Objective: To determine the impact of tuberculosis (TB) treatment at the time of combination antiretroviral therapy (cART) initiation on virologic and CD4+ cell count response to cART.
Methods: Systematic review and meta-analysis of studies reporting HIV RNA and CD4+ cell count response, stratified by TB treatment status at cART initiation. Stratified random-effects and meta-regression analyses were used when possible.
Results: Twenty-five eligible cohort studies reported data on 49 578 (range 42–15 646) adults, of whom 8826 (18%) were receiving TB treatment at cART initiation. Seventeen studies reported virologic response; 21 reported CD4+ cell count response. The summarized random-effects relative risk (RRRE) of virologic suppression in those receiving vs. not receiving TB treatment at different time points following cART initiation was 1.06 (0.86–1.29) at 1–4 months, 0.91 (0.83–1.00) at 6 months, 0.99 (0.94–1.05) at 11–12 months, and 0.99 (0.77–1.28) at 18–48 months. The overall RRRE at 1–48 months was 0.97 (95% confidence interval 0.92–1.03). Available data regarding the effect of TB treatment on virologic failure were heterogeneous and inconclusive (13 estimates). Differences in median CD4+ cell count gain between those receiving vs. not receiving TB treatment ranged from −10 to 60 cells/μl (median 27) by 6 months (seven estimates) and −10 to 29 (median 6) by 11–12 months (five estimates), although the heterogeneity of the response measures did not support meta-analysis.
Conclusion: Patients receiving TB treatment at cART initiation experience similar virologic suppression and CD4+ cell count reconstitution as those not receiving TB treatment, reinforcing the need to start cART during TB treatment and allowing more confidence in clinical decision-making.
aDepartment of Epidemiology
bDivision of Infectious Diseases
cCenter for AIDS Research, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Correspondence to Heidi M. Soeters, Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 2101 McGavran-Greenberg Hall, CB #7435, Chapel Hill, NC 27599-7435, USA. Tel: +1 404 308 1200; e-mail: email@example.com
Received 3 July, 2013
Accepted 14 July, 2013
Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website (http://www.AIDSonline.com).
Tuberculosis (TB) threatens the health of people living with HIV (PLWH). Globally in 2011, 13% of incident TB cases were coinfected with HIV and an estimated 0.4 million TB deaths occurred among PLWH . Given the World Health Organization's 2010 recommendation that all PLWH with TB be initiated on combination antiretroviral therapy (cART), regardless of CD4+ cell count , and the goal of 100% cART coverage of coinfected patients by 2015 , many individuals are initiating cART while concurrently on TB therapy. PLWH who are also being treated for TB may experience a differential response to cART due to drug–drug interactions [4,5], an increased risk of drug toxicity [4,5], immune reconstitution inflammatory syndrome (IRIS) , and the potential for lower adherence due to the high pill burden . The effect of TB treatment and its associated potential challenges and complications regarding a patient's response to cART require careful evaluation.
We aimed to describe the impact of receiving TB treatment at the time of cART initiation on virologic and CD4+ cell count response to cART among HIV-infected adults. In addition, we highlighted the various outcome measures used in the literature and make recommendations for some methodological standards that may ease future between-study comparisons.
Search strategy and selection criteria
To investigate the effect of TB treatment at time of cART initiation on virologic response and CD4+ cell count response, we carried out a systematic and sensitive search using an a priori protocol developed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines . We searched PubMed and EMBASE, as well as abstract databases, from the 2009 to 2012 Conferences on Retroviruses and Opportunistic Infections, International Union Against Tuberculosis and Lung Disease World Conferences on Lung Health, and International AIDS Society conferences. The search terms ‘HIV AND Tuberculosis AND (Viral Load OR CD4+ lymphocyte count OR Mortality) AND Antiretroviral therapy’ were used to identify relevant articles in PubMed and EMBASE. Searches were performed on 29 January 2013 and included original human participant studies published since 1997 (the start of the cART era). Additional articles were identified from reference lists, reviews, and Web of Science citation lists.
H.M.S. and A.V.R. independently reviewed titles and abstracts of original studies retrieved by the search. H.M.S. reviewed full text and references of selected articles. H.M.S. and M.R.P. independently abstracted study data from full reports; discrepancies were resolved by consensus among coauthors.
Studies were included if they reported HIV RNA and/or CD4+ cell count response following cART initiation among antiretroviral treatment-naive HIV-infected adults, stratified by TB treatment status at cART initiation. Studies with 5% or less antiretroviral-experienced patients or patients only previously exposed to a single intrapartum dose of nevirapine were also included. Studies of children younger than 14 years were excluded. No additional exclusion criteria or language restrictions were imposed.
The following information, if available, was abstracted from each article: first author surname; publication year; study dates; geographic location; study design; clinical setting; sample size; number receiving and not receiving TB treatment at cART initiation; if TB treatment was the main exposure of interest; types of TB included; culture confirmation of TB cases; TB site; timing of TB treatment in relation to cART initiation; length of follow-up; proportion antiretroviral-naive; percentage male; mean or median participant age; criteria for cART initiation; cART regimen; baseline median CD4+ cell count and HIV RNA; HIV RNA outcome measure(s); CD4+ cell count outcomes measure(s); covariate adjustment; exclusion criteria; proportion lost-to-follow-up; and how each study handled loss-to-follow-up, mortality, and regimen switching. For this purposes of this review, we abstracted results as presented in the specific studies according to their individual methods and assumptions.
Reported effect estimates over any length of time were abstracted. If only count data of those who experienced an outcome, stratified by TB treatment status, were reported, a risk ratio and 95% confidence interval (CI) were calculated. If a study reported an outcome only graphically, outcome values were visually estimated . Standard error estimates were inferred from reported CIs by [ln(upper limit) − ln(lower limit)]/3.92 . As we aimed to quantify virologic suppression, if a study reported on patients who failed to suppress, this information was converted to obtain data on suppression. For CD4+ cell counts, if two of three of the following measures were reported, we calculated the third measure: mean baseline CD4+ cell count, mean change in CD4+ cell count from baseline, mean absolute CD4+ cell count. We were unable to calculate the missing measures if only median CD4+ cell counts were reported.
For virologic suppression, summarized relative risks (RRs) were calculated using random-effects summarization with unconditional variances and the method of moments estimated between-study variance (τ2) . As several studies reported estimates at multiple time points, we used the estimate closest to the midpoint of each study's follow-up time to get an overall RR for virologic suppression. In addition, to examine short-term and long-term virologic suppression, summary RRs at 1–4 months, 6 months, 11–12 months, and 18–48 months were calculated. The P-values for a standard χ2 homogeneity test statistic were used to assess overall consistency among the effect estimates across studies. τ2 was used to calculate 95% population effects intervals  (wherein 95% of populations are estimated to have their means), opposite effects proportions  (proportion of populations likely to experience an RR below unity), and 95% prediction intervals  (95% of these intervals will cover the true value estimated by a future study). Stratified and random-effects meta-regression analyses were used to calculate stratum-specific summary measures and 95% CIs, along with ratios of the stratum-specific RRs as described by Bassler et al. .
Funnel plots of ln(virologic suppression RR) vs. the inverse-variance weight of studies were visually examined for asymmetry and statistically assessed using methods proposed by Begg  and Egger et al.  and the trim-and-fill method . STATA (version 12; Stata Corporation, College Station, Texas, USA) was used for these analyses.
Nine hundred and ninety unique abstracts were reviewed: 795 from PubMed, 143 from EMBASE, and 52 from conference proceedings (Fig. 1). Of these, 120 full-text articles were selected for review. In total, 18 articles [16–33] and five conference abstracts [34–38] were eligible. Five additional articles met our inclusion criteria: two from reference lists [39,40] and three from Web of Science citation searches [41–43]. One included abstract  was subsequently published as a full article ; only data from the full article were included. Three eligible studies were excluded: one because some patients included in the TB treatment-exposed group had completed TB treatment just prior to cART initiation , and two because they included some early incident TB cases in their TB treatment-exposed group [20,31]. Articles reporting on the same study population, but at differing time points following cART initiation, were retained [26,27,39]. Similarly, we retained both reports of a Tanzanian cohort [22,42].
Study and population characteristics
The 25 final studies provided data on 49 578 PLWH, of which 8826 (18%) were receiving TB treatment at cART initiation. Selected study and population characteristics are displayed in Table 1. All were cohort studies; four reported virologic response, eight reported CD4+ cell count response, and 13 reported both outcomes. Although the majority of studies was based in sub-Saharan Africa, nine included Asian populations [17,23,26,27,29,32,33,38,39] and three were from Europe or North America [19,21,28]. Most publications assessed response to cART, regardless of regimen type, although some reported estimates specific to nevirapine-based [18,26,27,30,39] or efavirenz-based [18,22,25,29,30,42] cART (see Supplemental Digital Content 1, http://links.lww.com/QAD/A406, which provides study-specific details on cART regimens). Although included studies used a variety of cART regimens, nevirapine was often used in combination with stavudine and efavirenz was often used in combination with zidovudine and lamivudine. All studies used cART initiation as the time origin, except one which began at the commencement of cART education and adherence sessions, with most patients starting cART a month or two later . Two studies included women previously exposed to a single intrapartum dose of nevirapine [18,40], and one study included 3% antiretroviral-experienced patients .
Seventeen studies examined TB treatment at cART initiation as the main exposure of interest [18,19,21,23,25–27,29,30,32,33,35,37–39,43,44]. The other eight studies examined TB treatment as a secondary exposure; five aimed to describe general cART outcomes [16,24,28,40,41], and one each examined the primary exposures of timeliness of clinic attendance , β-defensin genomic copy number , and liver enzyme abnormalities . The type of TB being treated varied across studies. Only one study had a subset of bacteriologically confirmed TB cases , whereas others included both confirmed and probable TB cases. One study focused solely on pulmonary TB , and three excluded patients who developed incident TB from the reference group [18,30,35]. Sixteen studies reported detail on the duration of TB treatment at the time of cART initiation (see Table, Supplemental Digital Content 2, http://links.lww.com/QAD/A406, which provides study-specific information on the timing of TB treatment, if available).
Overall loss-to-follow-up was reported by 15 studies and ranged from 0 to 64% (median 10%, interquartile range 7–12%) (see Table, Supplemental Digital Content 3, http://links.lww.com/QAD/A406, which details methods utilized by studies to handle loss-to-follow-up and mortality). Five studies limited their analysis to those who completed follow-up [16,30,35,37,44] and three studies considered those who discontinued cART for a variety of reasons and/or lacked follow-up laboratory data as treatment failures [21,26,27]. Although most studies did not describe how they handled patients who switched cART regimens, one excluded patients who stopped or changed cART during follow-up , three explicitly retained patients who switched [24,30,40], and one did a sensitivity analysis considering those who discontinued stavudine as treatment failures .
All studies included both sexes, with the proportion male ranging from 21 to 92% (median 45%). All patients were at least 14 years of age; mean patient age ranged from 31 to 41 years (median 36). Median baseline CD4+ cell count ranged from 29 to 196 cells/μl (median 94), and baseline HIV RNA ranged from 4.9 to 5.8 log10 copies/ml (median 5.3). One study reported results stratified by baseline CD4+ cell count .
There was heterogeneity in how each study quantified virologic response with respect to the reported effect measure, the cutoff used (50 or 400 copies/ml), and the timing of measurement (see Table, Supplemental Digital Content 4, http://links.lww.com/QAD/A406 for virologic measures as reported by each study). In total, 17 studies reported virologic suppression, either directly or as a measure that allowed conversion into virologic suppression. Times of reported virologic suppression ranged from 1 to 48 months following cART initiation, with some studies reporting multiple time points. Although most studies had overall suppression proportions more than 75%, several observed relatively low suppression. The study with the shortest follow-up time (1 month) reported the lowest overall proportion suppressed (46%) . Manosuthi et al. also reported low suppression among Thai patients: 69% at 6 months , 59% at 33 months , and 51% at 48 months . Three other studies reported suppression rates between 64 and 70% [16,21,32]. However, three of these studies that reported low suppression rates considered those who discontinued cART or lacked follow-up laboratory data as treatment failures [21,26,27].
In total, 15 studies reported RRs for virologic suppression in those receiving vs. not receiving TB treatment at cART initiation (Fig. 2). Overall, the random-effects relative risk (RRRE) for suppression was 0.97 (95% CI 0.92–1.03). When estimates were categorized according to follow-up time, the RRRE for suppression was 1.06 (0.86–1.29) at 1–4 months, 0.91 (0.83–1.00) at 6 months, 0.99 (0.94–1.05) at 11–12 months, and 0.99 (0.77–1.28) at 18–48 months after cART initiation (Table 2). In meta-regression analysis, a lower limit of detection of 50 or 400 copies/ml and type of cART regimen did not substantially influence the summary RRs (see Table, Supplemental Digital Content 5, http://links.lww.com/QAD/A406 for meta-regression results).
Additionally, six studies provided data on cART regimen-specific RRs of virologic suppression (see Figure, Supplemental Digital Content 6, http://links.lww.com/QAD/A406 for forest plot). The three lowest RRs for TB treatment exposure all correspond to three follow-up time points of the nevirapine-based cART arm of Boulle et al..
The funnel plot of overall suppression RRs did not appear asymmetrical because of publication bias or other factors, with Begg's and Egger's P-values for small study effects of 0.26 and 0.71, respectively (see Figure, Supplemental Digital Content 7, for the funnel plot, http://links.lww.com/QAD/A406).
Measures of virologic failure were highly heterogeneous (Supplemental Digital Content 4, http://links.lww.com/QAD/A406), with studies measuring whether patients reached HIV RNA levels of more than 5000 copies/ml , failed to suppress less than 400 copies/ml , rebounded after being previously undetectable or never became undetectable [23,25,26], time to first value at least 400 copies/ml , time to two consecutive values at least 5000 copies/ml , and time to first value more than 500 copies/ml among those who initially suppressed . Six of these studies did not find TB treatment to have a significant effect on virologic failure [17,18,23,25,26,40]. Interestingly, Boulle et al. found an association between TB treatment and virologic failure among those on nevirapine-based cART, but not among patients on efavirenz-based cART in their 2008 study, but reported the opposite finding in their 2010 study . The substantial heterogeneity among virologic failure outcome measures precluded a formal meta-analysis.
CD4+ cell count response to combination antiretroviral therapy
Methods for measuring and reporting CD4+ cell count response were even more heterogeneous than those used for virologic response, due to measurements at different time points and use of a diversity of outcome measures. Eight studies reported mean or median change in CD4+ cell count from baseline, five measured mean or median absolute CD4+ cell count during follow-up, and three reported the difference in CD4+ cell count gain from baseline in patients receiving vs. not receiving TB treatment at cART initiation (Table 3). In addition, some studies defined a specific measure of immunologic success [21,24] or immunologic failure [24,41], and two studies described the CD4+ cell count recovery trajectory [24,43] (see Table, Supplemental Digital Content 8, http://links.lww.com/QAD/A406 for detailed immunologic measures). Two studies limited reporting of CD4+ cell count response to virologically suppressed patients [24,40].
Overall, those receiving TB treatment at cART initiation tended to have lower baseline CD4+ cell counts, greater increases in CD4+ cell count from baseline, and lower absolute CD4+ cell counts during follow-up. Median change in CD4+ cell count from baseline after 6 months of cART (reported by seven studies) ranged from 97 to 200 cells/μl (median 167) among TB treatment-exposed patients and from 89 to 177 cells/μl (median 138) among those not on TB treatment. At 11–12 months, median change in CD4+ cell count from baseline (reported by five studies) ranged from 124 to 234 cells/μl (median 155) among TB treatment-exposed patients and from 104 to 205 cells/μl (median 165) among those not on TB treatment. This corresponds to a differential gain in CD4+ cell count between patients receiving vs. not receiving TB treatment at cART initiation ranging from −10 to 60 more CD4+ cells/μl (median 27) at 6 months and −10 to 29 more CD4+ cells/μl (median 6) at 11–12 months. Heterogeneity among CD4+ cell count response outcomes measures prevented formal meta-analysis.
In this systematic review and meta-analysis of the effect of TB treatment on virologic and CD4+ cell count response to cART, the first meta-analysis of this topic to our knowledge, we found that exposure to TB treatment at cART initiation does not impair virologic suppression or CD4+ cell count gain. The effect on the risk of virologic failure could not be assessed. Our findings indicate that despite concerns about drug–drug interactions, toxicity, high pill burden, and IRIS, TB treatment does not appear to reduce the efficacy of cART in regards to virologic suppression and CD4+ cell count response. The reported outcome measures were, however highly heterogeneous, impeding sound between-study comparisons or meta-analytic summarization for outcome measures other than virologic suppression. Although rigorous meta-analysis methods could not be applied for CD4+ cell response, we did observe similar within-study effects of TB treatment, and the overall impression is that TB treatment exposure does not have a substantial impact on CD4+ cell recovery.
Furthermore, time points reported by individual studies were also heterogeneous. The optimal time point for evaluating the effect of exposure to TB treatment on response to cART is unclear. Follow-up times shorter than 4 months may be too early to accurately describe response to cART, and follow-up times longer than 2 years may underestimate the impact of TB treatment at cART initiation, especially if patients who switch treatments or take second-line therapy are included in the analysis. For the sake of completeness, all reported outcome measures and follow-up times were retained in this review.
The exposure, TB treatment at cART initiation, captured both exposure to active TB disease and exposure to antituberculosis drugs. This combined exposure is useful from a health systems perspective, particularly in low-resource countries, where active TB cannot always be confirmed, especially in PLWH. This is further highlighted by the fact that the included studies used a variety of methods for determining who had active TB and should receive treatment, and no studies were limited to bacteriologically confirmed TB cases and only one study described this subset. Consequently, active TB could have been misclassified and some patients included in this meta-analysis may have received TB treatment even though they did not have TB.
Since being treated for active TB cannot be studied in a randomized controlled trial, all studies included in our review were observational. Consequently, there was much heterogeneity in the duration of TB treatment prior to cART initiation, with some patients on TB therapy for up to 8 months and others beginning TB treatment and cART concurrently. Although the timing of TB treatment in relation to cART initiation is an important factor when evaluating mortality [45–49], it is unclear whether TB treatment timing would influence virologic or CD4+ cell count response. Unfortunately, the included studies did not provide enough information on duration of TB treatment to systematically evaluate its effect on our results. Similarly, a lack of provided data on cART regimen switching during follow-up precluded a systematic evaluation of this factor.
This systematic review and meta-analysis may have been subject to some biases. First, virologic and immunologic response cannot be evaluated in those who have died or were lost-to-follow-up. Loss rates varied widely, ranging from 0 to 64% though most studies lost 12% or less, and studies handled loss-to-follow-up in a variety of ways, which may have influenced their results. Missing patients may systematically differ from those retained in the analysis. If response to cART among lost or deceased patients was differential by TB treatment status, than the results of these studies and our review could have been biased. Second, in eight of 25 studies, TB treatment was not the primary exposure and covariates included in some multivariable models may differ from ideal confounder adjustment for this research question. Third, some bias may have been introduced by estimation methods used when a study did not directly report an outcome measure but provided the necessary data to calculate the desired effect measures [8,9].
In conclusion, this recent comprehensive review of studies assessing the effect of TB treatment on response to cART indicates that TB treatment does not affect virologic suppression or CD4+ cell count gain after cART initiation and we were unable to assess the effect on virologic failure. These findings will allow healthcare workers to be more confident in their clinical decision-making and in their communication to patients about the need to start cART during TB treatment. The heterogeneity in outcome measures posed a challenge to the interpretation and summarization of the virologic and CD4+ cell count response to cART. Between-study comparisons could be greatly facilitated by methodological standardization of outcome measures and their time points in future studies.
The authors are grateful to Mellanye Lackey for her assistance with developing our search strategy, and to Harry Moultrie and Alan Brookhart for their thoughtful comments and guidance.
H.M.S. and A.V.R. devised and designed the study, developed the search strategy, established inclusion criteria, reviewed abstracts, and interpreted data. H.M.S. did all searches of published work, abstracted the study data, was responsible for the statistical analysis, created tables and figures, and drafted the report. M.R.P. double-abstracted the study data, discussed discrepancies and participated in revising the report. J.J.E. and S.N. helped design the analysis, provided expert clinical opinion, and participated in report revision.
M.R.P. was partially supported by NIH training grant 2T32AI070114. J.J.E. and S.N. were partially supported by the University of North Carolina Center for AIDS Research (CFAR), an NIH-funded program (P30 AI50410).
Conflicts of interest
H.M.S., S.N., and A.V.R. have no conflicts of interest. M.R.P. was a summer intern and research assistant at GlaxoSmithKline (GSK) in 2010–2011. J.J.E. is a consultant to GSK, Bristol MyersSquibb, Gilead, Merck, and Janssen, and an investigator on clinical research studies at UNC Chapel Hill supported by GSK.
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