nature, significant confounders may have gone undetected. The achieved statistical power to detect differences between M184V groups for the main virological failure end point was low. Data about adherence were lacking, measures of medication adherence and exposure were not available, and several baseline characteristics differed between groups.
Nonetheless, when we adjusted the analyses for these characteristics in several multivariable models, still no impact of M184V on virological failure was found.
In conclusion, DT with lamivudine plus bPI or dolutegravir could represent a safe and cheap strategy of ART simplification, both in resource-limited and high-income countries. Even in consideration of the efforts to reach universal access to ART, the possibility to prescribe maintenance regimens with lower toxicity and decreased cost could represent a significant advantage. Based on our findings, a previous selection of M184V should not represent a major obstacle to the efficacy of these regimens, provided that viral suppression has been consolidated and the activity of the drug accompanying lamivudine is fully preserved.
Supplementary Data
Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.
Acknowledgments
Vincenzo Mellace (CATANZARO—SERT Soverato); Amedeo Capetti (MILANO—Prima Divisione Malattie Infettive Ospedale L. Sacco); Maria Rita Gismondo (MILANO—Laboratorio Microbiologia Ospedale L. Sacco [Dipart. Scienze Cliniche, Sez. Malattie Infettive]); Maria Luisa Biondi (MILANO—Laboratorio di Diagnostica Molecolare Infettivologica AO S. Paolo); Cristina Mussini (MODENA—Clinica Malattie Infettive); Monica Pecorari (MODENA—Virologia); Nicola Gianotti (HSR—Studio MUSA); Daria Sacchini (PIACENZA—Malattie Infettive); Giustino Parruti (PESCARA—Malattie Infettive); Ennio Polilli (PESCARA—Virologia Pescara); Franco Baldelli (PERUGIA—Malattie Infettive); Stefania Zanussi (AVIANO—Centro di Riferimento Oncologico); Alessandro Nerli (PRATO—Malattie Infettive); Lucia Lenzi (PRATO—Virologia); Carlo Calzetti (PARMA—Divisione Malattie Infettive ed Epatologia Azienda Ospedaliera); Angela Vivarelli (PISTOIA—Malattie Infettive); Renato Maserati (PAVIA—Ambulatorio Clinica Malattie Infettive S. Matteo); Fausto Baldanti (PAVIA—Virologia S. Matteo); Federica Poletti (VERBANIA—Malattie Infettive VERBANIA); Vincenzo Mondino (VERBANIA—Virologia); Marina Malena (VERONA—Centro di Medicina Preventiva-ULSS 20); Antonio Cascio (PALERMO—Malattie Infettive Policlinico “P. Giaccone”); Gaetano Filice (PAVIA—Clinica Malattie Infettive e Tropicali); Giacomo Magnani (REGGIO EMILIA—Malattie Infettive); Alessandro Zerbini (REGGIO EMILIA—SS Autoimmunità, Allergologia e Biotecnologie Innovative); Francesca Lombardi (ROMA—Laboratorio Virologia Cattolica); Simona Di Giambenedetto (ROMA—Istituto di Clinica Malattie Infettive Cattolica); Massimo Andreoni (ROMA—Cattedra Malattie Infettive Tor Vergata); Marco Montano (ROMA—Virologia per Malattie Infettive Tor Vergata); Vincenzo Vullo (ROMA—Malattie Infettive e Tropicali La Sapienza—Umberto I); Ombretta Turriziani (ROMA—Medicina Sperimentale e Patologia—Sezione Virologia—La Sapienza); Maurizio Zazzi (SIENA—Virologia); Angela Gonnelli (SIENA—Malattie Infettive); Andrea De Luca (SIENA—Malattie Infettive 2); Enzo Boeri (MILANO—Virologia HSR); Stefano Bonora (TORINO—Malattie Infettive Amedeo di Savoia); Valeria Ghisetti (TORINO—Laboratorio di Virologia, Ospedale Amedeo di Savoia); Daniela Francisci (TERNI—Malattie Infettive); Paolo Grossi (VARESE—Clinica Malattie Infettive e Tropicali); Patrizia Bagnarelli (ANCONA—Virologia); Luca Butini (ANCONA—Immunologia Clinica); Romana del Gobbo (ANCONA—Malattie Infettive); Andrea Giacometti (ANCONA—Clinica di Malattie Infettive); Danilo Tacconi (AREZZO—Malattie Infettive); Laura Monno (BARI—Clinica Malattie Infettive Università); Grazia Punzi (BARI—Virologia); Annapaola Callegaro (BERGAMO—Microbiologia e Virologia); Franco Maggiolo (BERGAMO—Malattie Infettive); Alessia Zoncada (CREMONA—Malattie Infettive); Elisabetta Paolini (CREMONA—Servizio Immunoematologia e Medcina Trasfusionale); Laura Sighinolfi (FERRARA—Malattie Infettive AOU S. Anna); Grazia Colao (FIRENZE—Virologia CAREGGI); Paola Corsi (FIRENZE—Malattie Infettive CAREGGI); Pierluigi Blanc (FIRENZE—Malattie Infettive SM Annunziata); Luisa Galli (FIRENZE—Malattie Infettive Pediatria Meyer); Paola Meraviglia (MILANO—Seconda Divisione Malattie Infettive Ospedale L. Sacco); Andrea Tosti (FOLIGNO—Malattie Infettive/SERT); Bianca Bruzzone (GENOVA—Laboratorio di Igiene Ospedale S. Martino); Maurizio Setti (GENOVA—Clinica Medica Immunologia); Giovanni Penco (GENOVA—Malattie Infettive Ospedali Galliera); Antonio Di Biagio (GENOVA—Malattie Infettive Ospedale S. Martino); Cesira Nencioni (GROSSETO—Malattie Infettive); Riccardo Pardelli (LIVORNO—Malattie Infettive); Irene Arcidiacono (LODI—Malattie Infettive); Alberto Degiuli (LODI—Virologia Lodi); Michele De Gennaro (LUCCA—Malattie Infettive); Alessandro Soria (MONZA—Malattie Infettive); Alfredo Focà (CATANZARO—UO di Microbiologia Clinica); Surace/Latella (CATANZARO—Centro Malattie Epatiche e Trapianti); Lucio Cosco (CATANZARO—UO Malattie Infettive Ospedale Pugliese Ciaccio); Sergio Malandrin (MONZA—UO Microbiologia AO S. Gerardo); Paola Milini (MACERATA—Malattie Infettive); Paola Cicconi (MILANO—Clinica di Malattie Infettive Ospedale S. Paolo); Stefano Rusconi (MILANO—Dipart. Scienze Cliniche, Sez. Malattie Infettive—Università degli Studi); Valeria Micheli (MILANO—Laboratorio Microbiologia Ospedale L. Sacco [Seconda Divisione Malattie Infettive]).
Financial support. The authors received no specific funding for this work.
Potential conflicts of interest. Gagliardini reports travel grants from Gilead, Mylan, and Janssen-Cilag. Borghetti reports nonfinancial support from Bristol Myers Squibb, personal fees from Gilead Sciences, and nonfinancial support from ViiV Healthcare. Zazzi reports consultancy for ViiV Healthcare, Gilead Sciences, and Janssen-Cilag and grants for his institution from Viiv Healthcare and Gilead (fellowship program). Di Giambenedetto reports personal fees from Bristol-Myers Squibb, Gilead Sciences, Boehringer Ingelheim, Janssen-Cilag, and GlaxoSmithKline. De Luca reports consultancy forGilead, Viiv, Merk Sharp and Dome, and Janssen-Cilag and grants for his institution from Viiv Healthcare and Gilead (fellowship program). All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
Contributor Information
ARCA Study Group:
Vincenzo Mellace, Amedeo Capetti, Maria Rita Gismondo, Maria Luisa Biondi, Cristina Mussini, Monica Pecorari, Nicola Gianotti, Daria Sacchini, Giustino Parruti, Ennio Polilli, Franco Baldelli, Stefania Zanussi, Alessandro Nerli, Lucia Lenzi, Carlo Calzetti, Angela Vivarelli, Renato Maserati, Fausto Baldanti, Federica Poletti, Vincenzo Mondino, Marina Malena, Antonio Cascio, Gaetano Filice, Giacomo Magnani, Alessandro Zerbini, Francesca Lombardi, Simona Di Giambenedetto, Massimo Andreoni, Marco Montano, Vincenzo Vullo, Ombretta Turriziani, Maurizio Zazzi, Angela Gonnelli, Andrea De Luca, Enzo Boeri, Stefano Bonora, Valeria Ghisetti, Daniela Francisci, Paolo Grossi, Patrizia Bagnarelli, Luca Butini, Romana del Gobbo, Andrea Giacometti, Danilo Tacconi, Laura Monno, Grazia Punzi, Annapaola Callegaro, Franco Maggiolo, Alessia Zoncada, Elisabetta Paolini, Laura Sighinolfi, Grazia Colao, Paola Corsi, Pierluigi Blanc, Luisa Galli, Paola Meraviglia, Andrea Tosti, Bianca Bruzzone, Maurizio Setti, Giovanni Penco, Antonio Di Biagio, Cesira Nencioni, Riccardo Pardelli, Irene Arcidiacono, Alberto Degiuli, Michele De Gennaro, Alessandro Soria, Alfredo Focà, Latella Surace, Lucio Cosco, Sergio Malandrin, Paola Milini, Paola Cicconi, Stefano Rusconi, and Valeria Micheli
References
- 1. Palella FJ Jr, Baker RK, Moorman AC, et al. HIV Outpatient Study Investigators Mortality in the highly active antiretroviral therapy era: changing causes of death and disease in the HIV outpatient study. J Acquir Immune Defic Syndr 2006; 43:27–34. [DOI] [PubMed] [Google Scholar]
- 2. Arribas JR, Girard PM, Landman R, et al. OLE/RIS-EST13 Study Group Dual treatment with lopinavir-ritonavir plus lamivudine versus triple treatment with lopinavir-ritonavir plus lamivudine or emtricitabine and a second nucleos(t)ide reverse transcriptase inhibitor for maintenance of HIV-1 viral suppression (OLE): a randomised, open-label, non-inferiority trial. Lancet Infect Dis 2015; 15:785–92. [DOI] [PubMed] [Google Scholar]
- 3. Di Giambenedetto S, Fabbiani M, Quiros Roldan E, et al. Atlas-M Study Group Treatment simplification to atazanavir/ritonavir+lamivudine versus maintenance of atazanavir/ritonavir+two NRTIs in virologically suppressed HIV-1-infected patients: 48 week results from a randomized trial (ATLAS-M). J Antimicrob Chemother 2017; 72:1163–71. [DOI] [PubMed] [Google Scholar]
- 4. Pulido F, Ribera E, Lagarde M, et al. DUAL-GESIDA-8014-RIS-EST45 Study Group Dual therapy with darunavir and ritonavir plus lamivudine vs triple therapy with darunavir and ritonavir plus tenofovir disoproxil fumarate and emtricitabine or abacavir and lamivudine for maintenance of human immunodeficiency virus type 1 viral suppression: randomized, open-label, noninferiority DUAL-GESIDA 8014-RIS-EST45 trial. Clin Infect Dis 2017; 65:2112–8. [DOI] [PubMed] [Google Scholar]
- 5. Perez-Molina JA, Rubio R, Rivero A, et al. GeSIDA 7011 Study Group Simplification to dual therapy (atazanavir/ritonavir + lamivudine) versus standard triple therapy [atazanavir/ritonavir + two nucleos(t)ides] in virologically stable patients on antiretroviral therapy: 96 week results from an open-label, non-inferiority, randomized clinical trial (SALT study). J Antimicrob Chemother 2017; 72:246–53. [DOI] [PubMed] [Google Scholar]
- 6. Joly V, Burdet C, Landman R, et al. Yazdanpanah. promising results of Dolutegravir + Lamivudine maintenance in ANRS167 LAMIDOL Trial. Poster abstract presented at: PE9/11 at 16th European AIDS Conference; October 25–27, 2017; Milan, Italy. [Google Scholar]
- 7. Charpentier C, Montes B, Perrier M, Meftah N, Reynes J. HIV-1 DNA ultra-deep sequencing analysis at initiation of the dual therapy dolutegravir + lamivudine in the maintenance DOLULAM pilot study. J Antimicrob Chemother 2017; 72(10):2831–2836. [DOI] [PubMed] [Google Scholar]
- 8. Achhra AC, Mwasakifwa G, Amin J, Boyd MA. Efficacy and safety of contemporary dual-drug antiretroviral regimens as first-line treatment or as a simplification strategy: a systematic review and meta-analysis. Lancet HIV 2016; 3:e351–60. [DOI] [PubMed] [Google Scholar]
- 9. Ciaffi L, Koulla-Shiro S, Sawadogo AB, et al. MOBIDIP study group Boosted protease inhibitor monotherapy versus boosted protease inhibitor plus lamivudine dual therapy as second-line maintenance treatment for HIV-1-infected patients in sub-Saharan Africa (ANRS12 286/MOBIDIP): a multicentre, randomised, parallel, open-label, superiority trial. Lancet HIV 2017; 4:e384–92. [DOI] [PubMed] [Google Scholar]
- 10. Miller V, Stark T, Loeliger AE, Lange JM. The impact of the M184V substitution in HIV-1 reverse transcriptase on treatment response. HIV Med 2002; 3:135–45. [DOI] [PubMed] [Google Scholar]
- 11. www.dbarca.net. Accessed 30 December 2017.
- 12. Zazzi M, Prosperi M, Vicenti I, et al. ARCA Collaborative Group Rules-based HIV-1 genotypic resistance interpretation systems predict 8 week and 24 week virological antiretroviral treatment outcome and benefit from drug potency weighting. J Antimicrob Chemother 2009; 64:616–24. [DOI] [PubMed] [Google Scholar]
- 13. Borghetti A, Baldin G, Ciccullo A, et al. Virological control and metabolic improvement in HIV-infected, virologically suppressed patients switching to lamivudine/dolutegravir dual therapy. J Antimicrob Chemother 2016; 71:2359–61. [DOI] [PubMed] [Google Scholar]
- 14. Paredes R, Sagar M, Marconi VC, et al. In vivo fitness cost of the M184V mutation in multidrug-resistant human immunodeficiency virus type 1 in the absence of lamivudine. J Virol 2009; 83:2038–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Campbell TB, Shulman NS, Johnson SC, et al. Antiviral activity of lamivudine in salvage therapy for multidrug-resistant HIV-1 infection. Clin Infect Dis 2005; 41:236–42. [DOI] [PubMed] [Google Scholar]
- 16. Oliveira M, Ibanescu RI, Pham HT, et al. The M184I/V and K65R nucleoside resistance mutations in HIV-1 prevent the emergence of resistance mutations against dolutegravir. AIDS 2016; 30:2267–73. [DOI] [PubMed] [Google Scholar]
- 17. Wijting I, Rokx C, Boucher C, et al. Dolutegravir as maintenance monotherapy for HIV (DOMONO): a phase 2, randomised non-inferiority trial. Lancet HIV 2017; 4:e547–54. [DOI] [PubMed] [Google Scholar]
- 18. Blanco JL, Oldenbuettel C, Thomas R, et al. Pathways of resistance in subjects failing Dolutegravir monotherapy. Oral abstract 42 Conference on Retroviruses and Opportunistic Infections; 13–16 February 2017; Seattle, Washington. [Google Scholar]
- 19. Besson GJ, Lalama CM, Bosch RJ, et al. HIV-1 DNA decay dynamics in blood during more than a decade of suppressive antiretroviral therapy. Clin Infect Dis 2014; 59:1312–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Barton K, Winckelmann A, Palmer S. HIV-1 reservoirs during suppressive therapy. Trends Microbiol 2016; 24:345–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Fourati S, Lambert-Niclot S, Soulie C, et al. HIV-1 genome is often defective in PBMCs and rectal tissues after long-term HAART as a result of APOBEC3 editing and correlates with the size of reservoirs. J Antimicrob Chemother 2012; 67:2323–6. [DOI] [PubMed] [Google Scholar]
- 22. HIV Drug Resistance Database, Stanford University, https://hivdb.stanford.edu. Accessed 30 December 2017.
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.