Abstract
Objectives
To report predictors of outcomes of second-line ART for HIV treatment in a resource-limited setting.
Methods
All adult ART-naïve patients who initiated standard first-line treatment between April 2004-February 2012 at four public-sector health facilities in Johannesburg, South Africa, experienced virologic failure, and initiated standard second-line therapy were included. We assessed predictors of attrition (death and loss to follow-up [≥3 months late for a scheduled visit]) using Cox proportional hazards regression and predictors of virologic suppression (viral load <400 copies/ml ≥3 months after switch) using modified Poisson regression with robust error estimation at one year and ever after second-line ART initiation.
Results
1,236 patients switched to second-line a median (IQR) of 1.9 (0.9–4.6) months after first-line virologic failure. 12.6% and 45.3% of patients were no longer in care at one-year and at the end of follow-up, respectively. Patients with low CD4 counts (<50 vs. ≥200, aHR: 1.85; 95% CI: 1.03–3.32) at second-line switch were at greater risk for attrition by the end of follow-up. 74.9% of patients suppressed by one-year and 85.3% had ever suppressed by the end of follow-up.
Conclusions
Patients with poor immune status at switch to second-line ART were at greater risk of attrition and were less likely to suppress. Additional adherence support after switch may improve outcomes.
Keywords: HIV, antiretroviral therapy, second-line, death, loss to follow-up, virologic suppression
Introduction
The South African public-sector health system supports the world’s largest antiretroviral therapy program (ART) with an estimated 7 million HIV-infected and 3.1 million on ART.(1,2) Estimates from WHO suggest that among patients on ART in low-and middle income settings, approximately 95% are on non-nucleoside reverse transcriptase inhibitor (NNRTI) based first-line regimens and estimates of first-line treatment failure range between 6% and 32%.(3–5) Recently published estimates from a mathematical model note that in South Africa alone there were approximately 128,000 individuals on second-line ART in 2014. By 2020, that number is expected to expand to approximately 450,000 and to >900,000 by 2030.(6) Thus, as treatment programs across Southern Africa continue to grow, the absolute number of patients requiring second-line regimens will continue to increase.
Numerous programs in resource-limited settings have demonstrated successful treatment outcomes of first-line therapy. Fewer, however, have described treatment outcomes of second-line therapy, with evidence mainly restricted to smaller cohorts with limited information on efficacy and durability of second-line ART beyond one-year.(7–12) Nonetheless, programs that have reported outcomes have shown mixed results. The mortality rate after initiation of second-line treatment has been fairly low, with estimates of approximately 4% to 5%, but virologic failure estimates have remained higher, with many programs reporting second-line failure rates of more than 15%.(8–14)
Given the increasing need for second-line therapy in resource-limited settings, it is critical to assess the effectiveness of such treatment now that ART programs are more experienced. As poor response to treatment is likely to put patients at increased risk for mortality, and may increase risk of further transmission, understanding why certain patients fail to respond to treatment and how that impacts their risk for death and loss to follow-up is of great importance. Thus, we update our previous work, which was conducted at a single public-sector HIV treatment facility under more stringent ART initiation criteria, and report predictors of short- and long-term outcomes of more than 1,200 HIV-infected patients receiving second-line therapy at four public-sector HIV treatment facilities across Johannesburg, South Africa.(12)
Methods
Study Sites
Data from four public-sector facilities located across Johannesburg were used for this analysis. Since 2004, when ART provision began in the public-sector, these clinics have initiated over 40,000 patients onto ART. All demographic and clinical information, including data on drug regimens and dates of regimen changes as well as co-infections and comorbidities, at each of these sites is captured in an electronic medical record, TherapyEdge-HIV™, during the patient encounter. This system is integrated with the National Health Laboratory Service (NHLS) and all laboratory data, including CD4 counts and viral loads, are downloaded directly into the electronic record.(15)
All public-sector facilities follow the guidelines of the South African National Department of Health. From April 2004 to August 2011, patients were initiated onto first-line ART when their CD4 count fell below 200 cells/mm3 or when a WHO Stage IV condition was present.(16,17) Patients presenting for care between August 2011 and December 2014 were initiated when their CD4 count fell below 350 cells/mm3.(18)
Second-line treatment is available for patients who fail first-line ART. Clinics follow the algorithm laid out by the guidelines which call for switch to a protease-inhibitor based second-line regimen after two consecutive failing viral loads (viral load >1000 copies/ml).(17)
Study Population
We conducted a retrospective cohort analysis using routinely collected data. All ART-naïve, adult (≥18 years old) patients who initiated a standard first-line ART regimen between April 2004 and February 2012, experienced virologic failure, and then initiated a standard second-line ART regimen within one year of failure were included. Patients who initiated second-line ART during pregnancy or those who were switched to second-line without evidence of virologic failure were excluded.
Study Variables
Standard ART regimens were defined based on national ART guidelines in use during the period of analysis. First-line ART was defined as stavudine (d4T), zidovudine (AZT), or tenofovir (TDF), with lamivudine (3TC) and either nevirapine (NVP) or efavirenz (EFV). Patients on TDF could also have received emtricitabine (FTC) instead of 3TC.(16,17) Standard second-line ART was defined as AZT with lopinavir-ritonavir (LPVr) and either 3TC or didanosine (ddI) or TDF with LPVr and either 3TC or FTC.(16,17)
Under the 2004 guidelines, viral load testing was conducted at ART initiation and then every 6 months thereafter.(16) In 2010, the monitoring schedule was shifted to 6 months, 1 year and then yearly thereafter.(17) However, patients who experience an elevated viral load should have a repeat viral load test conducted 3 months later. Thus, we defined virologic failure as two consecutive failing viral loads (>1000 copies/ml) between two weeks and six months apart at least four months after ART initiation.
Clinical characteristics at second-line initiation, including body mass index (BMI), anaemia, CD4 count and viral load, were defined as the value closest to the date of second-line initiation up to 7 days after the date of switch. WHO standards were used to define anaemia as severe (Hb <8 g/dL), moderate (Hb 8–10 g/dL), mild (males: Hb 11–12 g/dL; females: Hb 11–11.9 g/dL), or none (males: Hb ≥13 g/dL; females: Hb ≥12 g/dL). In addition, to account for the effect of Johannesburg’s altitude (approximately 1,750 metres above sea level) on haemoglobin values, we applied a downward adjustment of 0.65 g/dL before creating anaemia categories.(19)
Patients were followed from the date of second-line ART initiation until transfer to another HIV treatment facility, loss to follow-up (defined as ≥3 months late for a scheduled visit), death, or close of the dataset (at 12 months for the one-year outcome or February 28, 2014 for the final outcome). The primary outcome for this analysis was attrition, defined as mortality and loss to follow-up combined, at one-year and ever after second-line ART initiation. For patients who report a South African national identification number (approximately 61%), mortality is ascertained primarily through routine linkage with the South Africa National Vital Registration System, which is estimated to have a record of approximately 90% of deaths.(20) For patients without a national ID number or those who choose to not report their number, mortality is ascertained primarily through routine loss to follow-up tracing.
The secondary outcome was virologic suppression (any viral load <400 copies/ml), at least 3 months after initiation of second-line treatment with only those patients with at least one viral load recorded after second-line ART initiation included. All patients with complete covariate information were included in one-year analyses of attrition. For virologic suppression, patients were included in one-year outcome analyses if they also had at least one viral load between 3 and 12 months on treatment. For final outcomes, only those patients who initiated second-line ART between 2005 and 2008 were included in order to ensure that patients could have been followed for at least 5 years.
Statistical Analysis
We present baseline demographic and clinical characteristics as proportions for categorical variables and as medians with interquartile ranges (IQR) for continuous variables. We conducted a complete case analysis using Cox proportional hazards regression to evaluate predictors of attrition and modified Poisson regression with robust error estimation to assess predictors of virologic suppression. Potential risk factors were chosen a priori based on the literature and results are presented as both unadjusted and adjusted hazard or risk ratios with 95% confidence intervals (CI).
Ethical approval
Approval for the use of anonymized data from TherapyEdge-HIV™ was provided by the Human Research Ethics Committee (Medical) of the University of the Witwatersrand and the Institutional Review Board of Boston University.
Results
1,236 people initiated standard second-line ART within one year of first-line failure and were included in the analysis. Patients were on first-line ART for a median (IQR) of 18.8 (12.9–30.9) months prior to initiation of second-line therapy with switch occurring in a median (IQR) of 1.9 (0.9–4.6) months after the second failing viral load. Patients were followed for a median (IQR) of 23.6 (14.0–36.1) months after second-line initiation. 59.1% of patients were female. At second-line initiation, the median (IQR) age was 37.7 (32.5–44.4) years, the median (IQR) CD4 count was 202.5 (114–305) cells/mm3, and the median viral load was 4.18 (3.64–4.81) log10 copies/ml. The CD4 count at switch increased from a median of 152 cells/mm3 in 2005–06 to 218 cells/mm3 in 2011–13 and more patients were co-infected with TB at switch in 2011–13 than in 2009–10 (5.7% vs. 1.1%). Patients had otherwise similar clinical characteristics with different drug regimens prescribed over time reflecting changing guidelines (Table 1).
Table 1.
Demographic and clinical characteristics of patients who switched to second-line antiretroviral therapy between 2005 and 2013 at four public-sector HIV treatment facilities in Johannesburg, South Africa
| Characteristic | Total | 2005/06 | 2007/08 | 2009/10 | 2011/12/13 |
|---|---|---|---|---|---|
| Total | 1236 | 71 | 269 | 266 | 630 |
|
| |||||
| Sex | |||||
|
| |||||
| Male | 505 (40.9%) | 24 (33.8%) | 109 (40.5%) | 116 (43.6%) | 256 (40.6%) |
| Female | 731 (59.1%) | 47 (66.2%) | 160 (59.5%) | 150 (56.4%) | 374 (59.4%) |
|
| |||||
| Age at second-line initiation | |||||
|
| |||||
| Median (IQR) | 37.7 (32.5 – 44.4) | 38.5 (32.0 – 44.1) | 35.8 (31.8 – 42.8) | 37.2 (32.2 – 44.3) | 38.3 (33.1 – 45.0) |
| <30 | 195 (15.8%) | 13 (18.3%) | 46 (17.1%) | 50 (18.8%) | 86 (13.7%) |
| 30–34 | 264 (21.4%) | 12 (16.9%) | 76 (28.3%) | 53 (19.9%) | 123 (19.5%) |
| 35–39 | 278 (22.5%) | 15 (21.1%) | 52 (19.3%) | 55 (20.7%) | 156 (24.8%) |
| 40–44 | 218 (17.6%) | 17 (23.9%) | 44 (16.4%) | 50 (18.8%) | 107 (17.0%) |
| ≥45 | 281 (22.7%) | 14 (19.7%) | 51 (19.0%) | 58 (21.8%) | 158 (25.1%) |
|
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| Confirmatory failing viral load (copies/ml) | |||||
|
| |||||
| Log10 Median (IQR) | 4.11 (3.62 – 4.80) | 4.08 (3.64 – 5.04) | 4.08 (3.71 – 4.57) | 3.86 (3.49 – 4.49) | 4.27 (3.66 – 4.92) |
| <5000 | 360 (29.1%) | 18 (25.4%) | 65 (24.2%) | 107 (40.2%) | 170 (27.0%) |
| 5000 – 9999 | 192 (15.5%) | 13 (18.3%) | 56 (20.8%) | 44 (16.5%) | 79 (12.5%) |
| 10000 – 49999 | 331 (26.8%) | 15 (21.1%) | 92 (34.2%) | 57 (21.4%) | 167 (26.5%) |
| 50000 – 99999 | 129 (10.4%) | 6 (8.5%) | 25 (9.3%) | 23 (8.7%) | 75 (11.9%) |
| ≥100000 | 224 (18.1%) | 19 (26.8%) | 31 (11.5%) | 35 (13.2%) | 139 (22.1%) |
|
| |||||
| Viral load at second-line initiation (copies/ml) | |||||
|
| |||||
| Log10 Median (IQR) | 4.18 (3.64 – 4.81) | 4.28 (3.88 – 5.05) | 4.08 (3.66 – 4.61) | 4.00 (3.52 – 4.59) | 4.31 (3.66 – 4.93) |
| <5000 | 340 (27.5%) | 10 (14.1%) | 73 (27.1%) | 89 (33.5%) | 168 (26.7%) |
| 5000 – 9999 | 171 (13.8%) | 13 (18.3%) | 46 (17.1%) | 45 (16.9%) | 67 (10.6%) |
| 10000 – 49999 | 361 (29.2%) | 23 (32.4%) | 90 (33.5%) | 74 (27.8%) | 174 (27.6%) |
| 50000 – 99999 | 134 (10.8%) | 5 (7.0%) | 24 (8.9%) | 21 (7.9%) | 84 (13.3%) |
| ≥100000 | 230 (18.6%) | 20 (28.2%) | 36 (13.4%) | 37 (13.9%) | 137 (21.8%) |
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| |||||
| CD4 count (cells/mm3) | |||||
|
| |||||
| Median (IQR) | 202.5 (114 – 305) | 152 (88 – 223) | 186 (111 – 274) | 195 (131 – 260) | 218 (113 – 345) |
| Missing | 10 | 0 | 0 | 5 | 5 |
| <50 | 129 (10.4%) | 9 (12.7%) | 24 (8.9%) | 20 (7.7%) | 76 (12.2%) |
| 50–99 | 130 (10.5%) | 11 (15.5%) | 32 (11.9%) | 27 (10.3%) | 60 (9.6%) |
| 100–199 | 342 (27.7%) | 27 (38.0%) | 88 (32.7%) | 85 (32.6%) | 142 (22.7%) |
| ≥200 | 625 (50.6%) | 24 (33.8%) | 125 (46.5%) | 129 (49.4%) | 347 (55.5%) |
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| Co-infected with TB | |||||
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| Yes | 45 (3.6%) | 2 (2.8%) | 4 (1.5%) | 3 (1.1%) | 36 (5.7%) |
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| BMI (kg/m2) | |||||
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| |||||
| Median (IQR) | 24.4 (21.4 – 28.3) | 24.4 (22.2 – 28.5) | 24.3 (21.4 – 28.4) | 23.7 (21.2 – 27.6) | 24.6 (21.4 – 28.4) |
| Missing | 56 | 2 | 19 | 9 | 26 |
| <18.5 | 69 (5.6%) | 5 (7.3%) | 17 (6.8%) | 16 (6.2%) | 31 (5.1%) |
| 18.5–24.9 | 588 (47.6%) | 34 (49.3%) | 121 (48.4%) | 131 (51.0%) | 302 (50.0%) |
| 25–29.9 | 320 (25.9%) | 19 (27.5%) | 70 (28.0%) | 68 (26.5%) | 163 (27.0%) |
| ≥30 | 203 (16.4%) | 11 (15.9%) | 42 (16.8%) | 42 (16.3%) | 108 (17.9%) |
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| Anaemia1 | |||||
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| |||||
| Median (IQR) | 12.7 (11.6 – 13.8) | 12.6 (11.3 – 13.6) | 12.8 (11.7 – 13.9) | 12.6 (11.4 – 13.6) | 12.8 (11.6 – 13.9) |
| Missing | 24 | 1 | 1 | 2 | 20 |
| None | 705 (57.0%) | 39 (55.7%) | 169 (63.1%) | 133 (50.4%) | 364 (59.7%) |
| Mild | 297 (24.0%) | 17 (24.3%) | 53 (19.8%) | 81 (30.7%) | 146 (23.9%) |
| Moderate | 196 (15.9%) | 13 (18.6%) | 41 (15.3%) | 44 (16.7%) | 98 (16.1%) |
| Severe | 14 (1.1%) | 1 (1.4%) | 5 (1.9%) | 6 (2.3%) | 2 (0.3%) |
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| First ART regimen | |||||
|
| |||||
| TDF-3TC-EFV | 217 (17.6%) | 0 (0.0%) | 0 (0.0%) | 5 (1.9%) | 212 (33.7%) |
| d4T-3TC-EFV | 827 (66.9%) | 58 (81.7%) | 237 (88.1%) | 216 (81.2%) | 316 (50.2%) |
| Other2 | 192 (15.5%) | 13 (18.3%) | 32 (11.9%) | 45 (16.9%) | 102 (16.2%) |
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| Second-line ART regimen | |||||
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| |||||
| TDF-3TC/EMT-LPVr3 | 374 (30.3%) | 1 (1.4%) | 4 (1.5%) | 93 (35.0%) | 276 (43.8%) |
| AZT-3TC-LPVr | 366 (29.6%) | 0 (0.0%) | 1 (0.4%) | 13 (4.9%) | 352 (55.9%) |
| AZT-ddI-LPVr | 496 (40.1%) | 70 (98.6%) | 264 (98.1%) | 160 (60.2%) | 2 (0.3%) |
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| Time on first-line ART (months) | |||||
|
| |||||
| Median (IQR) | 18.8 (12.9 – 30.9) | 14.4 (10.3 – 18.3) | 18.3 (12.9 – 25.3) | 20.8 (13.3 – 34.2) | 19.9 (13.0 – 36.2) |
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| Time from virologic failure to switch (months) | |||||
|
| |||||
| Median (IQR) | 1.9 (0.9 – 4.6) | 2.3 (0.9 – 5.3) | 2.0 (1.0 – 4.1) | 1.8 (0.9 – 4.6) | 2.0 (0.9 – 4.6) |
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| |||||
| Time from second-line switch to outcome or close of dataset | |||||
|
| |||||
| Median (IQR) | 23.6 (14.0 – 36.1) | 48.1 (20.1 – 92.9) | 34.5 (15.2 – 66.3) | 32.4 (12.5 – 45.2) | 20.4 (14.0 – 27.4) |
None: males: ≥13 g/dL, females: ≥12 g/dL; Mild: males: 11–12 g/dL, females: 11–11.9 g/dL; Moderate: 8–10 g/dL; Severe: <8 g/dL
Other regimens include: AZT-3TC-NVP/EFV, d4T-3TC-NVP, TDF-3TC-NVP, TDF-EMT-EFV
11 patients initiated TDF-EMT-LPVr
Attrition from care
1,150 patients had information on all covariates of interest and were included in the analysis of one-year outcomes and 12.6% died (1.9%) or were lost to follow-up (10.7%). Older patients were less likely to leave care than younger patients (35–39 vs. <30, HR: 0.40; 95% CI: 0.23–0.70) and patients with high viral loads (≥100000 vs. <5000, HR: 2.36; 95% CI: 1.47–3.78), low CD4 counts (<50 vs. ≥200, HR: 2.19; 95% CI: 1.38–3.46), and those co-infected with TB (HR: 2.41; 95% CI: 1.31–4.46) were at greater risk for attrition. After adjustment, including for sex, BMI, anaemia, TB co-infection, and ART regimen, the association was attenuated for viral load (aHR: 1.85; 95% CI: 1.08–3.18) while no association was observed for CD4 count (Table 2).
Table 2.
Unadjusted and adjusted estimates of attrition at one-year and ever after second-line initiation among patients at four public-sector HIV treatment facilities in Johannesburg, South Africa.
|
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|---|---|---|---|---|---|---|
| At one-year after second-line initiation (n=1150)1 | Ever after second-line initiation (n=318)2 | |||||
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| Characteristic | Dead or LTF/N (%) | Unadjusted HR (95% CI) | Adjusted HR (95% CI) | Dead or LTF/N (%) | Unadjusted HR (95% CI) | Adjusted HR (95% CI) |
|
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| Year of second-line initiation | ||||||
|
|
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|||||
| 2005/06 | 8/68 (11.8%) | Reference | Reference | 27/68 (39.7%) | Reference | Reference |
| 2007/08 | 39/250 (15.6%) | 1.36 (0.64 – 2.91) | 1.47 (0.68 – 3.18) | 117/250 (46.8%) | 1.51 (0.98 – 2.33) | 1.64 (1.04 – 2.60) |
| 2009/10 | 30/251 (12.0%) | 1.09 (0.50 – 2.38) | 1.11 (0.48 – 2.57) | – | – | – |
| 2011/12/13 | 68/581 (11.7%) | 1.03 (0.50 – 2.15) | 0.77 (0.27 – 2.16) | – | – | – |
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| Sex | ||||||
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| Male | 69/460 (15.0%) | Reference | Reference | 67/122 (54.9%) | Reference | Reference |
| Female | 76/690 (11.0%) | 0.74 (0.54 – 1.03) | 0.89 (0.61 – 1.30) | 77/196 (39.3%) | 0.75 (0.54 – 1.04) | 0.73 (0.49 – 1.08) |
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| Age at initiation | ||||||
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| <30 | 33/180 (18.3%) | Reference | Reference | 33/54 (61.1%) | Reference | Reference |
| 30–34 | 33/245 (13.5%) | 0.72 (0.44 – 1.17) | 0.77 (0.47 – 1.27) | 35/82 (42.7%) | 0.58 (0.36 – 0.93) | 0.59 (0.36 – 0.99) |
| 35–39 | 20/256 (7.8%) | 0.40 (0.23 – 0.70) | 0.41 (0.23 – 0.73) | 26/63 (41.3%) | 0.52 (0.31 – 0.88) | 0.52 (0.30 – 0.91) |
| 40–44 | 24/207 (11.6%) | 0.61 (0.36 – 1.02) | 0.61 (0.35 – 1.06) | 25/60 (41.7%) | 0.47 (0.28 – 0.79) | 0.49 (0.28 – 0.85) |
| ≥45 | 35/262 (13.4%) | 0.70 (0.44 – 1.13) | 0.76 (0.46 – 1.26) | 25/59 (42.4%) | 0.55 (0.33 – 0.93) | 0.48 (0.27 – 0.84) |
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| Viral load (copies/ml) | ||||||
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| <5000 | 29/319 (9.1%) | Reference | Reference | 30/81 (37.0%) | Reference | Reference |
| 5000 – 9999 | 22/158 (13.9%) | 1.59 (0.91 – 2.77) | 1.50 (0.85 – 2.64) | 27/56 (48.2%) | 1.73 (1.03 – 2.91) | 1.91 (1.12 – 3.28) |
| 10000 – 49999 | 34/337 (10.1%) | 1.12 (0.68 – 1.84) | 1.00 (0.60 – 1.67) | 42/102 (41.2%) | 1.22 (0.76 – 1.95) | 1.11 (0.68 – 1.81) |
| 50000 – 99999 | 17/122 (13.9%) | 1.59 (0.87 – 2.90) | 1.55 (0.84 – 2.87) | 12/26 (46.2%) | 1.47 (0.75 – 2.87) | 1.39 (0.70 – 2.74) |
| ≥100000 | 43/214 (20.1%) | 2.36 (1.47 – 3.78) | 1.85 (1.08 – 3.18) | 33/53 (62.3%) | 2.17 (1.32 – 3.56) | 1.64 (0.94 – 2.88) |
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| CD4 count (cells/mm3) | ||||||
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| <50 | 26/121 (21.5%) | 2.19 (1.38 – 3.46) | 1.43 (0.83 – 2.46) | 20/31 (64.5%) | 2.18 (1.30 – 3.64) | 1.85 (1.03 – 3.32) |
| 50–99 | 14/112 (12.5%) | 1.21 (0.68 – 2.17) | 0.78 (0.42 – 1.47) | 22/37 (59.5%) | 1.57 (0.95 – 2.57) | 1.33 (0.77 – 2.32) |
| 100–199 | 44/323 (13.6%) | 1.35 (0.92 – 1.99) | 1.16 (0.77 – 1.75) | 48/108 (44.4%) | 1.24 (0.84 – 1.83) | 1.22 (0.80 – 1.86) |
| ≥200 | 61/594 (10.3%) | Reference | Reference | 54/142 (38.0%) | Reference | Reference |
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| Co-infected with tuberculosis | ||||||
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| No | 134/1109 (12.1%) | Reference | Reference | 141/313 (45.1%) | Reference | Reference |
| Yes | 11/41 (26.8%) | 2.41 (1.31 – 4.46) | 2.11 (1.11 – 4.01) | 3/5 (60.0%) | 1.35 (0.43 – 4.23) | 0.98 (0.29 – 3.27) |
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| BMI | ||||||
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| <18.5 | 15/66 (22.7%) | 1.66 (0.96 – 2.88) | 1.66 (0.94 – 2.92) | 15/22 (68.2%) | 1.71 (0.98 – 2.97) | 1.31 (0.72 – 2.38) |
| 18.5–24.9 | 83/568 (14.6%) | Reference | Reference | 76/154 (49.4%) | Reference | Reference |
| 25–29.9 | 34/315 (10.8%) | 0.72 (0.49 – 1.08) | 0.83 (0.55 – 1.25) | 32/89 (36.0%) | 0.65 (0.43 – 0.99) | 0.69 (0.45 – 1.05) |
| ≥30 | 13/201 (6.5%) | 0.42 (0.24 – 0.76) | 0.47 (0.26 – 0.87) | 21/53 (39.6%) | 0.70 (0.43 – 1.14) | 0.81 (0.48 – 1.39) |
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| Anaemia3 | ||||||
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| None | 82/670 (12.2%) | Reference | Reference | 84/195 (43.1%) | Reference | Reference |
| Mild | 38/279 (13.6%) | 1.14 (0.78 – 1.68) | 0.97 (0.65 – 1.45) | 28/68 (41.2%) | 1.00 (0.65 – 1.54) | 0.90 (0.57 – 1.41) |
| Moderate | 23/187 (12.3%) | 1.03 (0.65 – 1.64) | 0.82 (0.49 – 1.37) | 28/49 (57.1%) | 1.64 (1.07 – 2.52) | 1.43 (0.87 – 2.34) |
| Severe | 2/14 (14.3%) | 1.16 (0.29 – 4.73) | 0.98 (0.23 – 4.08) | 4/6 (66.7%) | 1.86 (0.68 – 5.07) | 1.42 (0.48 – 4.18) |
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| First ART regimen | ||||||
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|||||
| TDF-3TC-EFV | 32/196 (16.3%) | 1.44 (0.96 – 2.15) | 1.57 (0.86 – 2.88) | – | – | – |
| d4T-3TC-EFV | 93/781 (11.9%) | Reference | Reference | 123/276 (44.6%) | Reference | Reference |
| Other4 | 20/173 (11.6%) | 0.99 (0.61 – 1.61) | 1.13 (0.68 – 1.88) | 21/42 (50.0%) | 1.11 (0.70 – 1.77) | 1.07 (0.64 – 1.79) |
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| Second-line ART regimen | ||||||
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| TDF-3TC/EMT-LPVr5 | 36/350 (10.3%) | 0.75 (0.50 – 1.13) | 1.21 (0.61 – 2.42) | 4/5 (80.0%) | – | – |
| AZT-3TC-LPVr | 46/335 (13.7%) | 1.03 (0.70 – 1.51) | 1.16 (0.50 – 2.70) | 0/1 (0%) | – | – |
| AZT-ddI-LPVr | 63/465 (13.6%) | Reference | Reference | 140/312 (44.9%) | – | – |
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One-year analyses include all patients with complete covariate information
Final analyses included only those patients who initiated second-line ART between 2005 and 2008 and had complete covariate information
None: males: ≥13 g/dL, females: ≥12 g/dL; Mild: males: 11–12 g/dL, females: 11–11.9 g/dL; Moderate: 8–10 g/dL; Severe: <8 g/dL
Other regimens include: AZT-3TC-NVP/EFV, d4T-3TC-NVP, TDF-3TC-NVP, TDF-EMT-EFV
11 patients initiated TDF-EMT-LPVr
Patients who initiated second-line ART from 2005–2008 were included in long-term analyses. By the end of follow-up, 45.3% of 318 patients had died (14.2%) or were lost (31.1%). Patients who initiated in 2007–08 were more likely to leave care than patients who initiated in 2005–06 (aHR: 1.64; 95% CI: 1.04–2.60), as were patients with low CD4 counts (<50 vs. ≥200, aHR: 1.85; 95% CI: 1.03–3.32), while being of older age was protective (≥45 vs. <30, aHR: 0.48; 95% CI: 0.27–0.84) (Table 2).
Virologic suppression
927 patients were included in one-year analyses of virologic suppression and 74.9% suppressed (Table 3). Patients whose first-line regimen consisted of TDF-3TC-EFV were slightly more likely to suppress than patients on d4T-3TC-EFV (aRR: 1.22; 95% CI: 1.07–1.39) while patients with high viral loads at switch were less likely to suppress (≥100000 vs. <5000, aRR: 0.79; 95% CI: 0.68–0.92). No associations were observed between second-line ART regimen and virologic suppression. Few characteristics were associated with suppression in long-term analyses and rates of suppression were moderately high (85.3%). Patients with low CD4 counts at the time of switch (<50 vs. ≥200, RR: 0.62; 95% CI: 0.44–0.87) and those with high viral loads (≥100000 vs. <5000, RR: 0.79; 95% CI: 0.64–0.97) were less likely to suppress but the relationship between a high viral load and suppression was attenuated after adjustment (aRR: 0.85; 95% CI: 0.69 – 1.04) (Table 3).
Table 3.
Unadjusted and adjusted estimates of virologic suppression at one-year and ever after second-line initiation among patients at four public-sector HIV treatment facilities in Johannesburg, South Africa.
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|---|---|---|---|---|---|---|
| At one-year after second-line initiation (n=927)1 | Ever after second-line initiation (n=272)2 | |||||
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| Characteristic | Suppressed/N (%) | Unadjusted RR (95% CI) | Adjusted RR (95% CI) | Suppressed/N (%) | Unadjusted RR (95% CI) | Adjusted RR (95% CI) |
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| Year of second-line initiation | ||||||
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| 2005/06 | 45/59 (76.3%) | Reference | Reference | 54/61 (88.5%) | Reference | Reference |
| 2007/08 | 160/205 (78.1%) | 1.02 (0.87 – 1.20) | 0.99 (0.85 – 1.15) | 178/211 (84.4%) | 0.95 (0.86 – 1.06) | 0.91 (0.83 – 1.01) |
| 2009/10 | 142/197 (72.1%) | 0.95 (0.80 – 1.12) | 0.88 (0.74 – 1.05) | – | – | – |
| 2011/12/13 | 347/466 (74.5%) | 0.98 (0.84 – 1.14) | 0.82 (0.65 – 1.03) | – | – | – |
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| Sex | ||||||
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| Male | 266/370 (71.9%) | Reference | Reference | 88/104 (84.6%) | Reference | Reference |
| Female | 428/557 (76.8%) | 1.07 (0.99 – 1.16) | 1.06 (0.97 – 1.15) | 144/168 (85.7%) | 1.01 (0.91 – 1.12) | 1.02 (0.91 – 1.14) |
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| Age at initiation | ||||||
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| <30 | 91/129 (70.5%) | Reference | Reference | 33/43 (76.7%) | Reference | Reference |
| 30–34 | 153/196 (78.1%) | 1.11 (0.97 – 1.27) | 1.12 (0.98 – 1.27) | 61/72 (84.7%) | 1.10 (0.91 – 1.34) | 1.13 (0.94 – 1.35) |
| 35–39 | 165/223 (74.0%) | 1.05 (0.92 – 1.20) | 1.09 (0.95 – 1.25) | 44/52 (84.6%) | 1.10 (0.90 – 1.35) | 1.09 (0.90 – 1.31) |
| 40–44 | 125/169 (74.0%) | 1.05 (0.91 – 1.21) | 1.08 (0.93 – 1.24) | 49/54 (90.7%) | 1.18 (0.98 – 1.42) | 1.19 (0.99 – 1.43) |
| ≥45 | 160/210 (76.2%) | 1.08 (0.94 – 1.24) | 1.12 (0.98 – 1.29) | 45/51 (88.2%) | 1.15 (0.95 – 1.39) | 1.20 (0.99 – 1.47) |
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| Viral load (copies/ml) | ||||||
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| <5000 | 207/264 (78.4%) | Reference | Reference | 67/74 (90.5%) | Reference | Reference |
| 5000 – 9999 | 99/126 (78.6%) | 1.00 (0.90 – 1.12) | 1.02 (0.91 – 1.14) | 39/43 (90.7%) | 1.00 (0.89 – 1.13) | 0.99 (0.88 – 1.12) |
| 10000 – 49999 | 222/286 (77.6%) | 0.99 (0.91 – 1.08) | 1.00 (0.91 – 1.10) | 78/91 (85.7%) | 0.95 (0.85 – 1.06) | 1.00 (0.90 – 1.12) |
| 50000 – 99999 | 66/92 (71.7%) | 0.91 (0.79 – 1.06) | 0.92 (0.79 – 1.06) | 18/22 (81.8%) | 0.90 (0.73 – 1.12) | 0.94 (0.76 – 1.16) |
| ≥100000 | 100/159 (62.9%) | 0.80 (0.70 – 0.92) | 0.79 (0.68 – 0.92) | 30/42 (71.4%) | 0.79 (0.64 – 0.97) | 0.85 (0.69 – 1.04) |
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| CD4 count (cells/mm3) | ||||||
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| <50 | 57/91 (62.6%) | 0.82 (0.69 – 0.97) | 0.86 (0.72 – 1.03) | 15/27 (55.6%) | 0.62 (0.44 – 0.87) | 0.65 (0.46 – 0.91) |
| 50–99 | 70/91 (76.9%) | 1.00 (0.89 – 1.14) | 1.05 (0.92 – 1.19) | 29/31 (93.6%) | 1.04 (0.93 – 1.15) | 1.08 (0.96 – 1.20) |
| 100–199 | 191/254 (75.2%) | 0.98 (0.90 – 1.07) | 1.00 (0.92 – 1.10) | 76/90 (84.4%) | 0.93 (0.84 – 1.04) | 0.96 (0.86 – 1.07) |
| ≥200 | 376/491 (76.6%) | Reference | Reference | 112/124 (90.3%) | Reference | Reference |
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| Co-infected with tuberculosis | ||||||
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| No | 672/899 (74.8%) | Reference | Reference | 229/268 (85.5%) | Reference | Reference |
| Yes | 22/28 (78.6%) | 1.05 (0.86 – 1.28) | 1.06 (0.86 – 1.29) | 3/4 (75.0%) | 0.88 (0.50 – 1.55) | 0.90 (0.55 – 1.48) |
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| BMI | ||||||
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| <18.5 | 30/44 (68.2%) | 0.93 (0.76 – 1.15) | 0.99 (0.80 – 1.22) | 12/15 (80.0%) | 0.99 (0.76 – 1.29) | 1.15 (0.87 – 1.48) |
| 18.5–24.9 | 327/448 (73.0%) | Reference | Reference | 105/130 (80.8%) | Reference | Reference |
| 25–29.9 | 204/265 (77.0%) | 1.05 (0.97 – 1.15) | 1.03 (0.94 – 1.12) | 72/78 (92.3%) | 1.14 (1.03 – 1.27) | 1.11 (1.00 – 1.23) |
| ≥30 | 133/170 (78.2%) | 1.07 (0.97 – 1.18) | 1.02 (0.92 – 1.13) | 43/49 (87.8%) | 1.09 (0.95 – 1.24) | 1.05 (0.92 – 1.21) |
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| Anaemia3 | ||||||
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| None | 408/540 (75.6%) | Reference | Reference | 149/167 (89.2%) | Reference | Reference |
| Mild | 167/227 (73.6%) | 0.97 (0.89 – 1.07) | 0.99 (0.91 – 1.09) | 49/61 (80.3%) | 0.90 (0.79 – 1.03) | 0.94 (0.83 – 1.07) |
| Moderate | 109/148 (73.7%) | 0.97 (0.88 – 1.09) | 0.99 (0.88 – 1.11) | 30/39 (76.9%) | 0.86 (0.72 – 1.03) | 0.89 (0.74 – 1.07) |
| Severe | 10/12 (83.3%) | 1.10 (0.85 – 1.43) | 1.12 (0.86 – 1.47) | 4/5 (80.0%) | 0.90 (0.58 – 1.39) | 1.08 (0.62 – 1.88) |
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| First ART regimen | ||||||
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| TDF-3TC-EFV | 117/145 (80.7%) | 1.12 (1.02 – 1.23) | 1.22 (1.07 – 1.39) | – | – | – |
| d4T-3TC-EFV | 461/639 (72.1%) | Reference | Reference | 200/235 (85.1%) | Reference | Reference |
| Other4 | 116/143 (81.1%) | 1.12 (1.03 – 1.23) | 1.15 (1.04 – 1.26) | 32/37 (86.5%) | 1.02 (0.89 – 1.17) | 1.03 (0.90 – 1.18) |
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| Second-line ART regimen | ||||||
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| TDF-3TC/EMT-LPVr5 | 204/284 (71.8%) | 0.95 (0.87 – 1.05) | 1.07 (0.91 – 1.26) | 3/3 (100%) | – | – |
| AZT-3TC-LPVr | 204/263 (77.6%) | 1.03 (0.94 – 1.12) | 1.13 (0.93 – 1.39) | 0/1 (0.0%) | – | – |
| AZT-ddI-LPVr | 286/380 (75.3%) | Reference | Reference | 229/268 (85.5%) | – | – |
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One-year analyses include all patients with at least one viral load conducted between 3 and 12 months after second-line ART initiation and complete covariate information
Final analyses included only those patients who initiated second-line ART between 2005 and 2008, had at least one viral load conducted at least 3 months after second-line ART initiation and had complete covariate information
None: males: ≥13 g/dL, females: ≥12 g/dL; Mild: males: 11–12 g/dL, females: 11–11.9 g/dL; Moderate: 8–10 g/dL; Severe: <8 g/dL
Other regimens include: AZT-3TC-NVP/EFV, d4T-3TC-NVP, TDF-3TC-NVP, TDF-EMT-EFV
11 patients initiated TDF-EMT-LPVr
Discussion
The number of people living with HIV in resource-limited settings who require second-line treatment to effectively manage their HIV infection is expanding, with close to 1 million people living with HIV anticipated to be on second-line treatment by 2030 in South Africa alone.(6) Thus, understanding the factors associated with good second-line treatment outcomes is imperative to the continued success of South Africa’s national ART program. In this cohort of 1,236 HIV-infected adult patients on second-line ART, we found overall low mortality one-year after second-line initiation, with just 2% of patients reported to have died, and moderately high rates of virologic suppression.
The low levels of mortality observed after second-line ART initiation in this cohort may reflect some under-ascertainment of deaths. Among included patients, approximately 64% provided a national ID number that could be linked with the national death registry. Therefore, losses to follow-up among patients without a national ID number may be masking mortality. While routine loss to follow-up tracing does mitigate this under-ascertainment, studies of loss to follow-up tracing have reported that 10% – 47% of patients who are lost from care cannot be traced.(21–24) In addition, the low mortality may also be indicative of some survivor bias as not all patients who failed first-line treatment switched to second-line ART. Thus, sicker patients may have died before being able to switch to a second-line regimen. In our cohort, when mortality was combined with loss to follow-up to form our primary outcome of attrition, 12.6% of patients had left care one year after second-line ART initiation, increasing to nearly half of all patients by the end of follow-up.
Patients with higher viral loads and lower CD4 counts at the time of switch to second-line were at greater risk for attrition and were less likely to experience virologic suppression. These findings are similar to those reported elsewhere but the larger sample size and longer follow-up time aid in making inferences.(7,12,13) While drug resistance testing is not routinely conducted, previous research has shown that sub-optimal adherence is likely to be the primary driver of virologic failure on second-line ART.(25–27) Thus, further adherence support may improve treatment outcomes for patients who are on second-line treatment. The higher proportion of TB co-infection at second-line switch observed in more recent years may be reflective of the expanded use of a more sensitive TB diagnostic, Xpert MTB/RIF.(28,29) While national scale-up of Xpert MTB/RIF was completed in 2013, some facilities had access to Xpert MTB/RIF for initial TB diagnosis from as early as 2011.
This analysis should be viewed in light of several limitations. As not all patients who are lost to follow-up are able to be successfully traced, some patients may also have self-transferred to another HIV treatment facility and, thus, may represent loss from the original treating facility but not loss from the national ART program. In addition, only those patients with a viral load recorded were included in analyses of virologic suppression. This may have resulted in a biased estimate of suppression if patients with a viral load result were systematically different from those who remained in care but did not have a viral load measurement recorded.
Our analysis also has several strengths. Our cohort of over 1,200 patients initiated on second-line therapy is one of the largest analyses presented from sub-Saharan Africa. Including only those patients who initiated standard regimens for both first- and second-line treatment, and limiting the analysis to patients who switched within one-year of virologic failure, protected our results from potential biases that may occur from including patients who switched to second-line for reasons other than virologic failure. Finally, the integration of the clinics’ electronic medical record systems with the NHLS improved ascertainment of clinical indicators and limited data entry errors.
Conclusions
HIV-infected patients initiated on standard second-line ART in South Africa can experience overall low rates of attrition and moderately high rates of virologic suppression shortly after second-line initiation, however individuals with poorer immune status at the time of initiation of second-line treatment are at greater risk for attrition, were less likely to suppress and may need additional adherence support in order to improve treatment outcomes.
Acknowledgments
We express our gratitude to the directors, staff, and patients of the Themba Lethu Clinic for their support of this research. This work was funded through the South African Mission of the United States Agency for International Development. Additional support to KS was provided by the National Institutes of Health. This study was made possible by the generous support of the American people through USAID. The contents are the responsibility of the Health Economics and Epidemiology Research Office and do not necessarily reflect the views of USAID, the United States government, or the Themba Lethu Clinic.
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