Journal Article > ResearchFull Text
J Int AIDS Soc. 23 June 2017; Volume 20 (Issue 1); DOI:10.7448/IAS.20.1.21327
Fenner L, Atkinson A, Boulle AM, Fox MP, Prozesky HW, et al.
J Int AIDS Soc. 23 June 2017; Volume 20 (Issue 1); DOI:10.7448/IAS.20.1.21327
Chronic immune activation due to ongoing HIV replication may lead to impaired immune responses against opportunistic infections such as tuberculosis (TB). We studied the role of HIV replication as a risk factor for incident TB after starting antiretroviral therapy (ART).
Journal Article > ResearchFull Text
AIDS. 10 September 2010; Volume 24 (Issue 14); DOI:10.1097/QAD.0b013e32833d45c5
Cornell M, Grimsrud A, Fairall L, Fox MP, van Cutsem G, et al.
AIDS. 10 September 2010; Volume 24 (Issue 14); DOI:10.1097/QAD.0b013e32833d45c5
OBJECTIVE: Little is known about the temporal impact of the rapid scale-up of large antiretroviral therapy (ART) services on programme outcomes. We describe patient outcomes [mortality, loss-to-follow-up (LTFU) and retention] over time in a network of South African ART cohorts. DESIGN: Cohort analysis utilizing routinely collected patient data. METHODS: Analysis included adults initiating ART in eight public sector programmes across South Africa, 2002-2007. Follow-up was censored at the end of 2008. Kaplan-Meier methods were used to estimate time to outcomes, and proportional hazards models to examine independent predictors of outcomes. RESULTS: Enrolment (n = 44 177, mean age 35 years; 68% women) increased 12-fold over 5 years, with 63% of patients enrolled in the past 2 years. Twelve-month mortality decreased from 9% to 6% over 5 years. Twelve-month LTFU increased annually from 1% (2002/2003) to 13% (2006). Cumulative LTFU increased with follow-up from 14% at 12 months to 29% at 36 months. With each additional year on ART, failure to retain participants was increasingly attributable to LTFU compared with recorded mortality. At 12 and 36 months, respectively, 80 and 64% of patients were retained. CONCLUSION: Numbers on ART have increased rapidly in South Africa, but the programme has experienced deteriorating patient retention over time, particularly due to apparent LTFU. This may represent true loss to care, but may also reflect administrative error and lack of capacity to monitor movements in and out of care. New strategies are needed for South Africa and other low-income and middle-income countries to improve monitoring of outcomes and maximize retention in care with increasing programme size.
Journal Article > ResearchFull Text
PLOS One. 28 February 2013; Volume 8 (Issue 2); e57611.; DOI:10.1371/journal.pone.0057611
Estill J, Egger M, Johnson LF, Gsponer T, Wandeler G, et al.
PLOS One. 28 February 2013; Volume 8 (Issue 2); e57611.; DOI:10.1371/journal.pone.0057611
OBJECTIVES
Mortality in patients starting antiretroviral therapy (ART) is higher in Malawi and Zambia than in South Africa. We examined whether different monitoring of ART (viral load [VL] in South Africa and CD4 count in Malawi and Zambia) could explain this mortality difference.
DESIGN
Mathematical modelling study based on data from ART programmes.
METHODS
We used a stochastic simulation model to study the effect of VL monitoring on mortality over 5 years. In baseline scenario A all parameters were identical between strategies except for more timely and complete detection of treatment failure with VL monitoring. Additional scenarios introduced delays in switching to second-line ART (scenario B) or higher virologic failure rates (due to worse adherence) when monitoring was based on CD4 counts only (scenario C). Results are presented as relative risks (RR) with 95% prediction intervals and percent of observed mortality difference explained.
RESULTS
RRs comparing VL with CD4 cell count monitoring were 0.94 (0.74-1.03) in scenario A, 0.94 (0.77-1.02) with delayed switching (scenario B) and 0.80 (0.44-1.07) when assuming a 3-times higher rate of failure (scenario C). The observed mortality at 3 years was 10.9% in Malawi and Zambia and 8.6% in South Africa (absolute difference 2.3%). The percentage of the mortality difference explained by VL monitoring ranged from 4% (scenario A) to 32% (scenarios B and C combined, assuming a 3-times higher failure rate). Eleven percent was explained by non-HIV related mortality.
CONCLUSIONS
VL monitoring reduces mortality moderately when assuming improved adherence and decreased failure rates.
Mortality in patients starting antiretroviral therapy (ART) is higher in Malawi and Zambia than in South Africa. We examined whether different monitoring of ART (viral load [VL] in South Africa and CD4 count in Malawi and Zambia) could explain this mortality difference.
DESIGN
Mathematical modelling study based on data from ART programmes.
METHODS
We used a stochastic simulation model to study the effect of VL monitoring on mortality over 5 years. In baseline scenario A all parameters were identical between strategies except for more timely and complete detection of treatment failure with VL monitoring. Additional scenarios introduced delays in switching to second-line ART (scenario B) or higher virologic failure rates (due to worse adherence) when monitoring was based on CD4 counts only (scenario C). Results are presented as relative risks (RR) with 95% prediction intervals and percent of observed mortality difference explained.
RESULTS
RRs comparing VL with CD4 cell count monitoring were 0.94 (0.74-1.03) in scenario A, 0.94 (0.77-1.02) with delayed switching (scenario B) and 0.80 (0.44-1.07) when assuming a 3-times higher rate of failure (scenario C). The observed mortality at 3 years was 10.9% in Malawi and Zambia and 8.6% in South Africa (absolute difference 2.3%). The percentage of the mortality difference explained by VL monitoring ranged from 4% (scenario A) to 32% (scenarios B and C combined, assuming a 3-times higher failure rate). Eleven percent was explained by non-HIV related mortality.
CONCLUSIONS
VL monitoring reduces mortality moderately when assuming improved adherence and decreased failure rates.
Journal Article > ResearchFull Text
BMJ Open. 11 January 2018; Volume 8 (Issue 1); DOI:10.1136/bmjopen-2017-017405
Ballif M, Zurcher K, Reid SE, Boulle AM, Fox MP, et al.
BMJ Open. 11 January 2018; Volume 8 (Issue 1); DOI:10.1136/bmjopen-2017-017405
Seasonal variations in tuberculosis diagnoses have been attributed to seasonal climatic changes and indoor crowding during colder winter months. We investigated trends in pulmonary tuberculosis (PTB) diagnosis at antiretroviral therapy (ART) programmes in Southern Africa.
Journal Article > ResearchFull Text
J Acquir Immune Defic Syndr. 1 June 2011; Volume 57 (Issue 2); DOI:10.1097/QAI.0b013e3182199ee9
Lawn SD, Campbell L, Kaplan R, Boulle AM, Cornell M, et al.
J Acquir Immune Defic Syndr. 1 June 2011; Volume 57 (Issue 2); DOI:10.1097/QAI.0b013e3182199ee9
We studied the time interval between starting tuberculosis treatment and commencing antiretroviral treatment (ART) in HIV-infected patients (n = 1433; median CD4 count 71 cells per microliter, interquartile range: 32-132) attending 3 South African township ART services between 2002 and 2008. The overall median delay was 2.66 months (interquartile range: 1.58-4.17). In adjusted analyses, delays varied between treatment sites but were shorter for patients with lower CD4 counts and those treated in more recent calendar years. During the most recent period (2007-2008), 4.7%, 19.7%, and 51.1% of patients started ART within 2, 4, and 8 weeks of tuberculosis treatment, respectively. Operational barriers must be tackled to permit further acceleration of ART initiation as recommended by 2010 WHO ART guidelines.
Journal Article > ResearchFull Text
Pediatrics. 17 September 2012; Volume 130 (Issue 4); e966-e977.; DOI:10.1542/peds.2011-3020
Gsponer T, Weigel R, Davies MA, Bolton C, Moultrie H, et al.
Pediatrics. 17 September 2012; Volume 130 (Issue 4); e966-e977.; DOI:10.1542/peds.2011-3020
BACKGROUND
Poor growth is an indication for antiretroviral therapy (ART) and a criterion for treatment failure. We examined variability in growth response to ART in 12 programs in Malawi, Zambia, Zimbabwe, Mozambique, and South Africa.
METHODS
Treatment naïve children aged <10 years were included. We calculated weight for age z scores (WAZs), height for age z scores (HAZs), and weight for height z scores (WHZs) up to 3 years after starting ART, by using the World Health Organization standards. Multilevel regression models were used.
RESULTS
A total of 17 990 children (range, 238–8975) were followed for 36 181 person-years. At ART initiation, most children were underweight (50%) and stunted (66%). Lower baseline WAZ, HAZ, and WHZ were the most important determinants of faster catch-up growth on ART. WAZ and WHZ increased rapidly in the first year and stagnated or reversed thereafter, whereas HAZ increased continuously over time. Three years after starting ART, WAZ ranged from −2.80 (95% confidence interval [CI]: −3.66 to −2.02) to −1.98 (95% CI: −2.41 to −1.48) in children with a baseline z score < −3 and from −0.79 (95% CI: −1.62 to 0.02) to 0.05 (95% CI: −0.42 to 0.51) in children with a baseline WAZ ≥ −1. For HAZ, the corresponding range was −2.33 (95% CI: −2.62 to −2.02) to −1.27 (95% CI: −1.58 to −1.00) for baseline HAZ < −3 and −0.24 (95% CI: −0.56 to 0.15) to 0.84 (95% CI: 0.53 to 1.16) for HAZ ≥ −1.
CONCLUSIONS
Despite a sustained growth response and catch-up growth in children with advanced HIV disease treated with ART, normal weights and heights are not achieved over 3 years of ART.
Poor growth is an indication for antiretroviral therapy (ART) and a criterion for treatment failure. We examined variability in growth response to ART in 12 programs in Malawi, Zambia, Zimbabwe, Mozambique, and South Africa.
METHODS
Treatment naïve children aged <10 years were included. We calculated weight for age z scores (WAZs), height for age z scores (HAZs), and weight for height z scores (WHZs) up to 3 years after starting ART, by using the World Health Organization standards. Multilevel regression models were used.
RESULTS
A total of 17 990 children (range, 238–8975) were followed for 36 181 person-years. At ART initiation, most children were underweight (50%) and stunted (66%). Lower baseline WAZ, HAZ, and WHZ were the most important determinants of faster catch-up growth on ART. WAZ and WHZ increased rapidly in the first year and stagnated or reversed thereafter, whereas HAZ increased continuously over time. Three years after starting ART, WAZ ranged from −2.80 (95% confidence interval [CI]: −3.66 to −2.02) to −1.98 (95% CI: −2.41 to −1.48) in children with a baseline z score < −3 and from −0.79 (95% CI: −1.62 to 0.02) to 0.05 (95% CI: −0.42 to 0.51) in children with a baseline WAZ ≥ −1. For HAZ, the corresponding range was −2.33 (95% CI: −2.62 to −2.02) to −1.27 (95% CI: −1.58 to −1.00) for baseline HAZ < −3 and −0.24 (95% CI: −0.56 to 0.15) to 0.84 (95% CI: 0.53 to 1.16) for HAZ ≥ −1.
CONCLUSIONS
Despite a sustained growth response and catch-up growth in children with advanced HIV disease treated with ART, normal weights and heights are not achieved over 3 years of ART.
Journal Article > ResearchFull Text
PLOS Med. 9 September 2014; Volume 11 (Issue 9); e1001718.; DOI:10.1371/journal.pmed.1001718
Boulle AM, Schomaker M, May MT, Hogg RS, Shepherd B, et al.
PLOS Med. 9 September 2014; Volume 11 (Issue 9); e1001718.; DOI:10.1371/journal.pmed.1001718
BACKGROUND
High early mortality in patients with HIV-1 starting antiretroviral therapy (ART) in sub-Saharan Africa, compared to Europe and North America, is well documented. Longer-term comparisons between settings have been limited by poor ascertainment of mortality in high burden African settings. This study aimed to compare mortality up to four years on ART between South Africa, Europe, and North America.
METHODS AND FINDINGS
Data from four South African cohorts in which patients lost to follow-up (LTF) could be linked to the national population register to determine vital status were combined with data from Europe and North America. Cumulative mortality, crude and adjusted (for characteristics at ART initiation) mortality rate ratios (relative to South Africa), and predicted mortality rates were described by region at 0–3, 3–6, 6–12, 12–24, and 24–48 months on ART for the period 2001–2010. Of the adults included (30,467 [South Africa], 29,727 [Europe], and 7,160 [North America]), 20,306 (67%), 9,961 (34%), and 824 (12%) were women. Patients began treatment with markedly more advanced disease in South Africa (median CD4 count 102, 213, and 172 cells/µl in South Africa, Europe, and North America, respectively). High early mortality after starting ART in South Africa occurred mainly in patients starting ART with CD4 count <50 cells/µl. Cumulative mortality at 4 years was 16.6%, 4.7%, and 15.3% in South Africa, Europe, and North America, respectively. Mortality was initially much lower in Europe and North America than South Africa, but the differences were reduced or reversed (North America) at longer durations on ART (adjusted rate ratios 0.46, 95% CI 0.37–0.58, and 1.62, 95% CI 1.27–2.05 between 24 and 48 months on ART comparing Europe and North America to South Africa). While bias due to under-ascertainment of mortality was minimised through death registry linkage, residual bias could still be present due to differing approaches to and frequency of linkage.
CONCLUSIONS
After accounting for under-ascertainment of mortality, with increasing duration on ART, the mortality rate on HIV treatment in South Africa declines to levels comparable to or below those described in participating North American cohorts, while substantially narrowing the differential with the European cohorts.
High early mortality in patients with HIV-1 starting antiretroviral therapy (ART) in sub-Saharan Africa, compared to Europe and North America, is well documented. Longer-term comparisons between settings have been limited by poor ascertainment of mortality in high burden African settings. This study aimed to compare mortality up to four years on ART between South Africa, Europe, and North America.
METHODS AND FINDINGS
Data from four South African cohorts in which patients lost to follow-up (LTF) could be linked to the national population register to determine vital status were combined with data from Europe and North America. Cumulative mortality, crude and adjusted (for characteristics at ART initiation) mortality rate ratios (relative to South Africa), and predicted mortality rates were described by region at 0–3, 3–6, 6–12, 12–24, and 24–48 months on ART for the period 2001–2010. Of the adults included (30,467 [South Africa], 29,727 [Europe], and 7,160 [North America]), 20,306 (67%), 9,961 (34%), and 824 (12%) were women. Patients began treatment with markedly more advanced disease in South Africa (median CD4 count 102, 213, and 172 cells/µl in South Africa, Europe, and North America, respectively). High early mortality after starting ART in South Africa occurred mainly in patients starting ART with CD4 count <50 cells/µl. Cumulative mortality at 4 years was 16.6%, 4.7%, and 15.3% in South Africa, Europe, and North America, respectively. Mortality was initially much lower in Europe and North America than South Africa, but the differences were reduced or reversed (North America) at longer durations on ART (adjusted rate ratios 0.46, 95% CI 0.37–0.58, and 1.62, 95% CI 1.27–2.05 between 24 and 48 months on ART comparing Europe and North America to South Africa). While bias due to under-ascertainment of mortality was minimised through death registry linkage, residual bias could still be present due to differing approaches to and frequency of linkage.
CONCLUSIONS
After accounting for under-ascertainment of mortality, with increasing duration on ART, the mortality rate on HIV treatment in South Africa declines to levels comparable to or below those described in participating North American cohorts, while substantially narrowing the differential with the European cohorts.
Journal Article > ResearchAbstract
J Acquir Immune Defic Syndr. 22 January 2013; Volume 63 (Issue 1); DOI:10.1097/QAI.0b013e318287c1fe
Hoffman CJ, Schomaker M, Fox MP, Mutevedzi, Giddy J, et al.
J Acquir Immune Defic Syndr. 22 January 2013; Volume 63 (Issue 1); DOI:10.1097/QAI.0b013e318287c1fe
In many resource-limited settings monitoring of combination antiretroviral therapy (cART) is based on the current CD4 count, with limited access to HIV RNA tests or laboratory diagnostics. We examined whether the CD4 count slope over 6 months could provide additional prognostic information.
Journal Article > ResearchFull Text
J Acquir Immune Defic Syndr. 1 August 2010; Volume 54 (Issue 5); DOI:10.1097/QAI.0b013e3181e0c4cf
Fenner L, Brinkhof MW, Keiser O, Weigel R, Cornell M, et al.
J Acquir Immune Defic Syndr. 1 August 2010; Volume 54 (Issue 5); DOI:10.1097/QAI.0b013e3181e0c4cf
BACKGROUND: Many HIV-infected children in Southern Africa have been started on antiretroviral therapy (ART), but loss to follow up (LTFU) can be substantial. We analyzed mortality in children retained in care and in all children starting ART, taking LTFU into account. PATIENTS AND METHODS: Children who started ART before the age of 16 years in 10 ART programs in South Africa, Malawi, Mozambique, and Zimbabwe were included. Risk factors for death in the first year of ART were identified in Weibull models. A meta-analytic approach was used to estimate cumulative mortality at 1 year. RESULTS: Eight thousand two hundred twenty-five children (median age 49 months, median CD4 cell percent 11.6%) were included; 391 (4.8%) died and 523 (7.0%) were LTFU in the first year. Mortality at 1 year was 4.5% [95% confidence interval (CI): 2.8% to 7.4%] in children remaining in care, but 8.7% (5.4% to 12.1%) at the program level, after taking mortality in children and LTFU into account. Factors associated with mortality in children remaining in care included age [adjusted hazard ratio (HR) 0.37; 95% CI: 0.25 to 0.54 comparing > or =120 months with <18 months], CD4 cell percent (HR: 0.56; 95% CI: 0.39 to 0.78 comparing > or =20% with <10%), and clinical stage (HR: 0.12; 95% CI: 0.03 to 0.45 comparing World Health Organization stage I with III/IV). CONCLUSIONS: In children starting ART and remaining in care in Southern Africa mortality at 1 year is <5% but almost twice as high at the program level, when taking LTFU into account. Age, CD4 percentage, and clinical stage are important predictors of mortality at the individual level.
Journal Article > ResearchFull Text
AIDS. 10 September 2009; Volume 23 (Issue 14); 1867-74.; DOI:10.1097/QAD.0b013e32832e05b2
Keiser O, Tweya H, Boulle AM, Braitstein P, Schechter M, et al.
AIDS. 10 September 2009; Volume 23 (Issue 14); 1867-74.; DOI:10.1097/QAD.0b013e32832e05b2
BACKGROUND
In high-income countries, viral load is routinely measured to detect failure of antiretroviral therapy (ART) and guide switching to second-line ART. Viral load monitoring is not generally available in resource-limited settings. We examined switching from nonnucleoside reverse transcriptase inhibitor (NNRTI)-based first-line regimens to protease inhibitor-based regimens in Africa, South America and Asia.
DESIGN AND METHODS
Multicohort study of 17 ART programmes. All sites monitored CD4 cell count and had access to second-line ART and 10 sites monitored viral load. We compared times to switching, CD4 cell counts at switching and obtained adjusted hazard ratios for switching (aHRs) with 95% confidence intervals (CIs) from random-effects Weibull models.
RESULTS
A total of 20 113 patients, including 6369 (31.7%) patients from 10 programmes with access to viral load monitoring, were analysed; 576 patients (2.9%) switched. Low CD4 cell counts at ART initiation were associated with switching in all programmes. Median time to switching was 16.3 months [interquartile range (IQR) 10.1-26.6] in programmes with viral load monitoring and 21.8 months (IQR 14.0-21.8) in programmes without viral load monitoring (P < 0.001). Median CD4 cell counts at switching were 161 cells/microl (IQR 77-265) in programmes with viral load monitoring and 102 cells/microl (44-181) in programmes without viral load monitoring (P < 0.001). Switching was more common in programmes with viral load monitoring during months 7-18 after starting ART (aHR 1.38; 95% CI 0.97-1.98), similar during months 19-30 (aHR 0.97; 95% CI 0.58-1.60) and less common during months 31-42 (aHR 0.29; 95% CI 0.11-0.79).
CONCLUSION
In resource-limited settings, switching to second-line regimens tends to occur earlier and at higher CD4 cell counts in ART programmes with viral load monitoring compared with programmes without viral load monitoring.
In high-income countries, viral load is routinely measured to detect failure of antiretroviral therapy (ART) and guide switching to second-line ART. Viral load monitoring is not generally available in resource-limited settings. We examined switching from nonnucleoside reverse transcriptase inhibitor (NNRTI)-based first-line regimens to protease inhibitor-based regimens in Africa, South America and Asia.
DESIGN AND METHODS
Multicohort study of 17 ART programmes. All sites monitored CD4 cell count and had access to second-line ART and 10 sites monitored viral load. We compared times to switching, CD4 cell counts at switching and obtained adjusted hazard ratios for switching (aHRs) with 95% confidence intervals (CIs) from random-effects Weibull models.
RESULTS
A total of 20 113 patients, including 6369 (31.7%) patients from 10 programmes with access to viral load monitoring, were analysed; 576 patients (2.9%) switched. Low CD4 cell counts at ART initiation were associated with switching in all programmes. Median time to switching was 16.3 months [interquartile range (IQR) 10.1-26.6] in programmes with viral load monitoring and 21.8 months (IQR 14.0-21.8) in programmes without viral load monitoring (P < 0.001). Median CD4 cell counts at switching were 161 cells/microl (IQR 77-265) in programmes with viral load monitoring and 102 cells/microl (44-181) in programmes without viral load monitoring (P < 0.001). Switching was more common in programmes with viral load monitoring during months 7-18 after starting ART (aHR 1.38; 95% CI 0.97-1.98), similar during months 19-30 (aHR 0.97; 95% CI 0.58-1.60) and less common during months 31-42 (aHR 0.29; 95% CI 0.11-0.79).
CONCLUSION
In resource-limited settings, switching to second-line regimens tends to occur earlier and at higher CD4 cell counts in ART programmes with viral load monitoring compared with programmes without viral load monitoring.