Journal Article > ResearchFull Text
Journal of the American Medical Association (JAMA). 21 July 2010; Volume 304 (Issue 3); DOI:10.1001/jama.2010.980
Pujades-Rodríguez M, Balkan S, Arnould L, Brinkhof MW, Calmy A
Journal of the American Medical Association (JAMA). 21 July 2010; Volume 304 (Issue 3); DOI:10.1001/jama.2010.980
CONTEXT
Long-term antiretroviral therapy (ART) use in resource-limited countries leads to increasing numbers of patients with HIV taking second-line therapy. Limited access to further therapeutic options makes essential the evaluation of second-line regimen efficacy in these settings.
OBJECTIVES
To investigate failure rates in patients receiving second-line therapy and factors associated with failure and death.
DESIGN, SETTING, AND PARTICIPANTS
Multicohort study of 632 patients > 14 years old receiving second-line therapy for more than 6 months in 27 ART programs in Africa and Asia between January 2001 and October 2008.
MAIN OUTCOME MEASURES
Clinical, immunological, virological, and immunovirological failure (first diagnosed episode of immunological or virological failure) rates, and mortality after 6 months of second-line therapy use. Sensitivity analyses were performed using alternative CD4 cell count thresholds for immunological and immunovirological definitions of failure and for cohort attrition instead of death.
RESULTS
The 632 patients provided 740.7 person-years of follow-up; 119 (18.8%) met World Health Organization failure criteria after a median 11.9 months following the start of second-line therapy (interquartile range [IQR], 8.7-17.0 months), and 34 (5.4%) died after a median 15.1 months (IQR, 11.9-25.7 months). Failure rates were lower in those who changed 2 nucleoside reverse transcriptase inhibitors (NRTIs) instead of 1 (179.2 vs 251.6 per 1000 person-years; incidence rate ratio [IRR], 0.64; 95% confidence interval [CI], 0.42-0.96), and higher in those with lowest adherence index (383.5 vs 176.0 per 1000 person-years; IRR, 3.14; 95% CI, 1.67-5.90 for < 80% vs > or = 95% [percentage adherent, as represented by percentage of appointments attended with no delay]). Failure rates increased with lower CD4 cell counts when second-line therapy was started, from 156.3 vs 96.2 per 1000 person-years; IRR, 1.59 (95% CI, 0.78-3.25) for 100 to 199/microL to 336.8 per 1000 person-years; IRR, 3.32 (95% CI, 1.81-6.08) for less than 50/microL vs 200/microL or higher; and decreased with time using second-line therapy, from 250.0 vs 123.2 per 1000 person-years; IRR, 1.90 (95% CI, 1.19-3.02) for 6 to 11 months to 212.0 per 1000 person-years; 1.71 (95% CI, 1.01-2.88) for 12 to 17 months vs 18 or more months. Mortality for those taking second-line therapy was lower in women (32.4 vs 68.3 per 1000 person-years; hazard ratio [HR], 0.45; 95% CI, 0.23-0.91); and higher in patients with treatment failure of any type (91.9 vs 28.1 per 1000 person-years; HR, 2.83; 95% CI, 1.38-5.80). Sensitivity analyses showed similar results.
CONCLUSIONS
Among patients in Africa and Asia receiving second-line therapy for HIV, treatment failure was associated with low CD4 cell counts at second-line therapy start, use of suboptimal second-line regimens, and poor adherence. Mortality was associated with diagnosed treatment failure.
Long-term antiretroviral therapy (ART) use in resource-limited countries leads to increasing numbers of patients with HIV taking second-line therapy. Limited access to further therapeutic options makes essential the evaluation of second-line regimen efficacy in these settings.
OBJECTIVES
To investigate failure rates in patients receiving second-line therapy and factors associated with failure and death.
DESIGN, SETTING, AND PARTICIPANTS
Multicohort study of 632 patients > 14 years old receiving second-line therapy for more than 6 months in 27 ART programs in Africa and Asia between January 2001 and October 2008.
MAIN OUTCOME MEASURES
Clinical, immunological, virological, and immunovirological failure (first diagnosed episode of immunological or virological failure) rates, and mortality after 6 months of second-line therapy use. Sensitivity analyses were performed using alternative CD4 cell count thresholds for immunological and immunovirological definitions of failure and for cohort attrition instead of death.
RESULTS
The 632 patients provided 740.7 person-years of follow-up; 119 (18.8%) met World Health Organization failure criteria after a median 11.9 months following the start of second-line therapy (interquartile range [IQR], 8.7-17.0 months), and 34 (5.4%) died after a median 15.1 months (IQR, 11.9-25.7 months). Failure rates were lower in those who changed 2 nucleoside reverse transcriptase inhibitors (NRTIs) instead of 1 (179.2 vs 251.6 per 1000 person-years; incidence rate ratio [IRR], 0.64; 95% confidence interval [CI], 0.42-0.96), and higher in those with lowest adherence index (383.5 vs 176.0 per 1000 person-years; IRR, 3.14; 95% CI, 1.67-5.90 for < 80% vs > or = 95% [percentage adherent, as represented by percentage of appointments attended with no delay]). Failure rates increased with lower CD4 cell counts when second-line therapy was started, from 156.3 vs 96.2 per 1000 person-years; IRR, 1.59 (95% CI, 0.78-3.25) for 100 to 199/microL to 336.8 per 1000 person-years; IRR, 3.32 (95% CI, 1.81-6.08) for less than 50/microL vs 200/microL or higher; and decreased with time using second-line therapy, from 250.0 vs 123.2 per 1000 person-years; IRR, 1.90 (95% CI, 1.19-3.02) for 6 to 11 months to 212.0 per 1000 person-years; 1.71 (95% CI, 1.01-2.88) for 12 to 17 months vs 18 or more months. Mortality for those taking second-line therapy was lower in women (32.4 vs 68.3 per 1000 person-years; hazard ratio [HR], 0.45; 95% CI, 0.23-0.91); and higher in patients with treatment failure of any type (91.9 vs 28.1 per 1000 person-years; HR, 2.83; 95% CI, 1.38-5.80). Sensitivity analyses showed similar results.
CONCLUSIONS
Among patients in Africa and Asia receiving second-line therapy for HIV, treatment failure was associated with low CD4 cell counts at second-line therapy start, use of suboptimal second-line regimens, and poor adherence. Mortality was associated with diagnosed treatment failure.
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.
Journal Article > ResearchFull Text
PLOS Med. 1 January 2011; Volume 8 (Issue 1); DOI:10.1371/journal.pmed.1000390
Egger M, Sidle J, Weigel R, Geng EH, Fox MP, et al.
PLOS Med. 1 January 2011; Volume 8 (Issue 1); DOI:10.1371/journal.pmed.1000390
The World Health Organization estimates that in sub-Saharan Africa about 4 million HIV-infected patients had started antiretroviral therapy (ART) by the end of 2008. Loss of patients to follow-up and care is an important problem for treatment programmes in this region. As mortality is high in these patients compared to patients remaining in care, ART programmes with high rates of loss to follow-up may substantially underestimate mortality of all patients starting ART.
Journal Article > ResearchFull Text
PLOS Med. 8 July 2008; Volume 5 (Issue 7); DOI:10.1371/journal.pmed.0050148
Keiser O, Orrell C, Egger M, Wood R, Brinkhof MW, et al.
PLOS Med. 8 July 2008; Volume 5 (Issue 7); DOI:10.1371/journal.pmed.0050148
BACKGROUND: The provision of highly active antiretroviral therapy (HAART) in resource-limited settings follows a public health approach, which is characterised by a limited number of regimens and the standardisation of clinical and laboratory monitoring. In industrialized countries doctors prescribe from the full range of available antiretroviral drugs, supported by resistance testing and frequent laboratory monitoring. We compared virologic response, changes to first-line regimens, and mortality in HIV-infected patients starting HAART in South Africa and Switzerland. METHODS AND FINDINGS: We analysed data from the Swiss HIV Cohort Study and two HAART programmes in townships of Cape Town, South Africa. We included treatment-naïve patients aged 16 y or older who had started treatment with at least three drugs since 2001, and excluded intravenous drug users. Data from a total of 2,348 patients from South Africa and 1,016 patients from the Swiss HIV Cohort Study were analysed. Median baseline CD4+ T cell counts were 80 cells/mul in South Africa and 204 cells/mul in Switzerland. In South Africa, patients started with one of four first-line regimens, which was subsequently changed in 514 patients (22%). In Switzerland, 36 first-line regimens were used initially, and these were changed in 539 patients (53%). In most patients HIV-1 RNA was suppressed to 500 copies/ml or less within one year: 96% (95% confidence interval [CI] 95%-97%) in South Africa and 96% (94%-97%) in Switzerland, and 26% (22%-29%) and 27% (24%-31%), respectively, developed viral rebound within two years. Mortality was higher in South Africa than in Switzerland during the first months of HAART: adjusted hazard ratios were 5.90 (95% CI 1.81-19.2) during months 1-3 and 1.77 (0.90-3.50) during months 4-24. CONCLUSIONS: Compared to the highly individualised approach in Switzerland, programmatic HAART in South Africa resulted in similar virologic outcomes, with relatively few changes to initial regimens. Further innovation and resources are required in South Africa to both achieve more timely access to HAART and improve the prognosis of patients who start HAART with advanced disease.
Journal Article > ResearchFull Text
PLOS One. 4 June 2009; Volume 4 (Issue 6); DOI:10.1371/journal.pone.0005790
Brinkhof MW, Pujades-Rodriguez M, Egger M
PLOS One. 4 June 2009; Volume 4 (Issue 6); DOI:10.1371/journal.pone.0005790
BACKGROUND: The retention of patients in antiretroviral therapy (ART) programmes is an important issue in resource-limited settings. Loss to follow up can be substantial, but it is unclear what the outcomes are in patients who are lost to programmes. METHODS AND FINDINGS: We searched the PubMed, EMBASE, Latin American and Caribbean Health Sciences Literature (LILACS), Indian Medlars Centre (IndMed) and African Index Medicus (AIM) databases and the abstracts of three conferences for studies that traced patients lost to follow up to ascertain their vital status. Main outcomes were the proportion of patients traced, the proportion found to be alive and the proportion that had died. Where available, we also examined the reasons why some patients could not be traced, why patients found to be alive did not return to the clinic, and the causes of death. We combined mortality data from several studies using random-effects meta-analysis. Seventeen studies were eligible. All were from sub-Saharan Africa, except one study from India, and none were conducted in children. A total of 6420 patients (range 44 to 1343 patients) were included. Patients were traced using telephone calls, home visits and through social networks. Overall the vital status of 4021 patients could be ascertained (63%, range across studies: 45% to 86%); 1602 patients had died. The combined mortality was 40% (95% confidence interval 33%-48%), with substantial heterogeneity between studies (P<0.0001). Mortality in African programmes ranged from 12% to 87% of patients lost to follow-up. Mortality was inversely associated with the rate of loss to follow up in the programme: it declined from around 60% to 20% as the percentage of patients lost to the programme increased from 5% to 50%. Among patients not found, telephone numbers and addresses were frequently incorrect or missing. Common reasons for not returning to the clinic were transfer to another programme, financial problems and improving or deteriorating health. Causes of death were available for 47 deaths: 29 (62%) died of an AIDS defining illness. CONCLUSIONS: In ART programmes in resource-limited settings a substantial minority of adults lost to follow up cannot be traced, and among those traced 20% to 60% had died. Our findings have implications both for patient care and the monitoring and evaluation of programmes.