Determinants of Progression of HIV Infection in a Greek Hemophilia Cohort Followed for Up to 16 Years After Seroconversion

Touloumi, Giota; Karafoulidou, Anastasia; Gialeraki, A.; Κατσαρού, Όλγα; I, Milona; Kapsimali,; Mandalaki, T.; Hatzakis, Angelos

doi:10.1097/00042560-199809010-00014

Cited by 27 publications

(19 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The older age in an HIV-infected individual has been found in several studies to be correlated with rapid disease progression. 31,32 Our analysis also showed that older age was associated with shorter time to the AIDS progression and survival. Survival was shorter among men than women but did not differ in the time to AIDS progression.…”

Section: Discussionsupporting

confidence: 56%

Effect of Tuberculosis Preventive Therapy on HIV Disease Progression and Survival in HIV-Infected Adults

Lim

Okwera²,

Mayanja‐Kizza

et al. 2006

HIV Clinical Trials

View full text Add to dashboard Cite

Purpose: To determine whether tuberculosis (TB) preventive therapies alter the rate of disease progression to AIDS or death and to identify significant prognostic factors for HIV disease progression to AIDS. Method:In a randomized placebo-controlled trial in Kampala, Uganda, 2,736 purified protein derivative (PPD)-positive and anergic HIV-infected adults were randomly assigned to four and two regimens, respectively. PPD-positive patients were treated with isoniazid (INH) for 6 months (6H; n = 536), INH plus rifampicin for 3 months (3HR; n = 556), INH plus rifampicin plus pyrazinamide for 3 months (3HRZ; n = 462), or placebo for 6 months (n = 464). Anergic participants were treated with 6H (n = 395) or placebo (n = 323).Results: During follow-up, 404 cases progressed to AIDS and 577 deaths occurred. The cumulative incidence of the AIDS progression was greater in the anergic cohort compared to the PPD-positive cohort (p < .0001). Among PPD-positive patients, the relative risk of the AIDS progression with INH alone was 0.95 (95% CI 0.68-1.32); with 3HR it was 0.83 (95% CI 0.59-1.17); and with 3HRZ it was 0.76 (95% CI 0.52-1.08), controlling for significant baseline predictors. Among anergic patients, the relative risk of the AIDS progression was 0.81 (95% CI 0.56-1.15). Survival was greater in the PPD-positive cohort compared to the anergic cohort (p = . 0001). Conclusion:The number of signs or symptoms at baseline and anergic status are associated with increasing morbidity and mortality. Even though the tuberculosis preventive therapies were effective in reducing the incidence of TB for HIV-infected adults, their benefit of delaying HIV disease progression to AIDS was not observed. There is now the promise for greater access to antiretroviral medications. These medications must be properly used to maximize benefit and minimize untoward, adverse effects. Although recommendations have been developed and the availability of new antiretroviral drugs has expanded treatment choices, 7 this does not take into account the technology void in many developing countries. To make informed decisions about when to start treatment, what therapy to start with, and how to monitor the response to treatment, health care practitioners need more details about the natural history of HIV infection. Few studies have addressed disease progression in sub-Saharan Africa, where over 65% of the world's 39.4 million infected adults and children live. 7 In Uganda, the prevalence of HIV infection in adults is estimated at 8% in rural areas and up to 40% in some rural areas and trading centers. 8,9 The cumulative progression to AIDS at 1, 3, and 5 years after seroconversion is 2%, 6%, and 22%, respectively. The median survival time after the onset of AIDS is 9.3 months. 10 Although the recent declines in morbidity and mortality due to HIV/AIDS are attributable to the use of more intensive antiretroviral therapies, 3,4 the availability of antiretroviral drugs is limited in developing countries. Even as the antiretroviral therapy rolls out i...

show abstract

Section: Discussionsupporting

confidence: 56%

Effect of Tuberculosis Preventive Therapy on HIV Disease Progression and Survival in HIV-Infected Adults

Lim

Okwera²,

Mayanja‐Kizza

et al. 2006

HIV Clinical Trials

View full text Add to dashboard Cite

show abstract

“…Due to the late entry of infected individuals into HIV diagnosis programs, the authors hypothesize that the very high number of AIDS deaths and the very short survival time for individuals after HIV infection in Nigeria and in most of sub-Saharan Africa could be attributed to the fact that the majority of these patients access health care late during the course of natural HIV infection. The median time from seroconversion to AIDS in industrialized countries is far longer than is suggested in this study and other studies from Africa [32,33,34,35], which in the past has been taken as evidence of rapid progression of the disease in Africa, as a high proportion of Africans infected with HIV-1 die sooner after HIV diagnosis than their counterparts in industrialized countries. This, however, does not seem to be the case.…”

Section: Discussioncontrasting

confidence: 51%

Estimating the time period between infection and diagnosis based on CD4+ counts at first diagnosis among HIV-1 antiretroviral naïve patients in Nigeria

Forbi¹,

Forbi²,

Agwale³

2010

J Infect Dev Ctries

View full text Add to dashboard Cite

Introduction: CD4 + T-cell levels are an important criterion for categorizing HIV-related clinical conditions. Late diagnosis of infection contributes to poor medical outcomes and the continuation of viral transmission. This population-based cohort study in north central Nigeria reports the initial CD4 + lymphocyte counts at the time of first HIV diagnosis and determines the approximate time interval when HIV infection was acquired.. Methodology: Confirmed HIV-1 infected individuals (n = 588) for whom the dates of first HIV diagnosis were known were enrolled in this study. CD4 + lymphocyte counts were measured using a Fluorescence Activated Cell Sorter (FACS) platform that automatically quantifies CD4 + lymphocytes as absolute numbers of lymphocytes per μL of blood. The estimated time interval between HIV infection and time of first HIV diagnosis was determined as a function of the CD4 + lymphocytes' decay rate per calendar year. Results: The results showed that 22.1% and 49.7% of HIV-infected individuals present late with advanced (CD4

show abstract

“…To illustrate the issue, data on CD4 cell counts from the Greek Haemophilia Cohort Study (GHCS) will be used. A total of 158 HIV-infected hemophiliac men with known seroconversion (SC) dates were enrolled in the GHCS and followed prospectively [31]. Clinical information and data on laboratory parameters were to be collected every 6 months.…”

Section: Missing Data In Hiv-1 Studies: the Greek Haemophilia Cohort mentioning

confidence: 99%

Impact of missing data due to drop‐outs on estimators for rates of change in longitudinal studies: a simulation study

Touloumi

Babiker

Pocock

et al. 2001

Statistics in Medicine

View full text Add to dashboard Cite

Many cohort studies and clinical trials are designed to compare rates of change over time in one or more disease markers in several groups. One major problem in such longitudinal studies is missing data due to patient drop-out. The bias and efficiency of six different methods to estimate rates of changes in longitudinal studies with incomplete observations were compared: generalized estimating equation estimates (GEE) proposed by Liang and Zeger (1986); unweighted average of ordinary least squares (OLSE) of individual rates of change (UWLS); weighted average of OLSE (WLS); conditional linear model estimates (CLE), a covariate type estimates proposed by Wu and Bailey (1989); random effect (RE), and joint multivariate RE (JMRE) estimates. The latter method combines a linear RE model for the underlying pattern of the marker with a log-normal survival model for informative drop-out process. The performance of these methods in the presence of missing data completely at random (MCAR), at random (MAR) and non-ignorable (NIM) were compared in simulation studies. Data for the disease marker were generated under the linear random effects model with parameter values derived from realistic examples in HIV infection. Rates of drop-out, assumed to increase over time, were allowed to be independent of marker values or to depend either only on previous marker values or on both previous and current marker values. Under MACR all six methods yielded unbiased estimates of both group mean rates and between-group difference. However, the cross-sectional view of the data in the GEE method resulted in seriously biased estimates under MAR and NIM drop-out process. The bias in the estimates ranged from 30 per cent to 50 per cent. The degree of bias in the GEE estimates increases with the severity of non-randomness and with the proportion of MAR data. Under MCAR and MAR all the other five methods performed relatively well. RE and JMRE estimates were more efficient(that is, had smaller variance) than UWLS, WLS and CL estimates. Under NIM, WLS and particularly RE estimates tended to underestimate the average rate of marker change (bias approximately 10 per cent). Under NIM, UWLS, CL and JMRE performed better in terms of bias (3-5 per cent) with the JMRE giving the most efficient estimates. Given that markers are key variables related to disease progression, missing marker data are likely to be at least MAR. Thus, the GEE method may not be appropriate for analysing such longitudinal marker data. The potential biases due to incomplete data require greater recognition in reports of longitudinal studies. Sensitivity analyses to assess the effect of drop-outs on inferences about the target parameters are important.

show abstract

Determinants of Progression of HIV Infection in a Greek Hemophilia Cohort Followed for Up to 16 Years After Seroconversion

Cited by 27 publications

References 38 publications

Effect of Tuberculosis Preventive Therapy on HIV Disease Progression and Survival in HIV-Infected Adults

Effect of Tuberculosis Preventive Therapy on HIV Disease Progression and Survival in HIV-Infected Adults

Estimating the time period between infection and diagnosis based on CD4+ counts at first diagnosis among HIV-1 antiretroviral naïve patients in Nigeria

Impact of missing data due to drop‐outs on estimators for rates of change in longitudinal studies: a simulation study

Contact Info

Product

Resources

About