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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
J Infect Dis. Author manuscript; available in PMC 2011 September 1.
Published in final edited form as:
PMCID: PMC2916952

ACTG 5197: A Placebo Controlled Trial of Immunization of HIV-1 Infected Persons with a Replication Deficient Ad5 Vaccine Expressing the HIV-1 Core Protein



HIV-1 specific cellular immunity contributes to control of HIV-1 replication. HIV-1 infected volunteers on antiretroviral therapy received a replication defective Ad5 HIV-1 gag vaccine in a randomized, blinded therapeutic vaccination study.


HIV-1-infected vaccine or placebo recipients underwent a 16-wk analytical treatment interruption (ATI). The log10 HIV-1 RNA at the ATI set point and time averaged area under the curve (TA-AUC) served as co-primary endpoints. Immune responses were measured by intracellular cytokine staining and CFSE dye dilution.


Vaccine benefit trends were seen for both primary endpoints, but did not reach a pre-specified p ≤ 0.025 level of significance. The estimated shift in TA-AUC and set point were 0.24 (unadjusted p=0.04) and 0.26 (unadjusted p=0.07) log10 copies lower in the vaccine than in the placebo arm. HIV-1 gag-specific CD4+ interferon-γ producing cells were an immunologic correlate of viral control.


The vaccine was generally safe and well tolerated. Despite a trend favoring viral suppression among vaccine recipients, differences in HIV-1 RNA levels did not meet the pre-specified level of significance. Induction of HIV-1 gag-specific CD4 cells correlated with control of viral replication in vivo. Future immunogenicity studies should require a substantially higher immunogenicity threshold before an ATI is contemplated.


Advances in antiretroviral therapy have substantially improved the prognosis for individuals with HIV-1. (1, 2) Progression of HIV-1 disease is generally assessed by the CD4 cell count although HIV-1 related morbidity and mortality stems both from AIDS-related opportunistic infections and neoplasms and from “non-AIDS” events including end organ damage to the heart, kidneys, nervous system and the liver (the last especially in persons co-infected with HBV or HCV). (3,4) The rate of CD4 cell decline is influenced by the level of viral replication, although host factors including genetic determinants and T-cell activation state are also important in determining the rate of CD4 cell decline. (5-8) Augmentation of HIV-specific immunity has been proposed as an approach to reduce viral replication and slow disease progression.

HIV-1 specific humoral and cellular immunity are easily demonstrated in individuals who are chronically infected with HIV-1.(9-11) Substantial evidence suggests that HIV-1 specific cellular immunity, in particular, plays an important role in control of viral replication. HIV-1 specific cytotoxic T-cells are first detected during primary infection when levels of HIV-1 RNA decline. (12). Cytotoxic-T cell responses to the HIV-1 gag gene product are associated with control of HIV-1 replication in vivo. (13,14). Depletion of CD8+ cells in SIV-infected rhesus macaques results in a dramatic rise in plasma SIV levels; SIV declines when CD8+ cells return (15,16). HIV-1 specific CD8+ cells can suppress viral replication in vitro by both cytolytic and non-cytolytic mechanisms. (17-19) Finally, vaccine priming of these cells prior to viral challenge is associated with better control of viral replication in simian models. (20,21) Here we report a clinical trial of the safety, immunogenicity and effectiveness of immunization with an HIV-1 gag vaccine in a replication-defective adenovirus vector.


Study Participants

HIV-1 infected individuals aged ≥ 18 and ≤55 on effective antiretroviral therapy for at least 2 years prior to entry with CD4+ cell counts ≥ 500 cells/mm3 and plasma HIV-1 RNA levels ≤50 copies/mL at screening and < 500 copies/mL for the prior 24 months were eligible. Initially participants could not have had a prior confirmed CD4 cell count < 300/mm3 but the protocol was later modified to allow up to 40 participants to have had nadir CD4 cell counts as low as 200/mm3. Except for cutaneous Kaposi sarcoma not anticipated to require systemic therapy, no prior AIDS-defining conditions were allowed. Participants were HBSAg negative with screening Adenovirus Type 5 (Ad5) titers < 200 units/mL. Participants signed informed consent documents approved by institutional review boards at each participating institution.

Study design

In the double blinded study design participants were randomized 2:1 to receive a replication defective Merck Ad5 vaccine containing an HIV-1 gag insert (1010 particles/dose) or a placebo consisting of the vaccine diluents and buffer without the vector and stratified by the highest known pre-therapy HIV-1 RNA level (Stratum I, II and III: <30,000, ≥ 30,000 or unknown, respectively). (22) (Figure 1) Plasma HIV-1 RNA levels and CD4 cell counts were monitored during a 16-week analytical treatment interruption (ATI). Participants were ineligible for ATI if they had a confirmed RNA level>500 copies/ml or CD4 cell count <500/mm3 during the vaccination period and could resume antiretroviral therapy at their discretion.

Figure 1
Study Design. a) Vaccination and treatment interruption schedule. b) Protocol Defined Study Steps

Assessment of virus specific immunity

Virus specific cellular immunity was assessed by peripheral blood lymphocytes interferon-γ production in response to HIV antigens (23,24). Separated mononuclear cells were frozen and shipped overnight on dry ice to Merck Research Laboratories. Lymphocytes were stimulated for 18 hours with gag, nef, or one of two pol (pol1 or pol2) peptide pools consisting of peptides 15 amino acids long and overlapping by 11 amino acids or incubated without peptides (mock stimulation). Interferon-γ production by CD4+ or CD8+ lymphocytes was assessed by 4-color intracellular cytokine flow cytometry. Values are expressed as the number of interferon-γ producing cells/106 lymphocytes after peptide stimulation. Participants were categorized as being responders to a peptide pool when ≥400/106 interferon-γ producing cells were observed and this response was at least 3 times greater than that to the mock peptide pool (except for CD8 response to pol2 which required >500/106 interferon-γ producing cells and ≥ 4 times the response to the mock peptide pool). A “categorical increase” in responsiveness to a peptide pool over baseline was defined as a ≥ 2 fold increase in antigen-specific interferon-γ producing cells over study entry.

Virus specific cellular immunity was also assessed by measuring proliferation of CD4 or CD8 T cells to AT-2 inactivated HIV-1 (MN, Jeffrey Lifson, National Cancer Institute) or HIV-1 p24 antigen (5 ug/mL, Protein Sciences, Meriden CT). Proliferation was assessed by labeling cells with carboxyfluorescein succinimidyl ester (CFSE) dye prior to the stimulation and measuring dye dilution by flow cytometry after 7 days.

Statistical Analysis

The primary goal of the study was to assess the effect of vaccination on viral rebound kinetics during the ATI. Two co-primary endpoints were assessed. For the time averaged area-under-the-curve (TA-AUC) analysis, viral rebound kinetics for each study participant were estimated by the linear trapezoidal method using the first, last and intervening plasma log10 HIV-1 RNA levels observed during the ATI to calculate the AUC and dividing the AUC by the number of days between the first and the last observation. Participants with <2 HIV-1 RNA observations during the ATI were excluded. The null hypothesis of no vaccine effect was tested against-the one-sided alternative that the TA-AUC was lower in the vaccine arm, using a stratified rank-sum test. Participants who did not have an HIV-1 RNA evaluation at Step II in week 16 and who did not register for Step III and did register for Step IV were assigned the worst ranks. The order of ranks was assigned in reverse order of the length of time off therapy; those off therapy for the shortest time were assigned the worst ranks.

The second co-primary endpoint, designated the “ATI viral set point” was defined as the mean of the log10 plasma HIV-1 RNA levels 12 and 16 weeks following treatment interruption. When one value was missing the other value was used. Participants who had neither a week 12 nor a week 16 HIV-1 RNA value were assigned a worst rank. The order of the ranks was assigned as described above. The null hypothesis of no vaccine effect was tested against the one-sided alternative that the ATI setpoint was lower in the vaccine arm, using a stratified rank-sum test.

The endpoints were defined as co-primary endpoints. A two-sample stratified rank sum test was used for each endpoint, adjusted by the Hochberg multiplicity procedure with a family-wise one-sided Type I error set at 0.025 (25). Joint 97.5% confidence lower bounds on the efficacy of vaccination for each endpoint are provided.

The statistical analysis of cellular immunity employed two-sided non-parametric exploratory tests, unadjusted for multiple testing, with nominal 5% Type I errors, based on all subjects with appropriate evaluations. Stratified tests were performed comparing, separately for CD4+ and CD8+ cells and for each antigen at study entry (when appropriate) and follow-up weeks 8, 38 and 42, the vaccine to the placebo arm with respect to a) IFN- γ producing cell count, b) categorical response to antigen, c) absolute change from study entry in IFN- γ producing cell count in response to antigen, d) fold change from study entry in IFN- γ producing cell count in response to antigen, e) categorical increase from study entry in IFN- γ producing cell count in response to antigen, f) absolute change in proliferating cells (CFSE low) from study entry to week 8 and 38 in response to antigen. Also, in the vaccine arm only, one-sample tests of a change from baseline to weeks 8, 38 and 42 were performed for the endpoints (c) and (d) above, and a 95% confidence interval on the probability of a categorical increase (e) was generated.


Study Participants

The study opened in August 2004 and closed in June of 2006 when 114 of the projected 120 study participants had been enrolled. Study closure was prompted by expiration of the vaccine lot dedicated to the study. Baseline characteristics of study participants are summarized in Table 1. Except for an imbalance in the baseline CD4 cell count, entry characteristics were comparable between the 77 vaccine participants and the 37 placebo recipients. The baseline CD4 cell count was not predictive of viral rebound kinetics. All but one of the 114 study participants received the 3 scheduled vaccinations. One vaccine recipient was diagnosed with lung cancer after receiving 2 doses and left the study. Among 113 study participants receiving all 3 injections 110 entered the ATI. Three vaccine recipients elected to continue antiretroviral therapy. During the ATI 3 participants met protocol specified criteria at which reinitiation of therapy was recommended (2 for CD4 cell decline and 1 for viral load increase).

Table 1
Baseline characteristics of participants at study entry


The vaccine was generally safe and well tolerated. Ten participants experienced 14 Grade 3 or 4 adverse events. Three were in placebo recipients and 11 were in vaccine recipients. Two adverse events (headache and thrombocytopenia) were judged by the investigator to be possibly or probably related to the study treatment. The others were scattered in nature and judged not to be study related.

Viral Rebound Kinetics

Viral rebound kinetics were assessed by two metrics. Of the 110 participants undergoing treatment interruption (73 vaccine, 37 placebo), a TA-AUC was calculated as outlined above for 99 of the study participants; 11 were assigned a worst rank based on the pre-specified protocol criteria. The median of the observed endpoints was 3.49 (IQR=3.07 – 3.91) log10 copies/mL among the 67 vaccine recipients and 3.77 (IQR=3.14-4.09) log10 copies/mL among the 32 placebo recipients. For a test of the null hypothesis that the TA-AUC is the same in both arms against the alternative hypothesis that the TA-AUC is lower in the vaccine recipients, the “p” value was 0.04. The rank-based point estimate of the shift of the vaccine arm compared to the placebo arm was that the TA-AUC was 0.24 log10 copies/mL lower in the vaccine arm.

The set point analysis in which the mean of the 12 and 16 week HIV-1 plasma log10 RNA levels were compared was conducted on 110 study participants. Eighty three (55 vaccine; 28 placebo) had week 12 and 16 measurements; 17 study participants (11 vaccine; 6 placebo) had a week 12 value but not a 16 week value; 4 participants (all vaccine) missed a 12 week value and 6 study participants (3 on each arm) had neither value. Of the 23 in which only week 12 values were available or in which both values were missing, 10 had resumed antiretroviral therapy before completing the ATI. The median of the observed week 12 and 16 plasma HIV-1 RNA levels in the vaccine (n=70) and placebo (n=34) arms were 4.10 (IQR=3.56 – 4.45) and 4.28 (IQR=3.65 – 4.72) log10 copies/mL, respectively. (Figure 2). For a test of the null hypothesis that the set point is the same in both arms against the alternative hypothesis that the set point is lower in the vaccine recipients, the “p” value was 0.07. A rank-based point estimate of the shift of the vaccine arm compared to the placebo arm was that the set point was 0.26 log10 copies/mL lower in the vaccine arm. Although vaccine benefit trends were seen for each co-primary endpoint, the study did not reach the protocol-specified level of statistical significance. Joint one-sided 97.5% confidence bounds indicate that the TA-AUC and a viral set point are no more than 0.07 and 0.15 log10 copies, respectively, higher in the vaccine arm than in the placebo arm. Thus, we cannot be certain that vaccination suppressed rebound following cessation of antiretroviral therapy.

Figure 2
Viral Rebound Kinetics Following Interruption of Antiretroviral Therapy

Immunologic responses

Few participants had a predefined CD4+ T cell interferon gamma categorical response to HIV-1 antigen pools prior to vaccination (Figure 3a). Categorical responses to gag were more frequent in the vaccine than in the placebo arm only at week 8 (p = .007). Categorical increases of CD4+ cell responses to gag were observed more frequently in the vaccine arm at week 8 (p < 0.001), week 38 (p=0.05) and week 42 (p=0.03) (Figure 4a). The number of CD4+ cells producing IFN-γ in response to gag was similar in the vaccine and placebo arms at study entry (p=0.88) but was higher in vaccine recipients at week 8 (median [IQR] vaccine = 234 [123, 383], placebo = 129 [72, 211], p=0.0024), and week 38 (vaccine = 205 [104,342], placebo = 131 [77, 244], p=0.0339), but not significantly different at week 42 (Figure 5a). The absolute change in IFN- γ producing CD4+ cell count was greater in the vaccine arm at week 8 (p < 0.0001), week 38 (p=0.0056) and week 42 (p=0.0287); fold changes were also greater at week 8 (p=0.0001), week 38 (p=0.0032) and week 42 (p=0.01). For vaccine (but not placebo) recipients, the median absolute and fold changes at weeks 8, 38 and 42 were all significantly greater than zero (all p-values <= 0.0076). For CD4+ cells producing IFN- γ in response to non-gag antigens, the only statistically significant differences were: the greater absolute change in response to pol1 and pol2 at week 8 (p=0.010 and p=0.003, respectively) and the greater proportion of subjects with categorical increase to pol2 at week 8 (p=0.01) among vaccine recipients. As shown in Figure 4a, the magnitude of these differences was modest.

Figure 3Figure 3
a) - Interferon- γ categorical responses to gag, nef pol1 or pol2 peptide pools in the CD4+ T-cell (a) or the CD8+ T-cell (b) subpopulation vs. time following initiation of vaccination sequence
Figure 4Figure 4
Interferon-γ categorical increase to gag, nef, pol1 or pol2 peptide pools in the CD4+ T-cell (a) or the CD8+ T-cell subpopulation (b) vs. time following initiation of vaccination sequence
Figure 5Figure 5
a) Gag-specific interferon- γ producing CD4+ cell (a) or CD8+ cell (B) count kinetics following initiation of vaccination sequence

Before vaccination, the percentage of all patients with a predefined CD8+ T cell IFN-γ response to HIV-1 antigen pools ranged from 30% (pol1) to 60% (gag) (Figure 3b). The proportions of subjects with CD8+ IFN γ responses to gag were more frequent in the vaccine than the placebo arm at week 38 (p = 0.007) but not significantly different at other weeks (Figure 3b). Categorical increases in CD8+ cell responses to gag were greater in the vaccine arm at week 8 (p=0.01) and week 42 (p=0.001) but not week 38 (Figure 4b). Though comparable at baseline, the number of CD8+ cells per million producing IFN-γ in response to gag was higher in the vaccine arm at week 8 (median [IQR] vaccine = 948 [348,2482], placebo = 569 [173,1187], p=0.0431), but not significantly different at weeks 38 and 42 (Figure 5b). The absolute change in IFN-γ producing CD8+ cell frequency was greater among vaccine than placebo recipients at week 8 (p=0.0146), week 38 (p=0.0402) and week 42 (p=0.024). There were no significant differences with respect to non-gag antigens.

There were no differences between vaccine and placebo arms in the changes in either CD4 or CD8 T cell proliferation in response to HIV or p24 as measured by CFSE dye dilution. (data not shown)

Baseline patient characteristics and viral rebound

To determine whether baseline demographic, clinical or immunological characteristics predicted control of viral rebound after treatment interruption, relationships among a number of baseline patient characteristics and viral rebound RNA AUC and set point were analyzed. None including age, baseline or nadir CD4 cell count were predictive of viral rebound kinetics (data not shown).

Immunologic correlates of viral rebound

Two immunological endpoints were associated both with treatment arm and with rebound kinetics. These were the percentage of CD4+ T cells producing interferon-γ to gag at week 8 (treatment arm association, p=0.0024; viral set-point association, p=0.0157) and 38 (treatment arm association, p=0.0339; viral set-point association, p=0.0028). This immunologic endpoint at weeks 8, 38 and 42 correlated strongly with viral set point (Spearman’s correlation = −0.24 (p=0.0157), −0.3 (p= 0.0028) and −0.4 (p= 0.0001) respectively) (Figure 6). Neither CD4+ nor CD8+ interferon-γ production in response to other HIV-1 peptide pools were predictive of the magnitude of viral rebound.

Figure 6
Associations between ATI viral set point and gag-specific interferon-γ producing CD4+ cell count at study weeks 8, 38 and 42

Though not associated with treatment arm, greater CD4+ cell proliferation to HIV-1 MN at study entry by CFSE dye dilution, predicted a lower viral set-point (Spearman’s correlation = −0.37, p<0.001). A greater increase in CD4+cell proliferation to HIV-1 MN at week 38 was correlated with a higher viral set-point (Spearman’s correlation = 0.33, p=0.004.). A higher percentage of CD8+ cells proliferating to HIV-1 MN and p24 at week 8 correlated with a lower viral set-point (Spearman’s correlation = −0.24 and −0.21, p=0.02 and 0.05 respectively). Greater increases in CD8+ cell proliferation to HIV-1 MN at weeks 8 and 38 also correlated with a lower viral set-point (Spearman’s correlation = −0.23 and −0.22, p=0.03 and 0.05 respectively.)


We found this vaccine to be generally safe and well tolerated in the patient population recruited for this clinical trial. Although the vaccine stimulated HIV-1 specific cellular immune responses, the impact of the vaccine on viral rebound kinetics during the ATI was modest at best. Though vaccination resulted in a modest early increase in HIV-1 gag-directed CD8+ interferon-γ producing cell frequency, vaccine recipients more frequently increased gag-specific interferon-γ CD4+ cell frequencies. CD4+ gag-specific interferon- γ cell proportions strongly correlated with control of viral replication in the ATI. This is consistent with other lines of evidence that CD4+ virus-specific immune responses and gag-directed immune responses, in particular, might be important immunologic correlates of viral control in vivo. (13, 14, 26) Although HIV-1 specific cytolytic activity by CD4+ effector cells has been reported, our study does not establish whether these cells have a direct effect on infected cells, are a surrogate of immune responsiveness, or augment HIV-1 specific cellular immunity indirectly through other cellular effectors. (27)

This study represents only one of many attempts to augment HIV-1 specific immunity in HIV-1 infected persons. (28-41) Although some studies have suggested that immunization might affect viral control in vivo, these effects have generally been modest and at the limits of statistical and/or biological significance. There are any number of reasons that could account for these limited responses. HIV-1 preferentially infects virus-specific CD4+ cells and it is possible that during many years of uncontrolled viral replication few cells remain that can respond to critical viral antigens.(42) Control of HIV-1 replication in vivo is associated with polyfunctional HIV-1 specific effectors that respond to HIV-1 antigenic stimulation with the production of multiple cytokines with cytolytic or immunomodulatory potential. (43-45) It is possible either that precursor cells for this subset of effectors are severely depleted after chronic infection or that current vaccines are incapable of eliciting such cells. A mismatch between viral sequences present in the patient and consensus antigens used in vaccine design could also contribute to the reduced effectiveness. (46) Finally, even if vaccination generates HIV-1 specific effector cells of the appropriate potency and specificity, it is possible that cells might not traffic to sites of HIV-1 replication in lymphoid tissues.(47)

Although we did not detect any adverse clinical outcomes in this trial, the suspension of antiretroviral therapy in individuals who are doing well on effective therapy should not be taken lightly. Interruption of antiretroviral therapy in a group of individuals who were started on therapy with more advanced disease in the SMART study led to an increased rate of HIV-1 associated morbidity and mortality. (3) Since most therapeutic immunization studies are much smaller than the SMART study, such events would likely go undetected in therapeutic vaccine studies.

Clinically meaningful augmentation of HIV-1 specific immunity remains an elusive but important goal that could be of benefit in chronic HIV-1 infection and could provide important insights into the development of an effective preventive vaccine. Future studies with more immunogenic vaccines or in patient populations who might be more likely to respond to vaccination are worthy of consideration. This study provides insights into the potential effects of modest and transient increases in virus-specific cellular immunity on viral rebound kinetics and could serve as a reference point for the degree of immunogenicity that should be exceeded in future studies before candidate vaccines advance to ATI study designs. We believe that ATI should be reserved for vaccines that elicit substantially greater immunogenicity than we observed in this study or that have been demonstrated in other completed studies. We would recommend against inclusion of participants with underlying conditions placing them at increased risk of morbidity from ATI including those with more advanced HIV disease when antiretroviral therapy was started, those at increased cardiovascular risk, those with renal or HIV-1 related neurologic disease or those with HBV or HCV co-infection. Despite favorable trends in viral rebound kinetics, these did not approximate those that would be expected to have any discernible effect on the course of disease.


The ACTG Study Team wishes to acknowledge the study participants without whose participation the study would not have been possible. We also wish to acknowledge the active involvement and support of the Division of AIDS Representative, Dr. Catherine Godfrey; the Study Pharmacist, Dr. Ana Martinez; the Field Representative, Ms. Ann Conrad; the Chief Laboratory Technologist, Ms. Caroline Schnizlein-Beck; and the Laboratory Data Coordinator, Ms. Heather Sprenger and Protocol Specialist Suria Yesmin.

Investigators from the following AIDS Clinical Trials Units enrolled also significantly contributed to the conduct of the study: Harvard, Belleview-NYU, Stanford, UCLA, UC San Diego, UC San Francisco, University of Miami, University of Pittsburgh, University of Rochester, University of Washington, University of Minnesota, Ohio State University, Case Western Reserve, Indiana University, Northwestern/Rush, Beth Israel-New York, Brown University, University of North Carolina, University of Texas-Southwestern, UC Davis, University of Maryland, University of Hawaii, University of Puerto Rico, University of Texas at Galveston, Cornell University.

The study was supported by the National Institute of Allergy and Infectious Diseases. Merck Research Laboratories provided vaccine and placebo and performed some of the immunological assays included in the manuscript.

Acknowledgement Appendix for A5197

Linda Meixner, R.N. and Susan Cahill, R.N.-UCSD, AVRC CRS (Site 701) CTU Grant # AI69432

Trisha Walton RN and Dr. Barbara Gripshover -Case CRS (Site 2501) CTU Grant # AI69501

Sue Richard ANP-C and Kelley Carpenter BA-UNC AIDS CRS (Site 3201) CTU Grant # U01 AI069423-02; M01 RR000046-48; P30AI050410(-11)

David M. Asmuth, MD-University of California Davis Medical Center, ACTU (Site 3851) CTU Grant # U01AI38858

Jorge L. Santana Bagur,MD and Olga Mendez,MD-Puerto Rico-AIDS CRS (Site 5401) CTU Grant # 5 U0I AI069415-03

Robert Kalayjian, MD, Principal Investigator and Kim Whitely, R.N.-MetroHealth CRS (Site 2503) CTU Grant # AI69501

Clyde Crumpacker, MD and Neah Kim, MSN, FNP- Beth Israel Deaconess (Partners/Harvard) CRS (Site 103) CTU Grant # U01 AI069472-03

Deborah McMahon, MD and Nancy Mantz, MSN, CRNP-Pitt CRS (Site 1001) CTU Grant # 1 U01 AI 069494-01

Todd Stroberg, R.N. and Glenn Sturge, B.S.-Cornell CRS (Site 7804) CTU Grant # RR-024996; U01-AI-69419

Mitchell Goldman, MD and Deborah O’Connor, RN, MSN- Indiana University Medical School (Site 2601) CTU Grant # AI25859

Karen Cavanagh RN and Judith A Aberg, M.D.- New York University/NYC HHC at Bellevue Hospital Center (Site 401) CTU Grant #AI -27665; AI069532; GCRC grant # M01RR00096

Beverly E. Sha, MD and Kristine L. Richards, RN-Rush Univ. Med. Ctr. ACTG CRS (Site 2702) CTU Grant # 5 U01 AI069471

Karen Tashima MD and Pamela Poethke RN-The Miriam Hosp. ACTG CRS (Site 2951) CTU Grant# A1069472

Susan L. Koletar, MD and Laura Laughlin, RN- The Ohio State University CRS(Site 2301) CTU Grant # AI069474

Mark Rodriguez, RN and Ge-Youl Kim, R.N.-Washington U CRS (Site 2101) CTU Grant # U01AI069495

Charles E. Davis, Jr. MD and Barbara Glick, RN, BSN-IHV Baltimore Treatment CRS (Site 4651) CTU Grant # RFA-AI 05002

Charles Bradley Hare, MD and Deborah Zeitschel, RN, MSN-UCSF AIDS CRS (Site 801) CTU Grant # 5UO1 AI069502-03

Henry H. Balfour Jr., MD and Kathy Fox, RN, MBA-University of Minnesota, ACTU (Site 1501)

Donna Mildvan, MD and Manuel Revuelta, MD-Beth Israel Medical Center (New York) (Site 2851) CTU Grant # AI46370

Nesli Basgoz, M.D. and Amy Sbrolla, RN, BSN-Massachusetts General Hospital ACTG CRS (Site 101) CTU Grant #UO1 A1 069472

Sandra Valle, PA-C and Debbie Slamowitz, RN-Stanford University AIDS CRS (Site 501) CTU Grant # AI 69556

Ronald Mitsuyasu, M.D. and Suzette Chafey, RN, BSN, MPH-UCLA CARE Center CRS (Site 601) CTU Grant # 5 U01 AI 069424-03

Margaret A. Fischl, M.D. and Hector H. Bolivar, MD- University of Miami School of Medicine, AIDS Clinical Research Unit (Site 901) CTU Grant # AI069477; AI27675; AI073961

Jane Reid RN, MS, APN-BC and Christine Hurley RN-University of Rochester ACTG CRS (Site 1101) CTU Grant # U01 AI069511; GCRC grant # UL1 RR 024160

Ann C. Collier, MD and Beck A. Royer, PA-C-University of Washington AIDS CRS (Site 1401) CTU Grant #: AI069434

Elizabeth Race, MD and Tianna Petersen, MS-UT Southwestern Medical Center at Dallas (Site 3751) CTU Grant# 5U01AI46376-05


Disclosures: Drs. Schooley, Lederman, Pollard and Kuritzkes have served as consultants to Merck Research Laboratories. Drs. Robertson, Mehrotra, Casimiro and Cox are employees of Merck Research Laboratories.

Executive Assistant: Alexis R. Sexton Phone: 858 822-0333, ude.dscu@notxesra

This work was presented in part at the 15th Conference on Retroviruses and Opportunistic Infections, Boston, MA, February 3 - 6, 2008.


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