35 research outputs found
Risk factors for death in HIV-infected adult african patients recieving anti-retroviral therapy
Objective: To determine risk factors for death in HIV-infected African patients on anti-retroviral therapy (ART).Design: Retrospective Case-control study.Setting: The MOH-USAID-AMPATH Partnership ambulatory HIV-care clinics in western Kenya.Results: Between November 2001 and December 2005 demographic, clinical and laboratory data from 527 deceased and 1054 living patients receiving ART were compared to determine independent risk factors for death. Median age at ART initiation was 38 versus 36 years for the deceased and living patients respectively (p<0.0148). Mediantime from enrollment at AMPATH to initiation of ART was two weeks for both groups while median time on ART was eight weeks for the deceased and fourty two weeks for the living (p<0.0001). Patients with CD4 cell counts <100/mm3 were more likely to die than those with counts >100/mm3 (HR=1.553. 95% CI (1.156, 2.087), p<0.003). Patientsattending rural clinics had threefold higher risk of dying compared to patients attending clinic at a tertiary referral hospital (p<0.0001). Two years after initiating treatment fifty percent of non-adherent patients were alive compared to 75% of adherent patients. Male gender, WHO Stage and haemoglobin level <10 grams% were associated with time to death while age, marital status, educational level, employment status andweight were not.Conclusion: Profoundly immunosuppressed patients were more likely to die early in the course of treatment. Also, patients receiving care in rural clinics were at greater risk of dying than those receiving care in the tertiary referral hospital
Chemokines in cerebrospinal fluid correlate with cerebral metabolite patterns in HIV-infected individuals
Chemokines influence HIV neuropathogenesis by affecting the HIV life cycle, trafficking of macrophages into the nervous system, glial activation, and neuronal signaling and repair processes; however, knowledge of their relationship to in vivo measures of cerebral injury is limited. The primary objective of this study was to determine the relationship between a panel of chemokines in cerebrospinal fluid (CSF) and cerebral metabolites measured by proton magnetic resonance spectroscopy (MRS) in a cohort of HIV-infected individuals. One hundred seventy-one stored CSF specimens were assayed from HIV-infected individuals who were enrolled in two ACTG studies that evaluated the relationship between neuropsychological performance and cerebral metabolites. Concentrations of six chemokines (fractalkine, IL-8, IP-10, MCP-1, MIP-1β, and SDF-1) were measured and compared with cerebral metabolites individually and as composite neuronal, basal ganglia, and inflammatory patterns. IP-10 and MCP-1 were the chemokines most strongly associated with individual cerebral metabolites. Specifically, (1) higher IP-10 levels correlated with lower N-acetyl aspartate (NAA)/creatine (Cr) ratios in the frontal white matter and higher MI/Cr ratios in all three brain regions considered and (2) higher MCP-1 levels correlated with lower NAA/Cr ratios in frontal white matter and the parietal cortex. IP-10, MCP-1, and IL-8 had the strongest associations with patterns of cerebral metabolites. In particular, higher levels of IP-10 correlated with lower neuronal pattern scores and higher basal ganglia and inflammatory pattern scores, the same pattern which has been associated with HIV-associated neurocognitive disorders (HAND). Subgroup analysis indicated that the effects of IP-10 and IL-8 were influenced by effective antiretroviral therapy and that memantine treatment may mitigate the neuronal effects of IP-10. This study supports the role of chemokines in HAND and the validity of MRS as an assessment tool. In particular, the findings identify relationships between the immune response—particularly an interferon-inducible chemokine, IP-10—and cerebral metabolites and suggest that antiretroviral therapy and memantine modify the impact of the immune response on neurons
Evaluation of Three Sampling Methods to Monitor Outcomes of Antiretroviral Treatment Programmes in Low- and Middle-Income Countries
BACKGROUND: Retention of patients on antiretroviral therapy (ART) over time is a proxy for quality of care and an outcome indicator to monitor ART programs. Using existing databases (Antiretroviral in Lower Income Countries of the International Databases to Evaluate AIDS and Médecins Sans Frontières), we evaluated three sampling approaches to simplify the generation of outcome indicators. METHODS AND FINDINGS: We used individual patient data from 27 ART sites and included 27,201 ART-naive adults (≥15 years) who initiated ART in 2005. For each site, we generated two outcome indicators at 12 months, retention on ART and proportion of patients lost to follow-up (LFU), first using all patient data and then within a smaller group of patients selected using three sampling methods (random, systematic and consecutive sampling). For each method and each site, 500 samples were generated, and the average result was compared with the unsampled value. The 95% sampling distribution (SD) was expressed as the 2.5(th) and 97.5(th) percentile values from the 500 samples. Overall, retention on ART was 76.5% (range 58.9-88.6) and the proportion of patients LFU, 13.5% (range 0.8-31.9). Estimates of retention from sampling (n = 5696) were 76.5% (SD 75.4-77.7) for random, 76.5% (75.3-77.5) for systematic and 76.0% (74.1-78.2) for the consecutive method. Estimates for the proportion of patients LFU were 13.5% (12.6-14.5), 13.5% (12.6-14.3) and 14.0% (12.5-15.5), respectively. With consecutive sampling, 50% of sites had SD within ±5% of the unsampled site value. CONCLUSIONS: Our results suggest that random, systematic or consecutive sampling methods are feasible for monitoring ART indicators at national level. However, sampling may not produce precise estimates in some sites
Comparison of Methods to Correct Survival Estimates and Survival Regression Analysis on a Large HIV African Cohort
The evaluation of HIV treatment programs is generally based on an estimation of survival among patients receiving antiretroviral treatment (ART). In large HIV programs, loss to follow-up (LFU) rates remain high despite active patient tracing, which is likely to bias survival estimates and survival regression analyses
Mortality of Patients Lost to Follow-Up in Antiretroviral Treatment Programmes in Resource-Limited Settings: Systematic Review and Meta-Analysis
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
Pitfalls of practicing cancer epidemiology in resource-limited settings: the case of survival and loss to follow-up after a diagnosis of Kaposi’s sarcoma in five countries across sub-Saharan Africa
Correcting Mortality for Loss to Follow-Up: A Nomogram Applied to Antiretroviral Treatment Programmes in Sub-Saharan Africa
Matthias Egger and colleagues present a nomogram and a web-based calculator to correct estimates of program-level mortality for loss to follow-up, for use in antiretroviral treatment programs
Estimating Loss to Follow-Up in HIV-Infected Patients on Antiretroviral Therapy: The Effect of the Competing Risk of Death in Zambia and Switzerland
BACKGROUND:
Loss to follow-up (LTFU) is common in antiretroviral therapy (ART) programmes. Mortality is a competing risk (CR) for LTFU; however, it is often overlooked in cohort analyses. We examined how the CR of death affected LTFU estimates in Zambia and Switzerland.
METHODS AND FINDINGS:
HIV-infected patients aged ≥18 years who started ART 2004-2008 in observational cohorts in Zambia and Switzerland were included. We compared standard Kaplan-Meier curves with CR cumulative incidence. We calculated hazard ratios for LTFU across CD4 cell count strata using cause-specific Cox models, or Fine and Gray subdistribution models, adjusting for age, gender, body mass index and clinical stage. 89,339 patients from Zambia and 1,860 patients from Switzerland were included. 12,237 patients (13.7%) in Zambia and 129 patients (6.9%) in Switzerland were LTFU and 8,498 (9.5%) and 29 patients (1.6%), respectively, died. In Zambia, the probability of LTFU was overestimated in Kaplan-Meier curves: estimates at 3.5 years were 29.3% for patients starting ART with CD4 cells <100 cells/µl and 15.4% among patients starting with ≥350 cells/µL. The estimates from CR cumulative incidence were 22.9% and 13.6%, respectively. Little difference was found between naïve and CR analyses in Switzerland since only few patients died. The results from Cox and Fine and Gray models were similar: in Zambia the risk of loss to follow-up and death increased with decreasing CD4 counts at the start of ART, whereas in Switzerland there was a trend in the opposite direction, with patients with higher CD4 cell counts more likely to be lost to follow-up.
CONCLUSIONS:
In ART programmes in low-income settings the competing risk of death can substantially bias standard analyses of LTFU. The CD4 cell count and other prognostic factors may be differentially associated with LTFU in low-income and high-income settings
Predictors of survival and functional outcomes in natalizumab-associated progressive multifocal leukoencephalopathy
Designs for clinical trials to test the efficacy of therapeutics in progressive multifocal leukoencephalopathy RID G-8810-2011
The design of a comparative treatment trial to evaluate the efficacy of therapeutics for progressive multifocal leukoencephalopathy (PML) is outlined. We propose a large simple randomized trial with patient survival as its primary endpoint, completed in a short period of time and involving a cohort with as few enrollment restrictions as possible. We use stratification as the counterweight to the lack of exclusion criteria and suggest that proper stratification will attenuate differences inherent in a heterogeneous subject cohort. Estimation of power, sample size, and study duration, implementation of interim analyses, toxicity management, and validation of secondary clinical measures are also addressed