Advertisement
Research Article

Gender Differences in Immune Reconstitution: A Multicentric Cohort Analysis in Sub-Saharan Africa

  • David Maman mail,

    david.maman@epicentre.msf.org

    Affiliations: Epicentre, Médecins Sans Frontières, Paris, France, Hospices Civils de Lyon, Service de Biostatistique, Lyon, France, Université de Lyon, Lyon, France, Université Lyon I, Villeurbanne, France, CNRS UMR5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique Santé, Pierre-Bénite, France

    X
  • Mar Pujades-Rodriguez,

    Affiliation: Epicentre, Médecins Sans Frontières, Paris, France

    X
  • Fabien Subtil,

    Affiliations: Hospices Civils de Lyon, Service de Biostatistique, Lyon, France, Université de Lyon, Lyon, France, Université Lyon I, Villeurbanne, France, CNRS UMR5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique Santé, Pierre-Bénite, France

    X
  • Loretxu Pinoges,

    Affiliation: Epicentre, Médecins Sans Frontières, Paris, France

    X
  • Megan McGuire,

    Affiliation: Epicentre, Médecins Sans Frontières, Paris, France

    X
  • Rene Ecochard,

    Affiliations: Hospices Civils de Lyon, Service de Biostatistique, Lyon, France, Université de Lyon, Lyon, France, Université Lyon I, Villeurbanne, France, CNRS UMR5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique Santé, Pierre-Bénite, France

    X
  • Jean-François Etard

    Affiliations: Epicentre, Médecins Sans Frontières, Paris, France, TransVIHMI, UMI 233, Montpellier, France

    X
  • Published: February 17, 2012
  • DOI: 10.1371/journal.pone.0031078

Abstract

Background

In sub-Saharan Africa, men living with HIV often start ART at more advanced stages of disease and have higher early mortality than women. We investigated gender difference in long-term immune reconstitution.

Methods/Principal Findings

Antiretroviral-naïve adults who received ART for at least 9 months in four HIV programs in sub-Saharan Africa were included. Multivariate mixed linear models were used to examine gender differences in immune reconstitution on first line ART.

A total of 21,708 patients (68% women) contributed to 61,912 person-years of follow-up. At ART start,. Median CD4 at ART were 149 [IQR 85–206] for women and 125 cells/µL [IQR 63–187] for men. After the first year on ART, immune recovery was higher in women than in men, and gender-based differences increased by 20 CD4 cells/µL per year on average (95% CI 16–23; P<0.001). Up to 6 years after ART start, patients with low initial CD4 levels experienced similar gains compared to patients with high initial levels, including those with CD4>250cells/µL (difference between patients with <50 cells/µL and those with >250 was 284 cells/µL; 95% CI 272–296; LR test for interaction with time p = 0.63). Among patients with initial CD4 count of 150–200 cells/µL, women reached 500 CD4 cells after 2.4 years on ART (95% CI 2.4–2.5) and men after 4.5 years (95% CI 4.1–4.8) of ART use.

Conclusion

Women achieved better long-term immune response to ART, reaching CD4 level associated with lower risks of AIDS related morbidity and mortality quicker than men.

Introduction

According to UNAIDS, more than 3.9 million patients were receiving antiretroviral therapy (ART) in sub-Saharan Africa at the end of 2009. This represents 37% of those in need of treatment and an increase of one million patients in one year [1]. Early initiation of ART in the course of disease is associated with better survival [2], [3] and better long-term immune reconstitution [4], [5]. Indeed, in 2009, the World Health Organization (WHO) raised the recommended CD4 threshold for ART initiation to 350 cells/µL [1], [6].

Immune recovery after ART initiation follows two phases: a rapid increase during the first months, followed by a slower one thereafter [7], [8], [9]. They correspond to different biological mechanisms: the first phase of rapid CD4 cell increase is linked to the relapse of pre-trapped CD4 cells [10], while the second phase corresponds to a proliferation of new CD4 cells, related to thymus reactivation, which progressively reconstitutes stocks of CD4 cells [11]. The feasibility of complete reconstitution remains unknown, as do influencing factors.

Most of large cohort studies describing long-term immune reconstitution have been performed in North American cohorts [12], [13]. In sub-Saharan Africa, the gender differences at ART start are important. In these settings, more women than men are infected [14], [15], as the majority of infections happen through heterosexual transmission. Furthermore, men are frequently underrepresented in ART cohorts, and they initiate ART at a more advanced stage of the disease with a lower CD4 cell counts. [16], [17], [18] In addition, they experience higher early mortality compared with women [17], [19], [20], [21].

This study explored gender differences in immune reconstitution after the first 9 months of ART, to focus on the second phase of immune reconstitution, in four sub-Saharan African HIV programs supported by Médecins Sans Frontières (MSF).

Methods

Data Analysis and Study Population

In collaboration with national Ministries of Health, MSF began providing free HIV care and antiretroviral therapy (ART) in four programs in Malawi, Uganda, and Kenya between March 2001 and July 2002. A standardized surveillance system was implemented to collect routine demographic, clinical, and treatment data (FUCHIA software, Epicentre, Paris, France). Data consistency checks were implemented to ensure the data quality.

The databases used for the analysis were locked on 30 November 2009. ART initiation was based on 2003 and 2006 WHO recommendations. Patients received non-nucleoside reverse transcriptase inhibitor-based first-line therapy in the form of fixed-dose combinations. Adherence support was provided by trained counsellors prior to ART start and during follow-up on treatment. CD4 cell counts were measured every 6 or 12 months, depending on the program, initially using manual methods (Dynabeads, Dynal Biotech SA, Compiègne, France), and since mid-2003 with semi-automated techniques (Cyflow counter, Partec, Münster, Germany).

Patients were included in the study if they (a) had initiated ART in one of the MSF-supported programs, (b) were aged 15 years or older, (c) were ART-naïve at the time of therapy start, (d) received ART for at least 9 months (Figure 1), (e) had complete information about baseline covariates and (f) had at least one CD4 count after 9 months of ART. We included patients at 9 months after ART start because we wanted all the CD4 measures taken at one year to be included, which can sometimes be taken a few months before or after; thus the 9th month was chosen as the inclusion benchmark.

thumbnail

Figure 1. Patient data inclusion flow chart.

doi:10.1371/journal.pone.0031078.g001

The last CD4 measurement considered was the one collected at end of follow-up, at switch to second-line therapy, at transfer out from the program, or closest to time of death, whichever occurred first.

Study Definitions and Statistical Methods

Loss to follow-up was defined as the absence of a clinical visit for at least 9 months (among patients who did not die or were not transferred out of the program) as patients had up to 6 months between two follow-up appointments. Second-line therapy was defined as a protease inhibitor-containing regimen associated with a concomitant change of at least one nucleoside reverse transcriptase inhibitor, as described previously in other studies [22].

For each patient, the initial CD4 cell count was the measurement taken between 3 months before and 1 month after ART start. If more than one measurement was taken, the closest to ART start was considered.

CD4 cell counts were described using medians and interquartile ranges (IQR). CD4 response to ART was the main outcome variable. Random intercept and coefficient mixed linear models with a second-degree natural polynomial of time [23], [24] were used to model long-term immune reconstitution and investigate differences by gender. Random effects characterize between-subject variations whereas fixed effects represent the mean value of a coefficient within the cohort. These models take into account the correlation between CD4 measures within each individual.

Factors considered in adjusted models were time on ART, initial CD4 categories (<50, 50–99, 100–149, 150–199, 200–249, ≥250 cells/µL), body mass index (BMI) (<16, 16–16.99, 17–17.99, ≥18 kg/m2) at ART start, WHO clinical stage at ART start (stages 1 to 4), age at ART start (<30, 30–50, >50 years old), and HIV program. Likelihood ratio (LR) tests and Wald tests for association were used with a significance level of 0.05.

Predicted evolution of mean CD4 counts over time since ART start were plotted, stratified by initial CD4 levels and gender. For female and male patients included in each CD4 cell strata, the mean time to reach a threshold of 500 cells/µL was predicted. The corresponding 95% CI were estimated using the delta method [25]. Data were analyzed using Stata 11 (Stata Corp., College Station, Texas, USA).

This multicentre study was based on analysis of routinely collected, patient monitoring data from the programmes that Médecins Sans Frontières is running in partnership with the local ministry of health for more than 10 years. The data were de-identified before we accessed them. Verbal consent for use of monitoring data is routinely obtained from patients at first consultation, The study protocol and the consent procedure were approved by the Comité de Protection des Personnes d'Ile de France (Ref 10,032), Paris, France.

Results

Patient Characteristics at ART Initiation

Of 39,103 patients who ever received ART in the four HIV programs, 12,946 met the inclusion criteria (Figure 1) and contributed 33,622 person-years at risk to the analysis. Patient median follow-up time since ART start were 2.77 years [IQR 1.86–4.17] for women and 2.64 [IQR 1.74–3.91] for men.

Patients treated in the Malawian cohort represented 52% of eligible patients (Table 1). Women accounted for 69% of patients. At ART start, median age was 36 years [IQR 30; 42]. Among them, 19% of women and 24% of men were classified WHO clinical stage 4. Median initial CD4 count was 141 cells/µL [IQR 77–200], and were higher in women [149 cells/µL; IQR 85–206] than in men [125 cells/µL; IQR 63–187].

thumbnail

Table 1. Study population characteristics at ART start, Uganda, Kenya, and Malawi, 2001–2009.

doi:10.1371/journal.pone.0031078.t001

At ART start, median BMI for women and men were 20.2 kg/m2 [IQR 18.4–22.3] and 19.5 kg/m2 [IQR 18.0–21.1], respectively.

At the end of follow-up, 8,878 women (91%) and 3,638 men (89%) patients were alive and receiving care, 206 men (5%) and 349 women (4%) had been lost to follow-up, 80 men (2%) and 229 women (3%) transferred to other programs. Among the study population 84 men (2%) and 119 women (1%) had died, and 60 men (1%) and 129 women (1%) had initiated second-line treatment.

Observed CD4 Response in Women and Men

Median CD4 cell counts increased with time on ART (Figure 2). The difference between men and women CD4 response also increased with time on ART. At 1 year of ART, women had a median CD4 count of 336 cells/µL [IQR 230–466], compared with 268 cells/µL [IQR 185–387] in men. At 6 years of ART, median CD4 cell count for women and men were 585 cells/µL [IQR 399–735] and 412 cells/µL [IQR 250–551], respectively. Among those who initiated ART with initial CD4 cell count below 50 cells/µL, 134 (15%) women and 127 (19%) men failed to reach a CD4 count of 100 cells/µL after one year on ART.

thumbnail

Figure 2. Observed median CD4 cell counts after ART start, by gender, Uganda, Kenya, and Malawi, 2001–2009.

N = 12,946 patients, 33,622 person-years.

doi:10.1371/journal.pone.0031078.g002

Modelling Long-Term CD4 Response in Women and Men

Detailed results of the model to explore the association between gender and CD4 recovery among patients followed up for more than 9 months on ART are presented in Table 2. From the 21,708 patients meeting the inclusion criteria, 12,946 patients with complete information on all the covariates at baseline and at least one CD4 measure after 9 months on ART contributed to the analysis.

thumbnail

Table 2. Associations between gender and other factors and mean CD4 response to ART.

doi:10.1371/journal.pone.0031078.t002

CD4 count increased regularly during the first 6 years after ART start, with a progressive slowing of immune reconstitution with time on ART.

Women experienced better reconstitution than men, after accounting for all the variables included in the model. After 1 year on ART, women had CD4 count 40 cells/µL (95% CI 34–46) higher than men, with a yearly average increase of 20 CD4 cells/µL higher than men (95% CI 16–23, P<0.0001).

Intervals between initial CD4 strata remained constant over time, as there was no interaction between initial CD4 and time on ART (LR test for interaction with time, P = 0.63). Patients with higher initial CD4 count reached higher CD4 levels after ART start. For example, 1 year after ART start, patients who initiated ART with CD4 count 100–150 cells/µL had a CD4 count on average 107 cells/µL higher than patients with initial count <50 cells/µL (95% CI 98–117). This difference increased with higher initial CD4 levels and was 284 cells/µL (95% CI 272–296) for patients with initial CD4 of 250 cells/µL or more compared to those with <50 cells/µL (LR test for trend, P<0.001).

Age was also associated with immune reconstitution. Patients younger than 30 years old when they initiated ART had mean CD4 count 52 cells/µL (95% CI 42–62) higher than those aged more than 50 years, one year after ART start (LR test, P<0.001). Associations with initial BMI and WHO clinical stage were less strong and did not reach statistical significance when the other variables were accounted in the model.

After 3 years of ART, women and men who had initial CD4 count 100–149 cells/µL reached 475 cells/µL (95% CI 468–482) and 388 cells/µL (95% CI 379–397), respectively (Figures 3 & 4). After 6 years of ART, the same group of patients reached 608 cells/µL (95% CI 594–621) and 467 cells/µL (95% CI 449–484), respectively. After the first year of ART, the higher the initial CD4 cell count, the higher the level of CD4 count was achieved, and these differences continued over time.

thumbnail

Figure 3. Predicted female mean CD4 count after ART start by initial CD4 level, Uganda, Kenya, and Malawi.

N = 8,878; mixed multivariate polynomial model.

doi:10.1371/journal.pone.0031078.g003
thumbnail

Figure 4. Predicted male mean CD4 count after ART start by initial CD4 level, Uganda, Kenya, and Malawi.

N = 4,068; mixed multivariate polynomial model.

doi:10.1371/journal.pone.0031078.g004

For predicted mean time from ART start to reach CD4 500 cells/µL (Table 3), women with initial count <50 cells/µL needed 5.8 years (95% CI 5.5–6.1), while men with the same initial CD4 count were unable to attain this CD4 level. Those men with pre-treatment CD4 count 200–249 cells/µL reached this threshold at 3.2 years (95% CI 3.0–3.4) after ART start whereas it would take only 1.8 years (1.7–1.9) to women.

thumbnail

Table 3. Time in years from ART start to reach CD4 count 500 cells/µL.

doi:10.1371/journal.pone.0031078.t003

Discussion

In this multisite analysis of four large sub-Saharan African HIV programs, long-term immune response up to 6 years after ART start was higher in women compared with men,, independently of characteristics at initiation.

The gender-based difference in immune reconstitution described here has inconsistently been found in previous studies in resource-rich countries, some studies showing a better female immune reconstitution [26], [27] whereas two literature reviews indicated that most of the studies did not find any viroimmunological difference between men and women [28], [29].

In resource-limited settings, studies showing worse male reconstitution are more common. In Cameroon and in China, two studies recently showed male poorer immune reconstitution even after initial patients characteristics were accounted for in the analysis. [30], [31]. In another large multicentric study in sub-Saharan Africa, a gender difference in immune reconstitution was found, but the difference was explained by baseline characteristics [32]. In Senegal, a cohort study found a borderline gender effect which disappeared when viral load and baseline CD4 levels were integrated in the model. [4] At last, a recent cohort study in Tanzania found gender differences in mortality, rates of loss of follow-up or side effects in men but failed to find a significant difference in immune reconstitution after 3 months of ART [33].

Our study confirmed that gender differences in immune reconstitution remained even when baseline factors are included the model. We also showed that this difference increased with time on ART up to 6 years after initiation. Furthermore, we quantified this difference to show that after 6 years on ART, it reached 140 CD4 cells/µL. When we estimated the time on ART required to reach 500 CD4 cells/µL, we found that men remained much longer under this threshold, known to be associated with higher morbidity [2], [34] and mortality [34].

Behavioural, biological factors or a combination of both could explain this difference. First, it is known that men living with HIV usually initiate ART at more advanced stages of disease, resulting in higher mortality [19], [20], [21] highlighting gender differences in health seeking behaviours. Therefore, one possible reason for this gender difference in immune reconstitution could also be behavioural and related to a poorer adherence of men to ART [31], [32]. Decentralization of HIV care in sub-Saharan Africa has been implemented through primary health facilities, and traditionally such care has been well attended by women and children but less so by men. [35] Interventions specifically addressing men's needs might be effective to improve treatment outcomes in this patient population. However, we could not verify this hypothesis as adherence and viral load were not routinely monitored in our cohorts.

Nevertheless, another explanation needs to be explored, reflecting a possible biological explanation. It is known that women have higher physiological CD4 levels compared to men [35], [36], [37] and some studies also underlined the effect of male hormones on the thymic function [37]. Therefore, this gender difference in immune reconstitution could also be linked to a higher potential for women to regenerate their CD4 lymphocytes stock on ART.

We lack of information on women previously exposed to “prevention to mother to child transmission” treatment. Previous exposure to ART (like single dose nevirapine) might underestimate the difference between men and women. The underlining hypothesis would be that women who took these prophylaxis would be more likely to be resistant to ART and thus to have a non optimal immune response. However, recent evidences seem to minimise this influence. [36]

Gender differences in long-term survival outcomes need to be explored and linked to this observed difference in immune reconstitution.

CD4 gains up to 6 years after ART start were similar regardless of the initial CD4 level. We demonstrated for the first time in sub-Saharan African countries that patients who started ART with CD4 count over 250 cells/µL achieved similar CD4 gains up to 6 years after ART initiation than those who initiated at lower CD4 levels. If the influence of initial CD4 level on future reconstitution was well known [4], [8], [12], [13], [38], [39], such levels of reconstitution for patients who initiated ART at high CD4 levels had never been observed previously in sub-Saharan settings. This finding supports the theory that patients may have the same reconstitution potential regardless of baseline CD4. We need to evaluate if complete reconstitution could be feasible if patients were initiated ART at even earlier stage.

This study suggests that long-term CD4 recovery is independent of the level of CD4 cells at ART start, and patients who initiated ART at earlier stages of disease spend shorter time below the threshold of 500 CD4 cells/µL, which is associated with high morbidity [40] and mortality [41], [42]. An earlier start of ART would decrease this high-risk period and facilitate the provision of care in areas suffering from human resources shortages.

Consistent with previous studies, advanced age at initiation was associated with poorer immune reconstitution [27], [43]. This might relate to greater difficulties to reactivate the thymic function and/or to poorer sustained adherence achieved by older patients [44].

We decided to study patient immune response after the first 9 months of ART because during the early stages of treatment, the release of pre-trapped CD4 cells could influence the observed response [45]. The large number of patients included in this analysis allowed careful investigation and quantification of the dose-response effect of initial CD4 counts on immune reconstitution. Indeed, this study used data from four large operational HIV programs running for almost a decade, giving strength to our findings.

Nevertheless, given the definition of inclusion criteria, exclusion of patients because of incomplete initial characteristics is likely to have overestimated the extent of the overall immune reconstitution. Indeed, patients with advanced HIV disease have often been prescribed ART without having initial CD4 count data. Since these patients were likely to have low initial CD4 count values, missing values on initial CD4 count did not follow a random process. Imputation of these missing values was therefore not recommended. Cohort attrition might also have biased estimates. Patients who were included in the analysis were those who survived the first months of ART when mortality is higher. We analyzed routinely collected data without double entry, which could not be implemented for cohorts of this size, though consistency checklists were routinely used to try to reduce data entry errors.

Concerning the generalization of these findings, MSF support on these programs needs to be accounted, as these programs might differ from regular Ministry of Health programs.

In this analysis, we found that women treated for HIV experienced higher immune reconstitution than men, and patients who survived after the first 9 months on ART. Reasons for the gender effect should primarily be investigated through differences in health-seeking and adherence behaviour and addressed to improve outcomes among men.

The paper has not been published or submitted for publication elsewhere. This study was presented at the Conference on Retrovirus and Opportunistic Infections CROI in Boston (David Maman, Mar Pujades-Rodriguez, Fabien Subtil, Loretxu Pinoges, Megan McGuire, René Ecochard, Jean-François Etard. Gender Differences in Long-term Immune Response to ART and Mortality: A Cohort Analysis in 4 Sub-Saharan HIV Programs, CROI Conference, Boston, USA, February 27th–March 2nd 2011.).

Acknowledgments

The authors would like to thank the patients and their families for their motivation and collaboration. We are also grateful to the field teams of Médecins Sans Frontières for their daily work and efforts to provide care to the patients and to ensure regular collection, entry, and cleaning of clinical patient data; and to the Epicentre FUCHIA team for their work maintaining and improving the quality of the data used in these analyses. We also thank Oliver Yun, Medical Editor of Doctors Without Borders/Médecins Sans Frontières (MSF), New York, for his editorial work. Mr Yun, who is employed by MSF, did not receive compensation for his editorial work; he provides free editorial support to authors employed by MSF/Epicentre.

Author Contributions

Data collection and cleaning: DM MM MPR LP. Analyzed the data: DM FS MPR RE JFE. Wrote the paper: DM MPR FS MM LP RE JFE.

References

  1. 1. World Health Organization (2010) Towards Universal Access; Scaling up priority HIV/AIDS interventionsin the health sector. 2010 Progress Report. Geneva: World Health Organisation.
  2. 2. Sterne JA, May M, Costagliola D, de Wolf F, Phillips AN, et al. (2009) Timing of initiation of antiretroviral therapy in AIDS-free HIV-1-infected patients: a collaborative analysis of 18 HIV cohort studies. Lancet 373: 1352–1363.
  3. 3. Kitahata MM, Gange SJ, Abraham AG, Merriman B, Saag MS, et al. (2009) Effect of early versus deferred antiretroviral therapy for HIV on survival. N Engl J Med 360: 1815–1826.
  4. 4. De Beaudrap P, Etard JF, Diouf A, Ndiaye I, Gueye NF, et al. (2009) Modeling CD4+ cell count increase over a six-year period in HIV-1-infected patients on highly active antiretroviral therapy in Senegal. Am J Trop Med Hyg 80: 1047–1053.
  5. 5. Garcia F, de Lazzari E, Plana M, Castro P, Mestre G, et al. (2004) Long-term CD4+ T-cell response to highly active antiretroviral therapy according to baseline CD4+ T-cell count. J Acquir Immune Defic Syndr 36: 702–713.
  6. 6. World Health Organization (2009) Rapid advice: antiretroviral therapy for HIV infection in adults and adolescents
  7. 7. Smith CJ, Sabin CA, Lampe FC, Kinloch-de-Loes S, Gumley H, et al. (2003) The potential for CD4 cell increases in HIV-positive individuals who control viraemia with highly active antiretroviral therapy. AIDS 17: 963–969.
  8. 8. Kaufmann GR, Bloch M, Zaunders JJ, Smith D, Cooper DA (2000) Long-term immunological response in HIV-1-infected subjects receiving potent antiretroviral therapy. AIDS 14: 959–969.
  9. 9. Lawn SD, Myer L, Bekker LG, Wood R (2006) CD4 cell count recovery among HIV-infected patients with very advanced immunodeficiency commencing antiretroviral treatment in sub-Saharan Africa. BMC Infect Dis 6: 59.
  10. 10. Bucy RP, Hockett RD, Derdeyn CA, Saag MS, Squires K, et al. (1999) Initial increase in blood CD4(+) lymphocytes after HIV antiretroviral therapy reflects redistribution from lymphoid tissues. J Clin Invest 103: 1391–1398.
  11. 11. Douek DC, McFarland RD, Keiser PH, Gage EA, Massey JM, et al. (1998) Changes in thymic function with age and during the treatment of HIV infection. Nature 396: 690–695.
  12. 12. Moore RD, Keruly JC (2007) CD4+ cell count 6 years after commencement of highly active antiretroviral therapy in persons with sustained virologic suppression. Clin Infect Dis 44: 441–446.
  13. 13. Kelley CF, Kitchen CM, Hunt PW, Rodriguez B, Hecht FM, et al. (2009) Incomplete peripheral CD4+ cell count restoration in HIV-infected patients receiving long-term antiretroviral treatment. Clin Infect Dis 48: 787–794.
  14. 14. Joint United Nations Programme on HIV/AIDS., World Health Organization. (2010) Report on the global HIV/AIDS epidemic. Geneva: Joint United Nations Programme on HIV/AIDS (UNAIDS): World Health Organization (WHO).
  15. 15. Barth RE, van der Loeff MF, Schuurman R, Hoepelman AI, Wensing AM (2010) Virological follow-up of adult patients in antiretroviral treatment programmes in sub-Saharan Africa: a systematic review. Lancet Infect Dis 10: 155–166.
  16. 16. Muula AS, Ngulube TJ, Siziya S, Makupe CM, Umar E, et al. (2007) Gender distribution of adult patients on highly active antiretroviral therapy (HAART) in Southern Africa: a systematic review. BMC Public Health 7: 63.
  17. 17. Braitstein P, Boulle A, Nash D, Brinkhof MW, Dabis F, et al. (2008) Gender and the use of antiretroviral treatment in resource-constrained settings: findings from a multicenter collaboration. J Womens Health (Larchmt) 17: 47–55.
  18. 18. Cornell M, Myer L, Kaplan R, Bekker LG, Wood R (2009) The impact of gender and income on survival and retention in a South African antiretroviral therapy programme. Trop Med Int Health 14: 722–731.
  19. 19. Kigozi IM, Dobkin LM, Martin JN, Geng EH, Muyindike W, et al. (2009) Late-disease stage at presentation to an HIV clinic in the era of free antiretroviral therapy in Sub-Saharan Africa. J Acquir Immune Defic Syndr 52: 280–289.
  20. 20. Ferradini L, Jeannin A, Pinoges L, Izopet J, Odhiambo D, et al. (2006) Scaling up of highly active antiretroviral therapy in a rural district of Malawi: an effectiveness assessment. Lancet 367: 1335–1342.
  21. 21. May M, Boulle A, Phiri S, Messou E, Myer L, et al. (2010) Prognosis of patients with HIV-1 (2010) infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes. Lancet 376: 449–457.
  22. 22. Pujades-Rodriguez M, O'Brien D, Humblet P, Calmy A (2008) Second-line antiretroviral therapy in resource-limited settings: the experience of Medecins Sans Frontieres. AIDS 22: 1305–1312.
  23. 23. Rabe-Hesketh S, Skrondal A (2008) Multilevel and longitudinal modeling using Stata. College Station, Texas, USA: Stata Press.
  24. 24. Laird NM, Ware JH (1982) Random-effects models for longitudinal data. Biometrics 38: 963–974.
  25. 25. Casella G, Berger RL (2002) Statistical Inference
  26. 26. Giordano TP, Wright JA, Hasan MQ, White AC Jr, Graviss EA, et al. (2003) Do sex and race/ethnicity influence CD4 cell response in patients who achieve virologic suppression during antiretroviral therapy? Clin Infect Dis 37: 433–437.
  27. 27. Hunt PW, Deeks SG, Rodriguez B, Valdez H, Shade SB, et al. (2003) Continued CD4 cell count increases in HIV-infected adults experiencing 4 years of viral suppression on antiretroviral therapy. AIDS 17: 1907–1915.
  28. 28. Nicastri E, Leone S, Angeletti C, Palmisano L, Sarmati L, et al. (2007) Sex issues in HIV-1-infected persons during highly active antiretroviral therapy: a systematic review. J Antimicrob Chemother 60: 724–732.
  29. 29. Braitstein P, Brinkhof MW, Dabis F, Schechter M, Boulle A, et al. (2006) Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries. Lancet 367: 817–824.
  30. 30. Boyer S, Eboko F, Camara M, Abe C, Nguini ME, et al. (2010) Scaling up access to antiretroviral treatment for HIV infection: the impact of decentralization of healthcare delivery in Cameroon. AIDS 24: Suppl 1S5–15.
  31. 31. Dou Z, Xu J, Jiao JH, Ma Y, Durako S, et al. (2011) Gender difference in 2-year mortality and immunological response to ART in an HIV-infected Chinese population, 2006–2008. PLoS One 6: e22707.
  32. 32. Nash D, Katyal M, Brinkhof MW, Keiser O, May M, et al. (2008) Long-term immunologic response to antiretroviral therapy in low-income countries: a collaborative analysis of prospective studies. AIDS 22: 2291–2302.
  33. 33. Hawkins C, Chalamilla G, Okuma J, Spiegelman D, Hertzmark E, et al. (2011) Sex differences in antiretroviral treatment outcomes among HIV-infected adults in an urban Tanzanian setting. AIDS 25: 1189–1197.
  34. 34. Lodwick RK, Sabin CA, Porter K, Ledergerber B, van Sighem A, et al. (2010) Death rates in HIV-positive antiretroviral-naive patients with CD4 count greater than 350 cells per microL in Europe and North America: a pooled cohort observational study. Lancet 376: 340–345.
  35. 35. Bila B, Egrot M (2009) Gender asymmetry in healthcare-facility attendance of people living with HIV/AIDS in Burkina Faso. Soc Sci Med 69: 854–861.
  36. 36. Ekouevi DK, Coffie PA, Chaix ML, Tonwe-Gold B, Amani-Bosse C, et al. (2010) Immunological response to highly active antiretroviral therapy following treatment for prevention of mother to child transmission of HIV-1: a study in Cote d'Ivoire. J Int AIDS Soc 13: 28.
  37. 37. Olsen NJ, Kovacs WJ (2011) Evidence that androgens modulate human thymic T cell output. J Investig Med 59: 32–35.
  38. 38. Falster K, Petoumenos K, Chuah J, Mijch A, Mulhall B, et al. (2009) Poor baseline immune function predicts an incomplete immune response to combination antiretroviral treatment despite sustained viral suppression. J Acquir Immune Defic Syndr 50: 307–313.
  39. 39. Severe P, Juste MA, Ambroise A, Eliacin L, Marchand C, et al. (2010) Early versus standard antiretroviral therapy for HIV-infected adults in Haiti. N Engl J Med 363: 257–265.
  40. 40. Baker JV, Peng G, Rapkin J, Abrams DI, Silverberg MJ, et al. (2008) CD4+ count and risk of non-AIDS diseases following initial treatment for HIV infection. AIDS 22: 841–848.
  41. 41. Emery S, Neuhaus JA, Phillips AN, Babiker A, Cohen CJ, et al. (2008) Major clinical outcomes in antiretroviral therapy (ART)-naive participants and in those not receiving ART at baseline in the SMART study. J Infect Dis 197: 1133–1144.
  42. 42. The HIV-CAUSAL Collaboration (2010) The effect of combined antiretroviral therapy on the overall mortality of HIV-infected individuals. AIDS 24: 123–137.
  43. 43. Florence E, Lundgren J, Dreezen C, Fisher M, Kirk O, et al. (2003) Factors associated with a reduced CD4 lymphocyte count response to HAART despite full viral suppression in the EuroSIDA study. HIV Med 4: 255–262.
  44. 44. Teixeira L, Valdez H, McCune JM, Koup RA, Badley AD, et al. (2001) Poor CD4 T cell restoration after suppression of HIV-1 replication may reflect lower thymic function. AIDS 15: 1749–1756.
  45. 45. Pakker NG, Notermans DW, de Boer RJ, Roos MT, de Wolf F, et al. (1998) Biphasic kinetics of peripheral blood T cells after triple combination therapy in HIV-1 infection: a composite of redistribution and proliferation. Nat Med 4: 208–214.