Matthews, Gail V.a; Manzini, Princeb; Hu, Zonghuic; Khabo, Paulb; Maja, Patrickb; Matchaba, Gugub; Sangweni, Phumeleb; Metcalf, Juliec; Pool, Nicholaasd; Orsega, Susanc; Emery, Seana; on behalf of the PHIDISA II study team
HIV/HBV coinfection in sub-Saharan Africa has the potential to become a major public health issue, particularly as the roll-out of antiretroviral therapy (ART) programs continues and mortality from AIDS-related illnesses in HIV-positive individuals falls. In high- income and middle-income countries following the widespread introduction of ART, a marked change in the spectrum of disease in HIV populations occurred with end-stage liver disease accounting for an increasing proportion of deaths, the majority of which resulted from increased liver fibrosis progression in the context of viral hepatitis coinfection [1–4].
In the developed world, the widespread use of tenofovir disoproxil fumarate (TDF), a nucleotide analogue with activity against both HIV and HBV reverse transcriptase, has been highly successful in achieving sustained HBV suppression in both treatment-naive and lamivudine (3TC)-resistant HIV/HBV-coinfected individuals [5–9]. Although an overall reduction in liver-related disease in HIV/HBV-coinfected individuals has not yet been demonstrated, the lack of any confirmed resistance development, combined with reports of fibrosis improvement and end-stage liver disease reversal [7,10,11], suggests that TDF therapy is the gold standard of care for individuals with HIV/HBV coinfection, a position now reflected in current treatment guidelines [12–14].
In resource-limited countries, appropriate diagnosis, monitoring, and therapy for HIV/HBV-coinfected individuals is variable. Pretreatment identification of coinfected patients is often not performed and access to TDF is infrequent; thus, 3TC is often the mainstay of ART in HIV/HBV-coinfected individuals in many countries. A retrospective analysis of HIV/HBV-coinfected individuals from the Canada, Australia, Europe, South Africa study demonstrated that 3TC was better than placebo in achieving HBV DNA reduction at 48 weeks ; however, there are no large-scale randomized clinical trial data on the efficacy of 3TC-containing (HBV-active) ART compared to non-HBV-active ART on HBV-related outcomes in HIV/HBV-coinfected individuals.
PHIDISA II was a randomized, open-label study conducted in the Republic of South Africa (RSA) designed to compare the effect of different ART treatments on AIDS or death among 1771 treatment-naive individuals . Four different ART regimens in a 2x2 factorial design were examined, using a nucleoside analogue backbone of zidovudine along with didanosine, or 3TC along with stavudine. The aims of this analysis were to examine HIV-related and HBV-related outcomes in HIV/HBV-coinfected participants enrolled in PHIDISA II by use of HBV-active (3TC-containing) vs. non-HBV-active (non-3TC-containing) regimens.
Participants in PHIDISA II were uniformed RSA military personnel and their family members who were eligible to receive services from the military health system. HIV-infected adult patients were enrolled at one of six study sites, were antiretroviral naive, with CD4+ T-lymphocyte cell counts less than 200 cells/μl, and/or had any history of or current AIDS-defining illness. Full details of eligibility criteria are given elsewhere .
Participation in this substudy was based on a confirmed positive HBsAg test using stored sera before randomization into PHIDISA II.
The South African National Defence Force Ethics Committee and the National Institute of Allergy and Infectious Diseases Intramural Institutional Review Board approved the PHIDISA II study. Written informed consent, including for the storage of blood specimens, was obtained from all participants.
The overall study design and outcomes of PHIDISA II trial have been described elsewhere .
In particular, relating to this substudy, the 2 × 2 factorial design afforded the opportunity, to compare the activity of 3TC vs. no 3TC in HIV-monoinfected and HIV–HBV-coinfected participants. Treatment switches were allowed for treatment-limiting side-effects and/or virological failure as described. Of note, a study amendment was put into place during the study to allow participants known to be hepatitis B-positive to continue on 3TC if switched off the stavudine component of their ART.
Medical histories, a physical examination, and laboratory studies, including plasma HIV RNA, CD4+ cell count, hematology and clinical chemistry, were obtained prior to randomization. Follow-up visits for data collection occurred monthly for the first 3 months and every 3 months thereafter unless more frequent monitoring was indicated. Numerical mortality data were collected but specific cause of death was not.
Plasma and sera samples were prepared at each follow-up visit for use in retrospective analyses such as the one reported here.
The parent study was closed prematurely on 31 March 2008 after an independent Data Safety Monitoring Board (DSMB) review recommended study termination due to slow recruitment. Median follow-up at this point was 24.7 months.
The outcome measures for this retrospective analysis were predefined and consisted of four hypotheses. First, the use of HBV-active HAART as opposed to non-HBV-active HAART in HIV–HBV-coinfected individuals may impact on immunological but not virological restoration. Second, the incidence of hepatic flare after HAART initiation is significant in HIV–HBV individuals with severe immunosuppression. Third, mortality in HIV–HBV coinfection is increased compared to that in HIV-positive individuals without HBV, but is reduced in long-term follow-up by the use of both HBV-active and non-HBV HAART, and fourth, the use of 3TC-containing ART in HIV/HBV-coinfected individuals is associated with significant reductions in HBV DNA viremia and an increased rate of HBeAg and HBsAg seroconversion compared to HIV–HBV-coinfected individuals on non-3TC-containing ART.
Assays for the testing for this study were performed at Bio Analytical Research Corporation (BARC, Johannesburg, RSA). Architect System by Abbott Laboratories (Diagnostics Division, Abbott Park, USA and Wiesbaden, Germany) using chemiluminescent microparticle immunoassay was used for the qualitative assays for anti-HBe, HBsAg, anti-HBc, and anti-HBs and performed using stored serum from serum separating tubes. HBV viral load was determined using Cobas AmpliPrep/Cobas Taqman HBV test by Roche (Roche Diagnostics. Mannheim, Germany) with a lower limit of detection of less than 54 IU/ml using stored plasma from plasma preparation tubes. For HBV genotyping, INNO-LiPA HBV genotyping was used. Total CD4+, HIV viral load, and alanine aminotransferase (ALT) were done as routine testing required by the PHIDISA II protocol.
Analyses of HIV-related parameters (CD4+ cell count and plasma HIV RNA) and hepatic flare were performed through month 24. Due to limited available stored samples for testing, analyses requiring further laboratory testing (HBV DNA and serological testing) were performed to month 12 only.
For comparisons between the two infection groups (HIV monoinfection and HIV/HBV-co-infected) and the comparisons between 3TC and non-3TC-containing regimens, nonparametric Wilcoxon tests were adopted for continuous variables and Fisher's exact tests for proportions of binary variables.
Logistic regressions were used to assess the association between the risk of hepatic flare and baseline characteristics. Logistic regressions were also used for prediction of HBV NDA suppression by baseline characteristics.
Kaplan–Meier survival curves, together with log rank tests, were adopted for estimating and comparing the time to death, the time to hepatic flare, and the time to HBV DNA suppression between the two infection groups or the two regimens.
The time weighted area under curve (TWAUC) was obtained from GEE (generalized estimation equation) estimation of the time profile of log10 HBV DNA load, and compared between the two regimens by the procedure of bootstrap.
A total of 1771 participants were enrolled into PHIDISA II, of whom 1665 (94%) were HBsAg-negative and 106 were HBsAg-positive, giving a prevalence of HIV/HBV coinfection of 6% [95% confidence interval (CI) 4.9–7.1%]. Of 106 HIV/HBV-coinfected participants, 57 were randomized to 3TC-containing ART and 47 to non-3TC-containing ART. The baseline characteristics of HIV-monoinfected vs. HIV/HBV-coinfected individuals are given in Table 1. HIV/HBV-coinfected individuals were more likely to be men (86 vs. 64%, P < 0.0001) with higher baseline ALT values (39 vs. 28 IU/l, P < 0.0001), lower albumin levels (38 vs. 40 IU/l, P < 0.0001), and lower platelet counts (202 vs. 235 μl, P = 0.002). HIV-related parameters and other variables were similar between the groups.
There were no significant differences in hepatitis B disease markers in HIV/HBV-coinfected participants randomized to 3TC or non-3TC-containing HAART. In the HIV/HBV-coinfected group, the overall median HBV DNA level was 6.79 log10IU/ml [interquartile range (IQR): 3.36–8.41], with similar levels in both 3TC and non-3TC-containing groups (7.0 vs. 6.21 logs, P = 0.74). Fifty two percent of participants were HBeAg-positive. The majority HBV genotype across all participants was A (89%).
The effect of initiation of 3TC vs. non-3TC-containing ART on CD4+ cell count responses and plasma HIV RNA levels from baseline to 24 months were compared in both HIV-monoinfected and HIV/HBV-coinfected individuals. Median gain in CD4+ cell count from ART initiation was not significantly different across all four groups (Fig. 1). Median CD4+ cell count rose by 105, 136, and 126 cells/μl at months 6, 12, and 24, respectively, in the 3TC-containing HIV/HBV group, and by 84, 127, and 192 cells/μl at 6, 12, and 24 months in the non-3TC-containing HIV/HBV group (P > 0.5 for comparison at all time points). An additional TWAUC analysis confirmed no statistically significant difference between the groups in CD4+ cell count recovery over time. Similarly, the proportion of individuals achieving plasma HIV RNA less than 400 copies/ml over time did not vary by HBV status (mono vs. coinfected) or by regimen (3TC vs. non-3TC). The proportion of individuals with undetectable plasma HIV RNA at 24 months was 69.3% in the HIV-monoinfected group and 56.8% in the HIV/HBV-coinfected group (60% 3TC vs. 54% non-3TC, P = 0.77).
Forty-six grade 3 hepatic flare events were observed over 4 months after ART initiation in 39 of 1771 (2.2%) participants. Hepatic flare was significantly more common in HIV/HBV-coinfected individuals (10/106; 9.4%) than in HIV-monoinfected individuals (29/1665; 0.02%), P < 0.0001 (Fig. 2). However, in both HIV-monoinfected and HIV/HBV-coinfected participants, the rate of hepatic flare was not affected when comparing those who did or did not receive 3TC. Six hepatic flare events were observed in four HIV/HBV-coinfected individuals on 3TC, and six hepatic flare events observed in six HIV/HBV-coinfected individuals on a non-3TC regimen. However, a temporal difference in flare events was observed. All four 3TC-treated individuals experienced flare within the first 2 months of treatment, whereas the non-3TC group flares occurred generally later in therapy. In a logistic regression model built to identify factors predicting hepatic flare, only viral hepatitis coinfection (HBV or HCV) was identified as predictive of hepatic flare. Age, weight, baseline CD4+, change in CD4+, baseline ALT, baseline plasma HIV RNA, and 3TC-use were not predictive, either in the overall population or in the HIV/HBV coinfection group alone. In HIV/HBV-coinfected individuals, HBeAg status and baseline HBV DNA level were also not predictive of hepatic flare. None of the episodes of hepatic flare were followed by HBV-related seroconversion.
The overall reduction in ALT in HIV/HBV-coinfected participants from baseline to month 24 was similar in both groups (5 IU/ml 3TC vs. 9 IU/ml non-3TC, P = 0.94).
Hepatitis B virus DNA suppression
Samples were available for HBV viral load and serological testing in only 60 participants by week 48 and analyses were truncated at this time point. Comparison of groups with and without available specimens at week 48 demonstrated no differences in age, sex, baseline CD4+ cell count, and plasma HIV RNA or WHO stage. Reasons for missing samples were 12 deaths and missed visit/lost to follow-up in the other 34. Of those in follow-up with samples available, 95% remained assigned to their original regimen.
The proportion of participants with HBV DNA below the limit of detection (<55 IU/ml) at baseline was 6% in the non-3TC group and 7% in the 3TC group. In the 3TC group, this increased to 34% at month 3 remaining stable thereafter; 35% at month 6, and 33% at month 12 (Fig. 3). In the non-3TC group, 11% of participants had HBV DNA less than 55 IU/ml at 3 months, 19% at 6 months, and 13% at 12 months. The proportion of participants at week 48 with undetectable HBV DNA was, thus, higher in the 3TC group (33 vs. 13%). This difference did not attain statistical significance (P = 0.13). HBV DNA reduction from baseline was also assessed by TWAUC analysis of log10 HBV change from baseline to week 48 in each group. At week 48, the mean time weighted log10 HBV DNA reduction was 1.20 in the 3TC group (95% CI 0.72–1.68) and 0.88 in the non-3TC group (95% CI 0.41–1.35). Switches on or off 3TC-therapy did not account for the lack of statistical difference between groups. Only one patient switched off their original 3TC-containing arm during this period without evidence of HBV rebound. The majority of cases of failure to suppress HBV DNA on 3TC by 12 months were due to persistent viremia rather than virological rebound. Seven participants had an increase in HBV DNA more than 1 log above the nadir by month 12, but none of these had had a previous undetectable HBV DNA.
Predictors of HBV DNA suppression at week 48 were analyzed in a multvariate model. Achieving undetectable HBV DNA at week 48 was positively associated with a lower HBV viral load at baseline [odds ratio (OR) –0.52 per log unit lower, P = 0.02] but not with the use of 3TC (OR −0.17, P = 0.73). HBV suppression was similarly not associated with age, sex, baseline CD4+ cell count, or baseline ALT. Positive HBeAg status was associated with a lower chance of HBV suppression at week 48 in univariate analysis (OR 2.0, P = 0.01) but was nonsignificant in the multivariate model (P = 0.14).
Hepatitis B virus serological change
Over the first 48 weeks of study, HBeAg loss was observed in only four of 43 (9%) of HBeAg-positive individuals, with anti-HBe seroconversion in three (one in 3TC group and two in non-3TC group). HBsAg loss was also observed in three individuals (one HBeAg-negative and two HBeAg-positive at baseline).
Mortality in the PHIDISA II study population was significantly greater in HIV/HBV-coinfected participants than in HIV-monoinfected participants (P = 0.04, Fig. 4). During follow-up, 18 of 106 (17%) coinfected participants died, 11 in the 3TC-containing arm and seven in the non-3TC-containing arm, as compared to 189 of 1665 (11.4%) of monoinfected individuals. Causes of death were not recorded within the main PHIDISA study. At month 24, both median albumin (42 vs. 44 g/l, P = 0.0018) and platelet count (239 vs. 273, P = 0.0013) remained significantly lower in coinfected than monoinfected individuals.
Our analysis of HIV and HBV-related outcomes in HIV/HBV-coinfected participants in a large randomized trial of ART therapy in South Africa provides several important findings with implications for the management of HBV infection in HIV-infected individuals initiating ART resource-limited settings.
Our study found a baseline 6% prevalence of HBsAg positivity consistent with rates of HIV/HBV coinfection in HIV-infected populations globally, but slightly lower than those reported for other African countries, which range from 9.0 to 20.0% [17–21]. Generally, the HIV/HBV-coinfected participants in PHIDISA II were comparable in baseline characteristics to HIV-monoinfected individuals; however, they did differ significantly by sex and by ALT, albumin, and platelets. These findings suggest higher rates of underlying advanced liver disease in the coinfected population and are of concern. In terms of other HBV-specific characteristics, this population had markers of highly active hepatitis B disease with over 50% HBeAg positivity and a median HBV viral load exceeding 7 logs. In fact, only 25% of this group had baseline HBV DNA less than 2000 IU/ml, the internationally accepted indicator of low activity replication. This is in contrast to a recently reported South African study in which over half the coinfected participants had low level HBV viremia . The impact of HBV coinfection on CD4+ cell count recovery after ART initiation in HIV-positive individuals has been debated. Most studies have not found a sustained negative effect of HBV on CD4+ cell count recovery [22,23], although an observational study in Thailand did find significantly lower mean increases in CD4+ cell count in coinfected individuals during the early weeks of therapy . The South African ART cohort study also did not demonstrate different CD4+ cell responses by HBV coinfection status , although in a recent report from Nigeria, HIV/HBV-coinfected individuals demonstrated lower CD4+ cell counts at baseline, and in the HBeAg-positive group, CD4+ cell recovery was delayed in the first 6 months suggesting a possible negative, and unexplained, effect on the response to ART . All of these studies were observational and were not able to examine the role of HBV active treatment, in addition to that of ART, in CD4+ cell count recovery. In PHIDISA II, the randomization to 3TC or non-3TC-containing regimens allowed this effect to be assessed. No difference in baseline CD4+ cell count, CD4+ cell count recovery, or plasma HIV RNA suppression over 2 years of follow-up in HIV/HBV-coinfected individuals compared to HIV-monoinfected individuals was found, irrespective of whether an HBV-active regimen was received or not. These data suggest that the presence of HBV viremia does not negatively impact on immune restoration or control of HIV replication.
The overall rate of grade 3 hepatic flare events in HIV-monoinfected patients within the study was extremely low, occurring in less than 1% of participants. The 10% rate of hepatic flare events observed in HIV/HBV-coinfected participants is higher than that reported in two recent African cohort studies [26,27], although lower than the 25% observed in a smaller HIV/HBV randomized trial from Thailand . As transaminitis is often asymptomatic, some of this difference may undoubtedly be driven by differences in monitoring frequency. Additionally, as hepatic flare is often multifactorial, particularly in the setting of HIV/HBV coinfection, there may be many reasons for varying rates including differences in ART, stage of HBV or HIV disease, and comedications. In the study by Hoffman et al., the highest rate of hepatotoxicity was observed in those with high HBV DNA levels (> 1 × 104 copies/ml); in our study, in which most individuals had high HBV DNA at baseline, we found no predictors of hepatotoxicity, including the use of 3TC vs. no active HBV drug. Due to temporal differences in HBV DNA and ALT sample collection, we were not able to assess the specific relationship between flare and HBV DNA suppression at time of flare.
Overall the efficacy of 3TC on markers of HBV disease in this HIV/HBV-coinfected population was poor. Although a greater proportion of individuals achieved control of HBV viremia by month 12 in the 3TC arm, the effect was observed in a minority of trial participants (33%). Failure to suppress HBV DNA adequately could not be explained by nonadherence, switches in medication, or the occurrence of viral rebound in previously suppressed individuals, and can only be attributed to the inadequacy of this 3TC for HBV control in this population. The only factor associated with a greater chance of HBV DNA suppression at baseline was lower HBV DNA. It is possible, therefore, that there may be a group of individuals with low level HBV viremia in whom 3TC is adequate for viral control and in whom HBV resistance is unlikely; this, however, was not possible to assess within our study.
Of concern, although cause of death was not collected, mortality in the coinfected individuals was significantly greater than those with HIV monoinfection. As we found no difference in baseline disease indicators, immune restoration, or HIV virological control between the groups, at least some of this excess mortality may have been due to HBV-related disease. This is supported by the significantly lower albumin and platelets in this group, important indicators of advanced liver disease. As control of HBV replication has been shown to result in improvement in parameters of liver disease , the failure of these markers to improve over follow-up is hardly surprising given the demonstrated inadequacy of 3TC in suppressing HBV DNA. Unfortunately, due to lack of extended HBV DNA testing and detail on causes of death, we were unable to specifically examine any reduction in mortality in the minority of participants with HBV DNA suppression.
Our study has some limitations. Although this was a prospective randomized trial, HBV DNA testing was performed retrospectively and a number of specimens were unobtainable. As this was particularly true after 48 weeks of follow-up, we decided to limit our analysis to this time point, thereby preventing long-term analysis. However, comparison of the groups with and without samples revealed no major differences between participants with the majority of missing samples attributable to death or missing visits. Given this, it is difficult to conceive that 3TC would have been more successful in this group, and if anything we may have overestimated the efficacy of 3TC.
Our results are somewhat surprising and in contrast to another smaller randomized study involving 3TC and/or tenofovir for the treatment of HIV/HBV in Thailand [15,28]. In that study, although more resistance was seen in the 3TC only arm, the median reduction in HBV DNA at week 48 was high (4.5 logs) and similar across all arms. Even in other studies [15,29], the median reductions in HBV DNA in 3TC-treated patients over 48 weeks were in the region of 2.0–3.0 logs – greater than that in our study. The reasons for this are unclear and may be linked to differences in HBV genotype, more highly replicative HBV DNA, more advanced liver disease in the PHIDISA II population, or possibly even ethnic differences. Unfortunately, HBV resistance testing to identify the frequency of 3TC-resistant HBV in this study was not possible.
In conclusion, this large randomized strategic trial of ART therapy in South Africa demonstrates that in the HIV/HBV-coinfected subpopulation, there was little benefit to the use of 3TC-containing vs. non-HBV-active ART. Immunovirological responses were equally good and hepatotoxicity rates were similar in both arms. Although HBV DNA suppression was marginally better in the 3TC-containing arm, this important goal was not achieved in most individuals and 3TC made no difference to rates of HBV seroconversion. The increased mortality in HIV/HBV-coinfected individuals within this study highlights the ineffectiveness of this strategy and the urgent requirement for better management of HBV disease. WHO guidelines have recently been changed to recommend the use of tenofovir in all HIV/HBV-coinfected populations, including those in resource-limited countries . PHIDISA II provides strong evidence to support further evaluation of this recommendation, given that 3TC provided no demonstrable additional benefit to coinfected individuals over that of ART itself.
Funding was provided by the United States Department of Defense (US DoD) and the United States Department of Health and Human Services (HHS) through the National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH). The Government of the United States through the US DOD and HHS, and the Government of Republic of South Africa (RSA) through its Department of Defence, signed a cooperative agreement, also known as joint research agreement, to conduct this research project.
ClinicalTrials.gov identifier: NCT00342355.
The authors wish to thank the entire PHIDISA staff, as well as the participants who devoted their time and effort to this research project. The authors wish to acknowledge the following Specialist consultants: Clindev who provided regulatory monitoring, Science Applications International Corporation Frederick, Inc. (SAIC Frederick), and BARC (Bio Analytical Research Corporation) who provided laboratory and personnel support, and the Henry Jackson Foundation for project and personnel support.
G.M. designed, interpreted analysis and wrote the draft manuscript.
P.M. conceived the study, interpreted analyses, and provided critical review of the draft manuscript.
Z.H. designed and performed statistical analysis and provided critical review of the draft manuscript.
P.K., P.M., and G.M. assisted with study design, coordinated data collection, interpreted analyses, and provided critical review of the draft manuscript.
J.M. and N.P. supervised laboratory testing, provided interpretation of analyses, and critical review of the draft manuscript.
S.O. provided review of the study design, supported data collection, and laboratory analyses. She assisted with interpretation of analyses and provided critical review of the manuscript.
S.E. assisted with study design and data collection, provided interpretation of study data, and provided critical review of the manuscript.
Conflicts of interest
P.M., P.M. P.K., P.S., S.O., G.M., and J.M. report no conflict of interests.
N.P. is employed by BARC laboratories who performed the HBV DNA testing for the study.
G.M. has received payment for educational materials from BMS, Roche, and MSD and traveling expenses from MSD.
S.E. has received travel/accommodation expenses from Merck Labs.
The PHIDISA II Study Group for Project PHIDISA.
Collaborators contributed to the study from the South Africa Medical Health Services (SAMHS), South African Defence Force (SANDF), Pretoria, South Africa; National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health, Bethesda, Maryland, United States of America; Critical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland, United States of America; Charisma Health, Pretoria, South Africa; University of Minnesota (UM), Minneapolis, Minnesota, United States of America; National Centre in HIV Epidemiology and Clinical Research, University of New South Wales. Sydney, Australia; Science Applications International Corporation (SAIC), Frederick, Maryland, United States of America; Palladian Partners Incorporated, Silver Spring, Maryland, United States of America; KwaZulu-Natal Department of Health, Pietermaritzburg, South Africa; United States Department of Defense (US DoD), Washington, DC, United States of America.
Senior Protocol Writing team: A. Ratsela (SAMHS National Principal Investigator), M. Polis (NIAID co-Principal Investigator), S. Dhlomo (KwaZulu-Natal Department of Health), S. Emery (University of New South Wales), G. Grandits (UM), P. Khabo (Charisma), T. Khanyile (SAMHS), S. Komati (SAMHS), J.D. Neaton (UM), C. Naidoo (SAMHS), D. Magongoa (SAMHS), D. Qolohle (SAMHS).
Executive Committee Present – S. Brodine (DOD), H.C. Lane (NIAID), N. Motumi (SAMHS), M. Radebe (SAMHS).
Past – X. Currie (SAMHS), A. Jamuna (SAMHS), P. J Oelofse (SAMHS), S. Ngqakayi (SAMHS), L. Siwisa (SAMHS), S. Swanapoel (SAMHS).
Data and Safety Monitoring Board – J. Levin (Chairperson- Pretoria, South Africa), W.N. Rida (Bethesda, Maryland, USA), T. Morodi (Pretoria, South Africa), Y. Leeuw (Pretoria, South Africa).
SAMHS South Africa Clinical sites Principal Investigator/Study Coordinator – 1-Military Site, Pretoria – S. Hassim, L. Malan; 3-Military Site, Cape Town – H. Somarro, T. Mokhathi, Bloemfontein – N. Mokwena, N. Coangae; Mtubatuba – T. Khanyile, Z. Yokwana; Mthata – B. Mabindla, G. Manqola; Phalaborwa – M. Maluleke, T. Tseka.
PHIDISA Headquarter staff – J. Dlamiini (Charisma), L. Ledwaba (Charisma), M. Marumo (SAMHS), U. Matchaba (Charisma), J. Mthethwa (SAMHS), P. Sangweni (Charisma).
US PHIDISA team – B. Baseler (SAIC Frederick), R. Eckes (NIAID), H. Masur (NIH Clinical Center), B. Grace (SAIC Frederick), G. Morgan (Palladian), L. McNay (NIAID), J. Metcalf (NIAID), S. Orsega (NIAID), A. Pau (NIAID), J. Tavel (NIAID), J. Zuckerman (NIAID), M. Simpson (SAIC Frederick), H, Highbarger (SAIC-Frederick), R. Dewar (SAIC Frederick).
Statistical and Data Management support – University of Minnesota – A. DuChene, M. Harrison, A. Lifson.
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