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Mortality in the First 3 Months on Antiretroviral Therapy Among HIV-Positive Adults in Low- and Middle-income Countries: A Meta-analysis

Brennan, Alana T. MPH*,†,‡,§; Long, Lawrence BBusSci, MCom; Useem, Johanna MPH; Garrison, Lindsey MPH§; Fox, Matthew P. MPH, DSc*,†,‡,§

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: September 1, 2016 - Volume 73 - Issue 1 - p 1-10
doi: 10.1097/QAI.0000000000001112



Two-third of the world's HIV-infected people live in sub-Saharan Africa, and more than 1.5 million of them die annually.1 The 2004 rapid scale-up of antiretroviral therapy (ART) that expanded throughout low- to middle-income countries (LMICs) using a large-scale public health approach has been effective in getting many HIV-positive patients on treatment, substantially decreasing the absolute number of people dying of AIDS-related illnesses.2–5 Between 2005 and 2013, AIDS-related deaths decreased by 35%,1 and 54% of the decrease occurred between 2011 and 2014, with variation by region ranging from 27% in the Pacific to 54% in the Caribbean.1

Despite the decrease in mortality in LMICs, early mortality remains very high. A previous study that included countries from sub-Saharan Africa estimated mortality in the first 12 months on ART between 8% and 26%, with roughly 60% of those deaths occurring in the first few months as a result of patients presenting for care with advanced HIV disease.2 A recent meta-analysis that expanded geographically to include Asia and the Americas estimated 12-month mortality at 17% for sub-Saharan Africa, 11% for Asia, and 7% for the Americas.6 While 12 months is the most commonly reported period, studies reporting mortality over time on treatment in the first year suggest that the first 3 months is when a large proportion of this early mortality is occurring and is therefore a more appropriate indicator of whether increasing treatment CD4 thresholds is leading to earlier treatment and better outcomes.2,7

In late 2009, to improve treatment outcomes among HIV-positive patients, the World Health Organization (WHO) increased CD4 count eligibility threshold from <200 cells per microliter8 to <350 cells per microliter9 and again to <500 cells per microliter in 2013.10 More recently, September 2015, they recommended initiating everyone regardless of CD4 count—universal “test-and-treat” model of care—which has been shown through mathematical modeling as a strategy that could lead to steep reductions in HIV incidence and reducing HIV-related morbidity and mortality by getting people on treatment at an earlier stage of their disease.11–19 Over time, although not significant, the median CD4 count at ART initiation in LMICs has slowly increased, likely reflecting increased early testing and the changing policy on CD4 eligibility.20 The objective of our study was to systematically review observational cohort data on early mortality (defined as within 3 months on treatment) in LMICs. Our main objective was to determine whether early mortality was declining in conjunction with WHO policy changes, to inform the current treatment guidelines which call for treatment for all, regardless of CD4 count. We also assessed early mortality post-ART initiation in 3 different regions and assessed CD4 count at ART initiation as a risk factor for mortality.


Search Strategy and Selection Criteria

We searched the databases PubMed, Web of Science (including Medline), Excerpta Medica Abstract Journals (EMBASE), International AIDS Society (IAS) abstract archives, and AIDS Conference abstract archives. We could not search the Conference on Retroviruses and Opportunistic Infections (CROI), as the archives at the time of this search were not available. We searched for articles published between January 01, 2003 (1 year before the roll out of ART in LMIC8) and October 31, 2014, and re-ran the search in PubMed only from November 01, 2014, to April 01, 2016. Our search key words can be found in Table S1, Supplemental Digital Content, We limited the search to human studies and articles published in English. A total of 2462 potentially relevant citations were identified and 1849 remained after de-duplication. Two reviewers (H.U. and L.G.) screened titles and abstracts to capture potentially relevant studies and one reviewer (M.P.F.) resolved any discrepancies between them. Studies were included if they met the following criteria: (1) observational studies, (2) conducted in LMIC,8 (3) age of participants was ≥15, and (4) researchers had reported at least on average 3 months of follow-up. Additional data were not obtained from study authors.

Data Extraction

The primary objective of this study was to measure mortality within 3 months post-ART initiation. The defined regions were LMIC in sub-Saharan Africa, Asia, and the Caribbean/Latin America. For each study, when possible, we extracted: year published, region, country, dates enrollment started and ended, total N in each cohort, number of deaths in the first 3 months on ART, percentage of females, age at ART initiation, and CD4 count at ART initiation. We also collected data on the percentage of patients who died, were loss to follow-up, if active tracing of patients lost to follow-up occurred, and if clinic level data were linked to a death registry.

Data Analysis

We extracted data on the number of deaths in individual studies, if available, and total number of subjects to calculate simple proportions and corresponding 95% confidence intervals (CIs). Most studies that used Kaplan–Meier methods did not summarize the number of deaths and the number in the risk set at each time point, so this was estimated based on the proportion of deaths at 3 months identified using the Kaplan–Meier curve multiplied by the total number of study subjects.

Meta-analyses were performed to estimate early mortality first overall, then stratified by region, year study enrollment ended (<2010 and ≥2010), CD4 count at ART initiation (categorized as <100, 100–200, and ≥200 cells/μL) and whether studies traced patients lost to follow-up. We used metaregression to assess the linearly effect of time on mortality by regressing the estimates of 3-month mortality on the year study enrollment ended as a continuous variable and binary (<2010 and ≥2010). Heterogeneity between the studies was examined using Cochran's Q and the I2 statistic.21 Random effects models were used to estimate all combined mortality rates and corresponding 95% CIs, using standard methods because there was evidence of high heterogeneity between studies.22

Sensitivity Analysis

As our mortality estimates are most likely underestimated because of high rates of loss to follow-up in LMICs, we conducted a simple sensitivity analysis. For studies that reported rates of loss to follow-up, we assumed that 46%, based on estimates from a meta-analysis,23 of patients lost from care had died and recalculate 3-month mortality.

Publication Bias

An analysis of publication bias was also performed using a funnel plot and Egger's linear regression test.24 We used a confidence level of 0.10 to accommodate the low power of the Egger's test to detect a departure from the null hypothesis of no bias (symmetrical funnel plot).


Study Characteristics

Of 1849 articles, 240 studies received full text review, of which 58 met our inclusion criteria (Figure S1, Supplemental Digital Content, Of 58 included studies, 43 (74.1%) were from sub-Saharan Africa, 13 (22.4%) from Asia, and 2 (3.4%) from Caribbean/Latin America (Table 1). Most studies (n = 36) were published after 2010, with the largest number in 2011 (n = 11). Cohort size ranged from 142 to 108,079 persons. The proportion of females ranged from 22% to 78%. Fifty studies (86%) reported a median CD4 count ranging from 11 to 280 cells per microliter. Fifty-three studies (91.4%) reported loss to follow-up, which overall ranged from 0% to 41%, with sub-Saharan Africa reporting the highest and Asia with the lowest rates of lost to follow-up.

Characteristics of Included Studies (n = 58) and 3-Month Mortality Rates (Reported and Adjusted for 46% Death Among Patients Lost From Care) Post-ART Initiation for Each Study, Region, and Combined Overall
Characteristics of Included Studies (n = 58) and 3-Month Mortality Rates (Reported and Adjusted for 46% Death Among Patients Lost From Care) Post-ART Initiation for Each Study, Region, and Combined Overall
Characteristics of Included Studies (n = 58) and 3-Month Mortality Rates (Reported and Adjusted for 46% Death Among Patients Lost From Care) Post-ART Initiation for Each Study, Region, and Combined Overall

Early Mortality

All estimates are summary pooled random effects estimates (heterogeneity between individual study estimates I2 = 99.5%, P < 0.0001) of early (3-month post-ART initiation) mortality. The overall summary estimate was 6.0% (95% CI: 5.4 to 6.6) (Table 1), but with variation by region with sub-Saharan Africa, Carribean/Latin America, and Asia at 6.3% (95% CI: 5.5 to 7.0), 6.0% (95% CI: 5.4 to 6.6), and 5.3% (95% CI: 3.8 to 6.8), respectively (Table 1). When we recalculated mortality, assuming 46% of patients who were lost to follow-up had died; the overall estimate increased to 10.6% (95% CI: 9.4 to 11.8), almost doubling the estimates in Asia and sub-Saharan Africa.

Although nonsignificant, the pooled estimate show a decline in mortality when comparing studies whose enrollment of patients ended <2010 (7.0%; 95% CI: 6.0 to 8.0) to ≥2010 (4.0%; 95% CI: 3.0 to 5.0) (Figs. 1, 2). Metaregression results confirmed this, showing a nonsignificant decrease of 2.1% (95% CI: −4.4 to 0.2) when comparing <2010 with ≥2010. When regressing mortality on year enrollment of patients ended as a continuous variable, we saw a small, nonsignificant decrease of 0.2% (95% CI: −0.7 to 0.3) in mortality with each passing year. Studies reporting a higher CD4 count (≥200 cells/μL) at ART initiation had lower early mortality (3.0%; 95% CI: 2.0 to 4.0) compared with the studies reporting a lower CD4 count (100–200 cells/μL—6.0%; 95% CI: 5.0 to 7.0 and <100 cells/μL—7.0%; 95% CI: 5.0 to 9.0) at ART initiation. We saw no difference in estimates between studies that report active tracing and/or linkage to the death registry compared with those that did not, 6.0% (95% CI: 5.0 to 7.0) and 5.0 (95% CI: 4.0 to 6.0), respectively.

Forest plot of estimates of mortality at 3 months by individual studies and pooled by year enrollment of patients ended (<2010 vs. ≥2010).
Forest plot of estimates of mortality at 3 months by individual studies and pooled by CD4 count at ART initiation.

Publication Bias

The funnel plot and significant Egger's test (P = 0.012) suggest that there is evidence of asymmetry (see Figure S2, Supplemental Digital Content, Although the presence of publication bias is a common explanation to an asymmetric funnel plot, data presented here are observational data without any intervention, so the funnel plot asymmetry could also be due to heterogeneity in the data.24


The overall estimate of early mortality in our study was 6.0%, consistent with previous findings.82 Our results suggest a decline in early mortality when comparing pooled estimates before 2010 with during or after 2010. The lack of a larger effect could be due to lack of follow-up time in studies included to evaluate the impact of early mortality after WHO guideline changes but is also possibly due to the fact that many countries included in the study did not revise their national policies and provide implementation training and support immediately after the publication of WHO guidelines. As such, it would be important to repeat this meta-analysis in the next few years to better illustrate the effects of the newer guidelines. It could also be related to the fact that increasing eligibility thresholds alone over the past 5 years were not enough incentive to get people into care at an earlier stage of their disease and that complex barriers to accessing HIV care and treatment, such as rigid clinic policies, poor service provision, stock-outs of supplies, stigma and discrimination, distance to health facilities, and poverty, still need to be addressed.83 A previous meta-analysis showing that from 2002 to 2013 CD4 count at ART initiation, a good indicator in how early people are accessing care for HIV, did not increase significantly as eligibility thresholds changed,20 further providing evidence to support this conclusion.

Our results also showed that, excluding the Carribean/Latin America where summary estimates were based only on 2 studies, mortality in the first 3 months on ART were comparable in sub-Saharan Africa and Asia at around 6%. When estimates were adjusted for death among patients lost to follow-up (assumed at 46%), estimates of early mortality almost doubled in Asia and sub-Saharan Africa. Previous studies have shown that estimates of mortality in LMICs are underestimated by 30%–50% because of potentially undercounting deaths, particularly among those lost to follow-up.82 Although our study showed no difference between studies that did or did not actively trace patients or link to the death registry, linking to vital registration systems, whenever possible, and active tracing of patients loss to follow-up could result in more valid estimates of mortality and help those patients loss to follow-up return to care to decrease their risk of death.84,85

Our results also showed that patients with a CD4 count <200 cells per microliter at ART initiation were at higher risk of death compared with those with a CD4 count ≥200 cells per microliter. Although we are not surprised by these results, it confirms the importance of enrolling patients in care earlier, as our results show that mortality is 50% lower in cohorts with a median CD4 count ≥200 cells per microliter compared with <200 cells per microliter. In addition, although CD4 at start of ART has increased slightly over time, the change in the proportion of patients presenting late to care has been far less noticeable.86

Our results should be considered alongside their limitations. First, like any systematic review, there is the possibility of incomplete retrieval or abstraction of data; however, we used 3 independent reviewers to try and best address this. Second, we did not obtain raw data from study investigators for pooled estimation of early mortality; however, we used only those studies that reported appropriate simple proportions or displayed Kaplan–Meier curves clearly. Third, there was also substantial heterogeneity and/or reporting bias among the studies. Despite this heterogeneity, we felt that it was important to pool the existing data to estimate mortality probability at 3-month post-ART initiation, as these data provide a more robust estimate than any single study alone. Fourth, our sensitivity analysis used rates of loss to follow-up over the entire follow-up period and not in the first 3 months on ART, as such our estimates of mortality adjusted for 46% mortality among those lost could be inaccurate.


Despite progress in making ART available to millions of HIV-infected persons in LMICs, early mortality has not declined. This is likely due to the fact that patients in these settings continue to start treatment at a considerably advanced stage of disease.2 To put this in a more globally context, when comparing rates of mortality among HIV patients on ART in LMICs to high-income countries, research has shown that mortality rates fall substantially over the first few months of ART in LMICs, and approaches that seen in Western Europe and North America after 4–6 months on ART.2 To reduce early HIV-related mortality at the population level, intensified efforts to increase demand for ART through active testing and facilitated referral should be a priority. Continued financial investments by multinational partners and the implementation of creative interventions to mitigate multidimensional complex barriers of accessing care and treatment for HIV are needed.


1. UNAIDS. The Gab Report. 2010. Available at: Accessed May 1, 2016.
2. Braitstein P, Brinkhof MW, Dabis F, et al. Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries. Lancet. 2006;367:817–824.
3. Palella FJ Jr, Delaney KM, Moorman AC, et al. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. HIV Outpatient Study Investigators. N Engl J Med. 1998;338:853–860.
4. Severe P, Leger P, Charles M, et al. Antiretroviral therapy in a thousand patients with AIDS in Haiti. N Engl J Med. 2005;353:2325–2334.
5. Stringer JS, Zulu I, Levy J, et al. Rapid scale-up of antiretroviral therapy at primary care sites in Zambia: feasibility and early outcomes. JAMA. 2006;296:782–793.
6. Gupta A, Nadkarni G, Yang WT, et al. Early mortality in adults initiating antiretroviral therapy (ART) in low- and middle-income countries (LMIC): a systematic review and meta-analysis. PLoS One. 2011;6:e28691.
7. 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.
8. World Health Organization. Scaling up Antiretroviral Therapy in Resource-limited Settings: Treatment Guidelines for a Public Health Approach (2003 Revision). Geneva: WHO; 2004. Available at: Accessed May 1, 2016.
9. World Health Organization. Antiretroviral Therapy for HIV Infection in Adults and Adolescents: Recommendations for a Public Health Approach—2010 Revision. 2010. Available at: Accessed May 1, 2016.
10. Consolidated Guidelines on the Use of Antiretroviral Drugs for Treating and Preventing HIV Infection Recommendations for a Public Health Approach. 2013. Available at: Accessed May 1, 2016.
11. Guideline on When to Start Antiretroviral Therapy and on Pre-exposure Prophylaxis fof HIV. WHO; 2015. Available at: Accessed May 1, 2016.
12. Granich RM, Gilks CF, Dye C, et al. Universal voluntary HIV testing with immediate antiretroviral therapy as a strategy for elimination of HIV transmission: a mathematical model. Lancet. 2009;373:48–57.
13. Dieffenbach CW, Fauci AS. Universal voluntary testing and treatment for prevention of HIV transmission. JAMA. 2009;301:2380–2382.
14. Dodd PJ, Garnett GP, Hallett TB. Examining the promise of HIV elimination by 'test and treat' in hyperendemic settings. AIDS. 2010;24:729–735.
15. Garnett GP, Baggaley RF. Treating our way out of the HIV pandemic: could we would we should we? Lancet. 2009;373:9–11.
16. Montaner JS, Hogg R, Wood E, et al. The case for expanding access to highly active antiretroviral therapy to curb the growth of the HIV epidemic. Lancet. 2006;368:531–536.
17. Blower S, Ma L, Farmer P, et al. Predicting the impact of antiretrovirals in resource-poor settings: preventing HIV infections whilst controlling drug resistance. Curr Drug Targets Infect Disord. 2003;3:345–353.
18. Baggaley RF, Fraser C. Modelling sexual transmission of HIV: testing the assumptions, validating the predictions. Curr Opin HIV AIDS. 2010;5:269–276.
19. Zachariah R, Harries AD, Philips M, et al. Antiretroviral therapy for HIV prevention: many concerns and challenges, but are there ways forward in sub-Saharan Africa? Trans R Soc Trop Med Hyg. 2010;104:387–391.
20. Siedner MJ, Ng CK, Bassett IV, et al. Trends in CD4 count at presentation to care and treatment initiation in sub-Saharan Africa, 2002-2013: a meta-analysis. Clin Infect Dis. 2015;60:1120–1127.
21. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21:1539–1558.
22. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7:177–188.
23. Brinkhof MW, Pujades-Rodriguez M, Egger M. Mortality of patients lost to follow-up in antiretroviral treatment programmes in resource-limited settings: systematic review and meta-analysis. PloS One. 2009;4:e5790.
24. Sterne JA, Sutton AJ, Ioannidis JP, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ. 2011;343:d4002.
25. Zhou J, Kumarasamy N; TREAT Asia HIV Observational Database. Predicting short-term disease progression among HIV-infected patients in Asia and the Pacific region: preliminary results from the TREAT Asia HIV Observational Database (TAHOD). HIV Med. 2005;6:216–223.
26. Ferradini L, Laureillard D, Prak N, et al. Positive outcomes of HAART at 24 months in HIV-infected patients in Cambodia. AIDS. 2007;21:2293–2301.
27. Dou Z, Xu J, Jiao JH, et al. Gender difference in 2-year mortality and immunological response to ART in an HIV-infected Chinese population, 2006-2008. PLoS One. 2011;6:e22707.
28. van Griensven J, Thai S. Predictors of immune recovery and the association with late mortality while on antiretroviral treatment in Cambodia. Trans R Soc Trop Med Hyg. 2011;105:694–703.
29. Argemi X, Dara S, You S, et al. Impact of malnutrition and social determinants on survival of HIV-infected adults starting antiretroviral therapy in resource-limited settings. AIDS. 2012;26:1161–1166.
30. Baqi S, Abro AG, Salahuddin N, et al. Four years of experience with antiretroviral therapy in adult patients in Karachi, Sindh, Pakistan. Int Health. 2012;4:260–267.
31. Alvarez-Uria G, Pakam R, Midde M, et al. Factors associated with attrition, mortality, and loss to follow up after antiretroviral therapy initiation: data from an HIV cohort study in India. Glob Health Action. 2013;6:21682.
    32. Bastard M, Soulinphumy K, Phimmasone P, et al. Women experience a better long-term immune recovery and a better survival on HAART in Lao People's Democratic Republic. BMC Infect Dis. 2013;13:27.
    33. Bhatta L, Klouman E, Deuba K, et al. Survival on antiretroviral treatment among adult HIV-infected patients in Nepal: a retrospective cohort study in Far-western region, 2006-2011. BMC Infect Dis. 2013;13:604.
    34. Liao L, Xing H, Su B, et al. Impact of HIV drug resistance on virologic and immunologic failure and mortality in a cohort of patients on antiretroviral therapy in China. AIDS. 2013;27:1815–1824.
    35. Allam RR, Murhekar MV, Bhatnagar T, et al. Survival probability and predictors of mortality and retention in care among patients enrolled for first-line antiretroviral therapy, Andhra Pradesh, India, 2008-2011. Trans R Soc Trop Med Hyg. 2014;108:198–205.
    36. Alvarez-Uria G, Pakam R, Midde M, et al. Incidence and mortality of tuberculosis before and after initiation of antiretroviral therapy: an HIV cohort study in India. J Int AIDS Soc. 2014;17:19251.
      37. Huang P, Tan J, Ma W, et al. Long-Term Effectiveness of antiretroviral therapy in China: an observational cohort study from 2003-2014. Int J Environ Res Public Health. 2015;12:8762–8772.
        38. Rebick G, Charles M, Leger P, et al. Antiretroviral therapy in adults and adolescents with AIDS in Haiti from 2003-2007: a cohort analysis. Paper presented at: International AIDS Conference; August 3–8, 2008; Mexico City, Mexico.
          39. Carriquiry G, Fink V, Koethe JR, et al. Mortality and loss to follow-up among HIV-infected persons on long-term antiretroviral therapy in Latin America and the Caribbean. J Int AIDS Soc. 2015;18:20016. eCollection 2015.
            40. Jerene D, Naess A, Lindtjørn B. Antiretroviral therapy at a district hospital in Ethiopia prevents death and tuberculosis in a cohort of HIV patients. AIDS Res Ther. 2006;3:10.
              41. Zachariah R, Fitzgerald M, Massaquoi M, et al. Risk factors for high early mortality in patients on antiretroviral treatment in a rural district of Malawi. AIDS. 2006;20:2355–2360.
              42. Chen SC, Yu JK, Harries AD, et al. Increased mortality of male adults with AIDS related to poor compliance to antiretroviral therapy in Malawi. Trop Med Int Health. 2008;13:513–519.
              43. Fairall LR, Bachmann MO, Louwagie GM, et al. Effectiveness of antiretroviral treatment in a South African program: a cohort study. Arch Intern Med. 2008;168:86–93.
              44. Geng EH, Emenyonu N, Bwana MB, et al. Sampling-based approach to determining outcomes of patients lost to follow-up in antiretroviral therapy scale-up programs in Africa. JAMA. 2008;300:506–507.
              45. Johannessen A, Naman E, Ngowi BJ, et al. Predictors of mortality in HIV-infected patients starting antiretroviral therapy in a rural hospital in Tanzania. BMC Infect Dis. 2008;8:52.
              46. Keiser O, Orrell C, Egger M, et al. Public-health and individual approaches to antiretroviral therapy: township South Africa and Switzerland compared. Plos Med. 2008;5:e148.
              47. Mulenga LB, Kruse G, Lakhi S, et al. Baseline renal insufficiency and risk of death among HIV-infected adults on antiretroviral therapy in Lusaka, Zambia. AIDS. 2008;22:1821–1827.
              48. Castelnuovo B, Manabe YC, Kiragga A, et al. Cause-specific mortality and the contribution of immune reconstitution inflammatory syndrome in the first 3 years after antiretroviral therapy initiation in an urban African cohort. Clin Infect Dis. 2009;49:965–972.
              49. Chung MH, Drake AL, Richardson BA, et al. Impact of prior HAART use on clinical outcomes in a large Kenyan HIV treatment program. Curr HIV Res. 2009;7:441–446.
              50. Zachariah R, Harries K, Moses M, et al. Very early mortality in patients starting antiretroviral treatment at primary health centres in rural Malawi. Trop Med Int Health. 2009;14:713–721.
              51. Alibhai A, Kipp W, Saunders LD, et al. Gender-related mortality for HIV-infected patients on highly active antiretroviral therapy (HAART) in rural Uganda. Int J Womens Health. 2010;2:45–52.
                52. Chan AK, Mateyu G, Jahn A, et al. Outcome assessment of decentralization of antiretroviral therapy provision in a rural district of Malawi using an integrated primary care model. Trop Med Int Health. 2010;15(suppl 1):90–97.
                53. Chi BH, Mwango A, Giganti M, et al. Early clinical and programmatic outcomes with tenofovir-based antiretroviral therapy in Zambia. J Acquir Immune Defic Syndr. 2010;54:63–70.
                54. Ford N, Kranzer K, Hilderbrand K, et al. Early initiation of antiretroviral therapy and associated reduction in mortality, morbidity and defaulting in a nurse-managed, community cohort in Lesotho. AIDS. 2010;24:2645–2650.
                55. May M, Boulle A, Phiri S, et al. Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes. Lancet. 2010;376:449–457.
                56. Taylor-Smith K, Tweya H, Harries A, et al. Gender differences in retention and survival on antiretroviral therapy of HIV-1 infected adults in Malawi. Malawi Med J. 2010;22:49–56.
                  57. Auld AF, Mbofana F, Shiraishi RW, et al. Four-year treatment outcomes of adult patients enrolled in Mozambique's rapidly expanding antiretroviral therapy program. PLoS One. 2011;6:e18453.
                  58. Bakanda C, Birungi J, Mwesigwa R, et al. Association of aging and survival in a large HIV-infected cohort on antiretroviral therapy. AIDS. 2011;25:701–705.
                  59. Birbeck GL, Kvalsund MP, Byers PA, et al. Neuropsychiatric and socioeconomic status impact antiretroviral adherence and mortality in rural Zambia. Am J Trop Med Hyg. 2011;85:782–789.
                  60. Hawkins C, Chalamilla G, Okuma J, et al. Sex differences in antiretroviral treatment outcomes among HIV-infected adults in an urban Tanzanian setting. AIDS. 2011;25:1189–1197.
                  61. Hoffmann CJ, Fielding KL, Johnston V, et al. Changing predictors of mortality over time from cART start: implications for care. J Acquir Immune Defic Syndr. 2011;58:269–276.
                  62. Koethe JR, Blevins M, Nyirenda C, et al. Nutrition and inflammation serum biomarkers are associated with 12-week mortality among malnourished adults initiating antiretroviral therapy in Zambia. J Int AIDS Soc. 2011;14:19.
                    63. Mills EJ, Bakanda C, Birungi J, et al. Male gender predicts mortality in a large cohort of patients receiving antiretroviral therapy in Uganda. J Int AIDS Soc. 2011;14:52.
                      64. Negin J, van Lettow M, Semba M, et al. Anti-retroviral treatment outcomes among older adults in Zomba district, Malawi. PLos One. 2011;6:e26546.
                      65. Peterson I, Togun O, de Silva T, et al. Mortality and immunovirological outcomes on antiretroviral therapy in HIV-1 and HIV-2-infected individuals in the Gambia. AIDS. 2011;25:2167–2175.
                      66. Biadgilign S, Reda AA, Digaffe T. Predictors of mortality among HIV infected patients taking antiretroviral treatment in Ethiopia: a retrospective cohort study. AIDS Res Ther. 2012;9:15.
                        67. Greig J, Casas EC, O'Brien DP, et al. Association between older age and adverse outcomes on antiretroviral therapy: a cohort analysis of programme data from nine countries. AIDS. 2012;26(suppl 1):S31–S37.
                        68. Maman D, Glynn JR, Crampin AC, et al. Very early anthropometric changes after antiretroviral therapy predict subsequent survival, in karonga, Malawi. Open AIDS J. 2012;6:36–44.
                          69. Somi G, Keogh SC, Todd J, et al. Low mortality risk but high loss to follow-up among patients in the Tanzanian national HIV care and treatment programme. Trop Med Int Health. 2012;17:497–506.
                          70. Weigel R, Estill J, Egger M, et al. Mortality and loss to follow-up in the first year of ART: Malawi national ART programme. AIDS. 2012;26:365–373.
                          71. Abo Y, Minga A, Menan H, et al. Incidence of serious morbidity in HIV-infected adults on antiretroviral therapy in a West African care centre, 2003-2008. BMC Infect Dis. 2013;13:607.
                          72. Estill J, Egger M, Johnson LF, et al. Monitoring of antiretroviral therapy and mortality in HIV programmes in Malawi, South Africa and Zambia: mathematical modelling study. PLoS One. 2013;8:e57611.
                          73. Otwombe KN, Laher F, Tutu-Gxashe T, et al. The effect of a Maturing antiretroviral program on early mortality for patients with advanced immune-Suppression in Soweto, South Africa. PLoS One. 2013;8:e81538.
                          74. Poka-Mayap V, Pefura-Yone EW, Kengne AP, et al. Mortality and its determinants among patients infected with HIV-1 on antiretroviral therapy in a referral centre in Yaounde, Cameroon: a retrospective cohort study. BMJ Open. 2013;3:e003210. Published online 2013 July 12.
                            75. Stringer JS, Mwango AJ, Giganti MJ, et al. Effectiveness of generic and proprietary first-line anti-retroviral regimens in a primary health care setting in Lusaka, Zambia: a cohort study. Int J Epidemiol. 2012;41:448–459.
                            76. Fatti G, Mothibi E, Meintjes G, et al. Antiretroviral treatment outcomes amongst older adults in a large multicentre cohort in South Africa. PLoS One. 2014;9:e100273.
                            77. Lessells RJ, Mutevedzi PC, Iwuji CC, et al. Reduction in early mortality on antiretroviral therapy for adults in rural South Africa since change in CD4+ cell count eligibility criteria. J Acquir Immune Defic Syndr. 2014;65:e17–e24.
                            78. Mugisha V, Teasdale CA, Wang C, et al. Determinants of mortality and loss to follow-up among adults enrolled in HIV care services in Rwanda. PLoS One. 2014;9:e85774. Published online 2014 January 15.
                            79. Tadesse K, Haile F, Hiruy N. Predictors of mortality among patients enrolled on antiretroviral therapy in Aksum hospital, Northern Ethiopia: a retrospective cohort study. PLoS One. 2014;9:e87392.
                            80. Geng EH, Odeny TA, Lyamuya RE, et al. Estimation of Mortality among HIV-infected people on antiretroviral therapy treatment in east Africa: a sampling based approach in an observational, multisite, cohort study. Lancet HIV. 2015;2:e107–e116.
                            81. Melaku Z, Lamb MR, Wang C, et al. Characteristics and outcomes of adult Ethiopian patients enrolled in HIV care and treatment: a multi-clinic observational study. BMC Public Health. 2015;15:462.
                            82. Murray CJ, Ortblad KF, Guinovart C, et al. Global, regional, and national incidence and mortality for HIV, tuberculosis, and malaria during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384:1005–1070.
                            83. Layer EH, Kennedy CE, Beckham SW, et al. Multi-level factors affecting entry into and engagement in the HIV continuum of care in Iringa, Tanzania. PLoS One. 2014;9:e104961.
                            84. Brinkhof MW, Spycher BD, Yiannoutsos C, et al. Adjusting mortality for loss to follow-up: analysis of five ART programmes in sub-Saharan Africa. PLoS One. 2010;5:e14149.
                            85. Boulle A, Schomaker M, May MT, et al. Mortality in patients with HIV-1 infection starting antiretroviral therapy in South Africa, Europe, or North America: a collaborative analysis of prospective studies. Plos Med. 2014;11:e1001718.
                            86. Avila D, Althoff KN, Mugglin C, et al. Immunodeficiency at the start of combination antiretroviral therapy in low-, middle-, and high-income countries. Al J Acquir Immune Defic Syndr. 2014;65:e8–e16.

                            early mortality; resource-limited setting; HIV; antiretroviral therapy; meta-analysis

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