In many resource-constrained settings, tuberculosis (TB) is the most common AIDS-defining opportunistic infection (OI)1 and is the leading cause of death in patients initiating antiretroviral treatment (ART) in sub-Saharan Africa.2 TB and other OIs may play an important role in immune recovery after ART initiation.3,4 HIV viral replication is enhanced by coinfection with Mycobacterium tuberculosis due to immune activation, which could in turn accelerate the depletion of CD4 cells by virus-induced immune destruction or apoptosis of lymphocytes.5–7 TB treatment is associated with decreased immune activation, after an initial increase during the first month of treatment presumably resulting from release of mycobacterial antigens.5
A recent European study showed an impaired CD4 count recovery among HIV-infected patients presenting with TB at ART initiation.4 There are limited data on the influence of different OIs on immune recovery after starting ART in sub-Saharan Africa and other resource-constrained settings.
We analyzed data from 3 ART programs in South Africa with access to routine CD4 cell count and HIV viral load monitoring to study the immune response after starting ART in adult patients with and without concurrent TB.
We analyzed data from adult patients starting ART between January 1, 2003, and December 31, 2010, in 3 South African treatment programs that participate in the International epidemiologic Databases to Evaluate AIDS in Southern Africa (IeDEA-SA, www.iedea-sa.org)8 collaboration and systematically record OIs (Khayelitsha, Tygerberg, and Themba Lethu Clinic). All sites provide integrated clinical care services for HIV and TB. Data were collected at each site as part of routine monitoring at enrollment and at each follow-up visit. All study sites have local institutional review board or ethics committee approval to collect data and participate in IeDEA-SA. Inclusion criteria were age older than 16 and younger than 85 years and no previous ART exposure. Virologically suppressed patients (<400 HIV RNA copies/mL) at ART initiation and patients with less than 6 months of follow-up were excluded. The selection of eligible patients is shown in the Supplemental Digital Content (see Figure S1, http://links.lww.com/QAI/A389).
A TB episode was defined as a diagnosis of TB (pulmonary/extrapulmonary) at the start of ART, as reported by each site. All three sites used CDC clinical and laboratory case definitions; however, whether the diagnosis of TB was confirmed or probable was not recorded in the database. To account for missing values of WHO clinical stage, CD4 cell count, and viral load at baseline and during follow-up, we generated 10 imputed datasets using the Amelia II package in R.9 The imputation model included age, sex, CD4 count and slope, viral load, observation time, WHO clinical stage, TB site, and treatment program.10 Results were combined with Rubin's rules.11 Patients were expected to have laboratory tests every 6 months for the purpose of determining missing follow-up values.
We used χ2 tests to test the statistical significance of differences between groups in binary variables and the Wilcoxon rank sum test for continuous variables. We calculated CD4 slopes (defined as cells/µL per 6 months) after starting ART up to 4 years of follow-up. We used linear mixed models to evaluate the effect of presenting with TB on slopes, adjusted for age, sex, CD4 count at ART start, current CD4 cell count, time on ART, WHO clinical stage at ART initiation, and treatment program. We further analyzed the effect of restricting the analysis to time under continuous viral suppression defined as time between ART initiation and first viral load rebound (≥1000 copies/mL) or the last follow-up visit. We also modeled CD4 trajectories up to 4 years after starting ART by TB status for 2 CD4 cell strata (<50 and 50–199 cells/µL) using additive linear mixed models. Models included interactions of TB status with splines of time on ART and were adjusted for age, sex, WHO clinical stage, and treatment site. Results for a male reference population aged 35–45 years with WHO clinical stage III from the Themba Lethu Clinic are shown.
All analyses were performed in Stata (version 11.2; Stata Corporation, College Station, TX) and R 12.1 (R Development Core Team, Vienna, Austria).
We included 15,646 adult patients with a median follow-up time of 710 days [interquartile range (IQR) 428–1075 days] and 624 days (IQR 364–967 days) when restricting analyses to time under viral suppression. A total of 10,622 (67.9%) patients were female, and 1052 (6.7%) had a TB diagnosis. Median age at ART initiation was 34 years (IQR 29–40 years), median CD4 cell count 98 cells/µL (IQR 41–161 cells/µL) (see Table S1,Supplemental Digital Content,http://links.lww.com/QAI/A389). Patients presenting with TB had lower median CD4 cell counts (45 versus 102 cells/µL) and more advanced disease (WHO clinical stage IV 39.3% versus 26.9%) compared with all other patients, whereas distributions of age and sex were comparable between the 2 groups (see Table S1, Supplemental Digital Content, http://links.lww.com/QAI/A389).
Patients presenting with TB at ART start gained about 5 CD4 cells more per 6 months than patients without TB [adjusted difference 4.9 CD4 cells/µL per 6 months, 95% confidence interval (95% CI): 0.2 to 9.7, P = 0.04, Table 1]. During the first 6 months, there was little evidence of a difference in CD4 count change (−3.3 CD4 cells, 95% CI: −15.3 to 8.8, P = 0.6). However, from 6 months onward (up to 4 years of follow-up), TB patients were doing slightly better than patients without TB (adjusted difference 6.5 CD4 cells, 95% CI: 2.0 to 11.1, P = 0.01). The results did not substantially change when restricting the analysis to time under viral suppression (Table 1). The proportion of patients with viral load suppression at 12 months was similar between patients presenting and not presenting with TB (80.9% versus 79.1%, P = 0.23).
Women had a more favorable CD4 cell response than men (adjusted difference 2.9 cells/µL, 95% CI: 0.6 to 5.1, P = 0.01), whereas the response was less favorable in older patients and patients with higher baseline CD4 cell counts (see Table S2,Supplemental Digital Content,http://links.lww.com/QAI/A389).
The results from the additive linear mixed model (Fig. 1) showed that patients presenting with TB had a similar CD4 count recovery initially, but a slightly more favorable trajectory in the long-term, consistent with the results for the CD4 slopes. Results were similar for patients with a CD4 cell count below 50 cells/µL at ART start and patients with a CD4 cell count between 50 and 199 cells/µL. Immune recovery was also similar in patients with pulmonary TB (adjusted difference 5.9 cells/µL, 95% CI: 0.3 to 11.5) and patients with extrapulmonary TB (adjusted difference 8.6 cells/µL, 95% CI: 0.7 to 16.5) compared with patients without TB at ART start.
We analyzed HIV-infected adult patients starting ART in 3 large HIV treatment programs in South Africa. We found that overall patients presenting with TB did not experience a worse CD4 cell count recovery after starting ART. The results were similar when restricting analyses to time under viral suppression.
Our results may be explained by several factors. First, TB infection causes immune activation, which is associated with progression to more advanced disease.12 Immune activation may lead to upregulation of HIV replication, as a result to CD4 depletion.5 Therefore, TB treatment alone without ART has a positive effect on the immune system by reducing immune activation, maintaining stable HIV viral load and CD4 cell counts.5,13,14 Second, a survival bias may exist as the most severely ill HIV coinfected TB patients with potentially impaired immune restoration may die before ART can be initiated. Therefore, a selection of patients with a better outcome may be reported in our dataset. Finally, patients with undiagnosed or unreported TB in the non-TB comparison group may present with an immune reconstitution syndrome, and therefore may have a rapid CD4 decline.15
Our finding extends those of a previous study from one of the included cohorts (the Khayelitsha ART program), which showed that receiving TB treatment at ART initiation was associated with an improved CD4 gain.3 In contrast to the previous analysis, we used mixed linear models, modeled nonlinear trajectories, and imputed missing values. Moreover, our analyses included a larger and more representative dataset. Another study from South Africa also failed to show a worse immunological outcome among patients with TB,16 but the analysis was not restricted to time under viral suppression. We found no evidence for a worse immune recovery in patients with extrapulmonary TB. Finally, we also demonstrated that the immune recovery was poorer in men and older patients, as previously shown.3,17 Interestingly, our study contrasts with a recent report from a high-income setting which showed that patients presenting with TB had impaired CD4 cell count responses to ART.4 The impaired immune recovery was mainly driven by a delay in achieving viral suppression.4 Although studies from high-income settings suggested a decrease in viral load after TB treatment in patients with or without additional ART,18,19 we and others failed to show such an effect in sub-Saharan settings in patients receiving TB treatment on ART.20,21 The situation in European countries, however, differs from settings in sub-Saharan Africa with regard to the public health systems, TB screening practices, clinical follow-up, and patient characteristics.
The favorable CD4 cell count immune recovery in patients with concurrent TB remained even when restricting analyses to time under viral suppression. Viral suppression is indicative of adherence to ART. HIV-infected patients on TB treatment may be more adherent to ART, particularly when TB treatment is directly observed. Similarly, the provision of cotrimoxazole or isoniazid preventive therapy has been shown to improve retention in care among pre-ART patients.22,23 However, we found no evidence, as assessed by HIV RNA suppression, for an effect of adherence.
A limitation of our study was the potential underascertainment of TB as shown by the low prevalence of TB cases and the lack of a uniform case definition. The underascertainment of TB may have masked a worse immune recovery after starting ART in patients with TB compared with patients starting without known TB. However, we restricted our study to cohorts that systematically collect information on OIs. Our study may also have been influenced by OIs that occurred during follow-up, but results were similar when restricting analyses to time under viral suppression during which an OI episode is unlikely. Another limitation was the heterogeneity between the included ART programs.24 To address this, we calculated relative differences adjusted for the most important confounding factors.
In summary, we found that HIV-infected patients presenting with TB did not have a worse immune recovery after ART initiation compared with other patients. This is possibly due to a favorable long-term effect of the TB treatment, or factors not captured in our dataset, such as more frequent counseling offered to this patient group or more frequent clinical visits. We stress that immune recovery does not necessarily mean that CD4 cell function is fully restored.25 Our study underscores the benefit of cotreatment of HIV and TB and indicates that management and integration of services may have a positive long-term effect on the immune recovery in resource-constraint settings.
Our study needs to be confirmed in observational data from HIV cohorts with a high degree of diagnostic ascertainment of OIs. Further studies need to focus on integrated TB-HIV management and its effect on OI incidence and immune recovery after ART initiation.
The authors thank all patients whose data were used in this study. Thee authors also would like to thank all who contributed to recording and entering data as well as preparing and sending it to the IeDEA Southern Africa collaboration.
IeDEA-SA participating sites:
Anna Coutsoudis, PMTCT Plus, Durban, South Africa; Diana Dickinson, Gaborone Independent Hospital, Gaborone, Botswana; Brian Eley, Red Cross Children's Hospital, Cape Town, South Africa; Lara Fairall, Free State provincial ARV roll-out, South Africa; Tendani Gaolathe, Princess Marina Hospital, Gaborone, Botswana; Janet Giddy, McCord Hospital, Durban, South Africa; Christopher J Hoffmann, Aurum Institute, Johannesburg, South Africa; Timothy Meade, CorpMed Clinic, Lusaka, Zambia; Patrick MacPhail, Themba Lethu Clinic, Helen Joseph Hospital, Johannesburg, South Africa; Lerato Mohapi, Perinatal HIV Research Unit, Johannesburg, South Africa; Margaret Pascoe, Newlands Clinic, Harare, Zimbabwe; Hans Prozesky, Tygerberg Academic Hospital, Cape Town, South Africa; Harry Moultrie, Enhancing Children's HIV Outcomes (Harriet Shezi Children's Clinic, Chris Hani Baragwanath Hospital, Soweto); Karl Technau, University of Witwatersrand Paediatric HIV Clinics (Empilweni Clinic, Rahima Moosa Mother and Child Hospital, Johannesburg, South Africa); Gilles van Cutsem, Khayelitsha ART Programme and Médecins sans Frontières, Cape Town, South Africa; Paula Vaz, Paediatric Day Hospital, Maputo, Mozambique; Ralf Weigel, Lighthouse Clinic, Lilongwe, Malawi; Robin Wood, Gugulethu and Masiphumelele ART Programmes, Cape Town, South Africa.
1. Brinkhof MW, Egger M, Boulle A, et al.. Tuberculosis after initiation of antiretroviral therapy in low-income and high-income countries. Clin Infect Dis. 2007;45:1518–1521.
2. Lawn SD, Harries AD, Anglaret X, et al.. Early mortality among adults accessing antiretroviral treatment programmes in sub-Saharan Africa. AIDS. 2008;22:1897–1908.
3. Boulle A, van CG, Hilderbrand K, et al.. Seven-year experience of a primary care antiretroviral treatment programme in Khayelitsha, South Africa. AIDS. 2010;24:563–572.
4. Cingolani A, Cozzi LA, Castagna A, et al.. Impaired CD4 T-Cell count response to combined antiretroviral therapy in antiretroviral-naive HIV-Infected patients presenting with tuberculosis as AIDS-defining condition. Clin Infect Dis. 2012;54:853–861.
5. Lawn SD. AIDS in Africa: the impact of coinfections on the pathogenesis of HIV-1 infection. J Infect. 2004;48:1–12.
6. Havlir DV, Barnes PF. Tuberculosis in patients with human immunodeficiency virus infection. N Engl J Med. 1999;340:367–373.
7. Morris L, Martin DJ, Bredell H, et al.. Human immunodeficiency virus-1 RNA levels and CD4 lymphocyte counts, during treatment for active tuberculosis, in South African patients. J Infect Dis. 2003;187:1967–1971.
8. Egger M, Ekouevi DK, Williams C, et al.. Cohort Profile: the international epidemiological databases to evaluate AIDS (IeDEA) in sub-Saharan Africa. Int J Epidemiol. 2012;41:1256–1264.
9. Honaker J, King G, Blackwell M, et al.. Amelia II: A program for missing data, R package version 1.5, 2012. Available at http://gkingharvardedu/amelia/
10. Honaker J, King G. What to do about missing values in time-series cross-section data. Am J Pol Sci. 2010;54:561–581.
11. Rubin DB. Multiple imputation after 18+ years. J Am Stat Assoc. 1996;91:473–489.
12. Wallis RS, Vjecha M, Amir-Tahmasseb M, et al.. Influence of tuberculosis on human immunodeficiency virus (HIV-1): enhanced cytokine expression and elevated beta 2-microglobulin in HIV-1-associated tuberculosis. J Infect Dis. 1993;167:43–48.
13. Lancioni CL, Mahan CS, Johnson DF, et al.. Effects of antiretroviral therapy on immune function of HIV-infected adults with pulmonary tuberculosis and CD4+ >350 cells/mm3. J Infect Dis. 2011;203:992–1001.
14. Morris A, Beard CB, Huang L. Update on the epidemiology and transmission of Pneumocystis carinii. Microbes Infect. 2002;4:95–103.
15. Lawn SD, Wilkinson RJ, Lipman MC, et al.. Immune reconstitution and "unmasking" of tuberculosis during antiretroviral therapy. Am J Respir Crit Care Med. 2008;177:680–685.
16. Lawn SD, Myer L, Bekker LG, et al.. Burden of tuberculosis in an antiretroviral treatment programme in sub-Saharan Africa: impact on treatment outcomes and implications for tuberculosis control. AIDS. 2006;20:1605–1612.
17. Balestre E, Eholie SP, Lokossue A, et al.. Effect of age on immunological response in the first year of antiretroviral therapy in HIV-1-infected adults in West Africa. AIDS. 2012;26:951–957.
18. Goletti D, Weissman D, Jackson RW, et al.. Effect of Mycobacterium tuberculosis
on HIV replication. Role of immune activation. J Immunol. 1996;157:1271–1278.
19. Sulkowski MS, Chaisson RE, Karp CL, et al.. The effect of acute infectious illnesses on plasma human immunodeficiency virus (HIV) type 1 load and the expression of serologic markers of immune activation among HIV-infected adults. J Infect Dis. 1998;178:1642–1648.
20. Lawn SD, Shattock RJ, Acheampong JW, et al.. Sustained plasma TNF-alpha and HIV-1 load despite resolution of other parameters of immune activation during treatment of tuberculosis in Africans. AIDS. 1999;13:2231–2237.
21. Whalen CC, Nsubuga P, Okwera A, et al.. Impact of pulmonary tuberculosis on survival of HIV-infected adults: a prospective epidemiologic study in Uganda. AIDS. 2000;14:1219–1228.
22. Grant AD, Fielding KL, Charalambous S, et al.. Why have trials of isoniazid preventive therapy among people with HIV infection not demonstrated an effect on mortality?: did close examination of the trees obscure our view of the wood? AIDS. 2010;24(suppl 5):S15–S18.
23. Kohler PK, Chung MH, McGrath CJ, et al.. Implementation of free cotrimoxazole prophylaxis improves clinic retention among antiretroviral therapy-ineligible clients in Kenya. AIDS. 2011;25:1657–1661.
24. Fenner L, Forster M, Boulle A, et al.. Tuberculosis in HIV programmes in lower-income countries: practices and risk factors. Int J Tuberc Lung Dis. 2011;15:620–627.
25. Lawn SD, Bekker LG, Wood R. How effectively does HAART restore immune responses to Mycobacterium tuberculosis
? Implications for tuberculosis control. AIDS. 2005;19:1113–1124.