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AIDS Research and Human Retroviruses
 
AIDS Res Hum Retroviruses. 2009 February; 25(2): 135–139.
PMCID: PMC2755543
NIHMSID: NIHMS146000

Delaying a Treatment Switch in Antiretroviral-Treated HIV Type 1-Infected Patients with Detectable Drug-Resistant Viremia Does Not Have a Profound Effect on Immune Parameters: AIDS Clinical Trials Group Study A5115

Abstract

Some patients are unable to achieve and maintain an undetectable plasma HIV-1 RNA level with combination antiretroviral therapy (ART) and are therefore maintained on a partially suppressive regimen. To determine the immune consequences of continuing ART despite persistent viremia, we randomized 47 ART-treated individuals with low to moderate plasma HIV-1 RNA levels (200–9999 copies/ml) to either an immediate switch in therapy or a delayed switch (when plasma HIV-1 RNA became ≥10,000 copies/ml). After 48 weeks of follow-up, naive and memory CD4+ T cell percents were comparable in the two groups. The proportion of subjects with a lymphocyte proliferative response to Candida, Mycobacterium avium- intracellulare complex, or HIV-gag was also not significantly different at week 48. Delaying a treatment switch in patients with partial virologic suppression and stable CD4+ T cells does not have profound effects on immune parameters.

The immediate goal of antiretroviral therapy (ART) is to reduce plasma HIV-1 RNA levels to below detectable limits. Failure to achieve this goal is associated with the gradual accumulation of drug-resistance mutations, which can compromise future drug options. Some patients, however, are unable to achieve this goal, and are maintained on a partially suppressive regimen. Moreover, the “switch” criteria in many areas of the world is a plasma HIV-1 RNA >10,000 copies/ml.1 Although this approach is associated with the accumulation of drug-resistance mutations,2 it is associated with much slower rates of immunologic and clinical progression, at least as compared to situations in which all treatment is interrupted.3,4

The immune consequences of a delayed switch strategy are uncertain. Most of the data generated to date is retrospective, and therefore subject to survival bias (i.e., those who are better able to maintain peripheral CD4+ T cell counts despite viral replication are more likely to be maintained on a stable regimen). Also, the measurement of peripheral CD4+ T cell counts is an imperfect surrogate for immune function. More comprehensive assessments are now available, but these measurements generally need to be performed in the context of prospective studies because of the need for real-time processing.

AIDS Clinical Trials Group (ACTG) Protocol 5115 was a randomized pilot study that evaluated the optimal time to switch treatment in ART-treated patients with plasma HIV-1 RNA of greater than 200 copies/ml but less than 10,000 copies/ml for at least 52 weeks.5 Subjects were randomized to a switch threshold of either ≥200 copies/ml (immediate switch) or ≥10,000 copies/ml (delayed switch). Subjects in the delayed switch arm were also encouraged to modify therapy if their CD4+ T cells declined by greater than 20% from baseline. We previously reported that 50% of subjects in the immediate switch arm had plasma HIV-1 RNA <50 copies/ml at 48 weeks.5 Ten of 23 subjects in the delayed switch arm met the switch criteria, and 7 had plasma HIV-1 RNA <50 copies/ml at 48 weeks. Subjects in both arms had similar outcomes at 48 weeks postrandomization in terms of drug resistance accumulation, peripheral CD4+ T cell numbers, and frequency of activated (CD38+) CD8+ T cells.5

While CD4+ T cells and CD38+CD8+ T cell frequency are validated surrogates for clinical outcomes in HIV infection,68 these measures do not provide a complete picture of immune function. CD4+ T cells are made up of subsets that are differentially affected by HIV and have variable impact on disease progression. Naive and memory CD4+ T cell frequency can predict clinical progression and CD4+ T cell change in treatment-naive individuals9,10 and after the initiation of ART.11,12 Impairments in lymphocyte proliferative response to antigens are also associated with disease progression13,14 and are not readily restored with ART.15,16 ACTG 5115 provided an opportunity to determine whether these immune parameters are affected by a delay in treatment switch in patients with partial virologic suppression. We also explored the association between these parameters and study outcomes.

The study population and design of ACTG 5115 have been reported elsewhere.5 Peripheral blood mononuclear cells (PBMCs) were obtained from subjects and isolated by density centrifugation at baseline and every 16 weeks through week 48. Four-color flow cytometry was done using antibodies for CD3, CD4, CD45RA, CD45RO, and CD62L that were conjugated to fluorescein isothiocyanate, phycoerythrin, peridinin chlorophyll-protein, or allophycocyanin (Becton Dickinson-Pharmingen, San Jose, CA). The naive CD4+ T cell subset was defined as the percent of CD3+CD4+ T cells that was CD45RA+CD62L+, while the memory T cell subset was defined as the percent that was CD45RACD45RO+. Lymphocyte proliferation in response to pokeweed mitogen (0.1μg/ml; Sigma Chemical, St. Louis, MO), Candida CASTA antigen (10 μg/ml:, Greer Laboratory, Lenoir, NC), Mycobacterium avium-intracellulare complex (MAC) antigen (1:10 dilution; BioWhitaker Laboratory, Walkersville, MD), and HIV p24 antigen/control (5 μg/ml; Protein Sciences, Meriden, CT) was done on fresh PBMCs as described previously.17 Results were expressed as a stimulation index (SI), defined as the ratio of the median counts per minute of the wells with antigen to the median counts per minute of the wells without antigen. An SI  3 was considered a positive response.

Distributions of immunology measures at weeks 0 and 48 between binary groups were compared using the Wilcoxon rank sum test. The p-values reported did not adjust for multiple comparisons. Univariate and multivariate linear or Cox regression models were used to explore baseline immunologic risk factors for various study outcomes.

Of the 45 subjects (22 from the immediate switch arm and 23 from the delayed switch arm) that had baseline immunology data, only 36 subjects (17 from the immediate switch arm and 19 from the delayed switch arm) had available week 48 advanced flow data and only 35 subjects (18 from the immediate switch arm and 17 from the delayed switch arm) had available week 48 pathogen-specific response data. The 36 subjects with available naive and memory CD4+ T cell frequency were statistically comparable to the 9 subjects with incomplete samples in terms of baseline plasma HIV-1 RNA, CD4+ T cells, %CD38+CD8+ T cells, naive and memory CD4+ T cells frequencies, intravenous drug use, sex, race, number of prior ART failure, and pathogen-specific response. However, excluded subjects had marginally higher %CD38+HLA-DR+CD8+ T cells (median 47% for excluded subjects vs. 33.5% for included subjects, p = 0.04). The 35 subjects with available pathogen-specific response measures were statistically comparable to the 10 subjects with incomplete samples in terms of the factors mentioned above, except that the excluded subjects had higher %CD38+HLA-DR+CD8+ T cells (median 48% for excluded subjects vs. 33% for included subjects, p = 0.02) and a higher proportion of female subjects (5/10 for excluded subjects vs. 5/35 for included subjects, p = 0.03).

Naive and memory CD4+ T cell percentages were not significantly different between subjects in the two treatment arms at either baseline or week 48. Median (Q1–Q3) naive T cell percents in the immediate switch arm at baseline and week 48 were 34.5 (24–34)% and 33.5 (28–44)%, respectively, while median (Q1–Q3) naive T cell percents in the delayed switch arm at baseline and week 48 were 31.0 (27–43)% and 31.0 (21–35)%, respectively. Median (Q1–Q3) memory CD4+ T cell percents in the immediate switch arm at baseline and week 48 were 55.5 (51–64)% and 62.5 (55–71)%, respectively, while median (Q1–Q3) memory CD4+ T cell percents in the delayed switch arm at baseline and week 48 were 66.0 (55–74)% and 66.0 (61–74)%, respectively. The median (Q1–Q3) changes in naive CD4+ T cell percents over 48 weeks were 1.0 (−7.0–4.0)% in the immediate switch arm and −1.5 (−6.0–0.5)% in the delayed switch arm. The median (Q1–Q3) changes in memory CD4+ T cell percents over 48 weeks were 0.0 (−5.0–4.0)% in the immediate switch arm and −1.5 (−4.5–0.5)% in the delayed switch arm. No statistically significant difference was detected between the arms.

At baseline, while the proportion of subjects with a positive or negative lymphocyte proliferative response to Candida or HIV-gag was similar between the two arms, there was a trend for more subjects in the delayed switch arm to have a positive response to MAC (p = 0.07) (Table 1).By week 48, the proportion of subjects that had a switch from a negative to positive MAC response was higher in the immediate switch arm (8 of 18, 44%) than in the delayed switch arm (2 of 17, 12%) (p = 0.03). While treatment assignment may account for the difference in the proportion of subjects that had a change in MAC-specific response, the higher proportion of MAC responders in the delayed switch arm at baseline may have made it less likely to demonstrate an increase in MAC response in this arm. There were no consistent differences between the groups in terms of the change in response to either Candida or HIV-gag from baseline to 48 weeks (Table 1). At week 48, the proportion of subjects with a positive or negative response to Candida, MAC or HIV-gag was similar between the two arms.

Table 1.
Lymphocyte Proliferative Stimulation Indices (SI) to Candida, MAC, and HIV-gaga

We next explored the relationship between baseline immune parameters (%CD38+HLA-DR+CD8+ T cells, %naive CD4+ T cells, %memory CD4+ T cells, and pathogen-specific immunity) and the following study endpoints: the occurrence of CDC class B or C events, the change in plasma HIV-1 RNA, and the change in CD4+ T cells, and found no consistent associations in univariate regression models. There was a trend, however, suggesting that a higher naive CD4+ T cell percent was associated with longer time to virologic failure after a treatment switch (p = 0.06).

A surprising finding in ACTG 5115 was that those who switched immediately had lower CD4+ T cells 16 weeks after switching compared to those who delayed their switches.5 At 16 weeks postswitch, CD4+ T cells in subjects in the immediate switch arm decreased by 31 cells/mm3 while they increased by 75 cells/mm3 in subjects in the delayed arm (p = 0.03). To investigate the determinants of CD4+ T cell change postswitch, we included the following factors in univariate and multiple linear regression models: treatment arm assignment, plasma HIV-1 RNA, CD4+ T cells, proportion of naive/memory CD4+ T cells, %CD38+HLA-DR+CD8+ T cells, future drug options index,5 HIV-specific lymphocyte proliferative response, and the change in HIV-1 RNA at 16 weeks postswitch. The diversity of drug regimens used both at baseline and at the time of switch5 did not allow for a meaningful analysis of a drug regimen's effect on outcomes. In the univariate regression models, we found significant associations with treatment arm assignment (p = 0.03), %CD38+HLA-DR+CD8+ T cells (p = 0.05), and HIV gag-specific lymphocyte proliferative response (p = 0.01). If all these three variables were simultaneously included in a multiple regression model, all remained significant [treatment arm assignment (p = 0.004), %CD38+HLA-DR+CD8+ T cells (p = 0.01), and HIV gag-specific lymphocyte proliferative response (p = 0.05)]. Linear regression analysis showed that higher percent naive CD4+ T cells and lower CD8+ T cell activation at the time of the switch resulted in higher CD4+ T cell counts at 16 weeks postswitch.

ACTG 5115 was a pilot randomized prospective study that explored the consequences of delaying a treatment switch in ART-treated patients with persistently detectable viremia under 10,000 copies of HIV-1 RNA/ml. This is an important issue for treatment-experienced patients who may not have access to a regimen that is able to fully suppress HIV replication. The impact of persistent low-to moderate-level viremia on immune function is of particular interest to individuals being treated in resource-poor regions, where newer antiretroviral agents are often not available and the switch criteria may be a plasma HIV-1 RNA >10,000 copies/ml.1 The current analysis reinforces findings from the primary study in that delaying a treatment switch in patients with plasma HIV-1 RNA levels below 10,000 copies/ml was not associated with significant immunologic harm, at least as defined by changes in naive and memory CD4+ T cell frequency, or Candida- and HIV-specific lymphocyte proliferative responses. However, this observation occurred in a setting in which only 50% of subjects in the immediate switch arm achieved virologic suppression. Contemporary regimens that include drugs that were not available at the time of the study can achieve higher rates of virologic suppression in treatment-experienced patients with drug-resistant viremia,18 and may affect the extent of immune reconstitution in these patients. Nevertheless, these observations are consistent with other studies that show that clinical disease progression among treated individuals with low to moderate levels of drug-resistant viremia is relatively slow.1922

In summary, while delaying a treatment switch in the context of partial virologic suppression is associated with the accumulation of drug resistance mutations, it does not have a profound impact on immune parameters in treatment-experienced patients, at least during 48 weeks of observation. Although our sample size is limited, the results of this prospective randomized study are consistent with clinical data from larger cohorts, and argue that in the absence of a fully suppressive regimen, strategies aimed at maintaining viral loads below 10,000 copies RNA/ml should be considered.

Acknowledgments

This work was funded by the following grants from the National Institutes of Health: AI68636 (ACTG); U01-AI069471 (A.R.T.); U01-AI068634 and U01-AI38855 (H.J. and Y.Z.); U01-AI069472 and K24-RR16482 (D.R.K.); U01 AI069484, U01-AI062563, P30-AI64518, and K24-AI0744 (J.A.B.); AI068636 (A.L.L.); and U01-AI069494 (S.A.R.). Other A5115 team members included Hairong Huang (Harvard School of Public Health, Boston, MA) and Edward P. Acosta (University of Alabama, Birmingham). The protocol team is grateful to the individuals who volunteered to participate in this study. The team is also grateful to the following for their contribution to the study's conduct: Rush University Immunology Support Laboratory: Betty Donoval and A5115 Sites/Site Personnel: Lee McClurkin, RN, and Janet Mueller, BS MT (Duke University); Karen Tashima, MD, and Helen Sousa, LPN (Miriam Hospital); Margaret Travis, RN (Rush University Medical Center); Sylvia Stoudt, RN, and Pat Cain, RN (Stanford University); Beverly Putnam, RN ANP, and M. Graham Ray, RN MSN (University of Colorado Health Sciences Center); Lorna Nagamine, RN, and Debra Ogata-Arakaki, RN (University of Hawaii); Jose G Castro, MD, and Margaret A Fischl, MD (University of Miami); Joseph J. Eron, MD, and David Currin RN (University of North Carolina); Nancy Mantz, MSN CRNP (University of Pittsburgh); William A. O'Brien, MD, MS, and Cheryl Mogridge, ACRN (University of Texas, Galveston); Mamta Jain, MD, and Todd Morgan, RS (University of Texas, Southwestern Medical Center); David Haas, MD, Jie Wang, RN, and Michael Morgan, FNP (Vanderbilt University).

Disclosure Statement

No competing financial interests exist.

References

1. World Health Organization. Antiretroviral Therapy for HIV infection in Adults and Adolescents: Recommendations for a Public Health Approach, 2006 Rev. WHO Press; Geneva, Switzerland: 2006. pp. 34–35.
2. Hatano H. Hunt P. Weidler J. Coakley E. Hoh R. Liegler T. Martin JN. Deeks SG. Rate of viral evolution and risk of losing future drug options in heavily pretreated, HIV-infected patients who continue to receive a stable, partially suppressive treatment regimen. Clin Infect Dis. 2006;43:1329–1336. [PubMed]
3. Deeks SG. Barbour JD. Martin JN. Swanson MS. Grant RM. Sustained CD4 + T cell response after virologic failure of protease inhibitor-based regimens in patients with human immunodeficiency virus infection. J Infect Dis. 2000;181:946–953. [PubMed]
4. Lawrence J. Mayers DL. Hullsiek KH. Collins G. Abrams DI. Reisler RB. Crane LR. Schmetter BS. Dionne TJ. Saldanha JM. Jones MC. Baxter JD. Structured treatment interruption in patients with multidrug-resistant human immunodeficiency virus. N Engl J Med. 2003;349:837–846. [PubMed]
5. Riddler SA. Jiang H. Tenorio A. Huang H. Kuritzkes DR. Acosta EP. Landay A. Bastow B. Haas DW. Tashima KT. Jain MK. Deeks SG. Bartlett JA. A randomized study of antiviral medication switch at lower- versus higher-switch thresholds: AIDS Clinical Trials Group Study A5115. Antiviral Ther. 2007;12:531–541. [PubMed]
6. Giorgi JV. Hultin LE. McKeating JA. Johnson TD. Owens B. Jacobson LP. Shih R. Lewis J. Wiley DJ. Phair JP. Wolinsky SM. Detels R. Shorter survival in advanced human immunodeficiency virus type 1 infection is more closely associated with T lymphocyte activation than with plasma virus burden or virus chemokine coreceptor usage. J Infect Dis. 1999;179:859–870. [PubMed]
7. Giorgi JV. Liu Z. Hultin LE. Cumberland WG. Hennessey K. Detels R. Elevated levels of CD38 + CD8 + T cells in HIV infection add to the prognostic value of low CD4 + T cell levels: Results of 6 years of follow-up. The Los Angeles Center, Multicenter AIDS Cohort Study. J Acquir Immune Defic Syndr. 1993;6:904–912. [PubMed]
8. Deeks SG. Kitchen CM. Liu L. Guo H. Gascon R. Narvaez AB. Hunt P. Martin JN. Kahn JO. Levy J. McGrath MS. Hecht FM. Immune activation set point during early HIV infection predicts subsequent CD4 + T-cell changes independent of viral load. Blood. 2004;104:942–947. [PubMed]
9. Chattopadhyay PK. Douek DC. Gange SJ. Chadwick KR. Hellerstein M. Margolick JB. Longitudinal assessment of de novo T cell production in relation to HIV-associated T cell homeostasis failure. AIDS Res Hum Retroviruses. 2006;22:501–507. [PMC free article] [PubMed]
10. Ullum H. Lepri AC. Victor J. Skinhoj P. Phillips AN. Pedersen BK. Increased losses of CD4 + CD45RA + cells in late stages of HIV infection is related to increased risk of death: Evidence from a cohort of 347 HIV-infected individuals. AIDS. 1997;11:1479–1485. [PubMed]
11. Mildvan D. Bosch RJ. Kim RS. Spritzler J. Haas DW. Kuritzkes D. Kagan J. Nokta M. DeGruttola V. Moreno M. Landay A. Immunophenotypic markers and antiretroviral therapy (IMART): T cell activation and maturation help predict treatment response. J Infect Dis. 2004;189:1811–1820. [PubMed]
12. Goicoechea M. Smith DM. Liu L. May S. Tenorio AR. Ignacio CC. Landay A. Haubrich R. Determinants of CD4 + T cell recovery during suppressive antiretroviral therapy: Association of immune activation, T cell maturation markers, and cellular HIV-1 DNA. J Infect Dis. 2006;194:29–37. [PubMed]
13. Gurley RJ. Ikeuchi K. Byrn RA. Anderson K. Groopman JE. CD4 + lymphocyte function with early human immunodeficiency virus infection. Proc Natl Acad Sci USA. 1989;86:1993–1997. [PubMed]
14. Hofmann B. Jakobsen KD. Odum N. Dickmeiss E. Platz P. Ryder LP. Pedersen C. Mathiesen L. Bygbjerg IB. Faber V, et al. HIV-induced immunodeficiency. Relatively preserved phytohemagglutinin as opposed to decreased pokeweed mitogen responses may be due to possibly preserved responses via CD2/phytohemagglutinin pathway. J Immunol. 1989;142:1874–1880. [PubMed]
15. Lederman HM. Williams PL. Wu JW. Evans TG. Cohn SE. McCutchan JA. Koletar SL. Hafner R. Connick E. Valentine FT. McElrath MJ. Roberts NJ., Jr Currier JS. Incomplete immune reconstitution after initiation of highly active antiretroviral therapy in human immunodeficiency virus-infected patients with severe CD4 + cell depletion. J Infect Dis. 2003;188:1794–1803. [PubMed]
16. Blazevic V. Sahgal N. Kessler HA. Landay AL. Shearer GM. T cell responses to recall antigens, alloantigen, and mitogen of HIV-infected patients receiving long-term combined antiretroviral therapy. AIDS Res Hum Retroviruses. 2000;16:1887–1893. [PubMed]
17. Lederman MM. Connick E. Landay A. Kuritzkes DR. Spritzler J. St Clair M. Kotzin BL. Fox L. Chiozzi MH. Leonard JM. Rousseau F. Wade M. Roe JD. Martinez A. Kessler H. Immunologic responses associated with 12 weeks of combination antiretroviral therapy consisting of zidovudine, lamivudine, and ritonavir: Results of AIDS Clinical Trials Group Protocol 315. J Infect Dis. 1998;178:70–79. [PubMed]
18. Steigbigel RT. Cooper DA. Kumar PN. Eron JE. Schechter M. Markowitz M. Loutfy MR. Lennox JL. Gatell JM. Rockstroh JK. Katlama C. Yeni P. Lazzarin A. Clotet B. Zhao J. Chen J. Ryan DM. Rhodes RR. Killar JA. Gilde LR. Strohmaier KM. Meibohm AR. Miller MD. Hazuda DJ. Nessly ML. DiNubile MJ. Isaacs RD. Nguyen BY. Teppler H. Raltegravir with optimized background therapy for resistant HIV-1 infection. N Engl J Med. 2008;359:339–354. [PubMed]
19. Raffanti SP. Fusco JS. Sherrill BH. Hansen NI. Justice AC. D'Aquila R. Mangialardi WJ. Fusco GP. Effect of persistent moderate viremia on disease progression during HIV therapy. J Acquir Immune Defic Syndr. 2004;37:1147–1154. [PubMed]
20. Ledergerber B. Lundgren JD. Walker AS. Sabin C. Justice A. Reiss P. Mussini C. Wit F. d'Arminio Monforte A. Weber R. Fusco G. Staszewski S. Law M. Hogg R. Lampe F. Gill MJ. Castelli F. Phillips AN. Predictors of trend in CD4-positive T-cell count and mortality among HIV-1-infected individuals with virological failure to all three antiretroviral-drug classes. Lancet. 2004;364:51–62. [PubMed]
21. Murri R. Lepri AC. Cicconi P. Poggio A. Arlotti M. Tositti G. Santoro D. Soranzo ML. Rizzardini G. Colangeli V. Montroni M. Monforte AD. Is moderate HIV viremia associated with a higher risk of clinical progression in HIV-infected people treated with highly active antiretroviral therapy: Evidence from the Italian cohort of antiretroviral-naive patients study. J Acquir Immune Defic Syndr. 2006;41:23–30. [PubMed]
22. Kousignian I. Abgrall S. Duval X. Descamps D. Matheron S. Costagliola D. Modeling the time course of CD4 T-lymphocyte counts according to the level of virologic rebound in HIV-1-infected patients on highly active antiretroviral therapy. J Acquir Immune Defic Syndr. 2003;34:50–57. [PubMed]

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