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1.
J Acquir Immune Defic Syndr ; 57(4): 305-10, 2011 Aug 01.
Article in English | MEDLINE | ID: mdl-21423024

ABSTRACT

OBJECTIVE: To evaluate the short-term and long-term effects of highly active antiretroviral therapy (HAART) on tuberculosis (TB) risk compared with risk without HAART in a low TB incidence setting. DESIGN: An observational cohort study among HIV-infected persons in care at the Comprehensive Care Center (Nashville, TN) between January 1998 and December 2008. METHODS: A marginal structural model was used to estimate the effect of HAART on short-term (≤180 days) and long-term (>180 days) TB risk, with CD4⁺ lymphocyte count incorporated as a time-updated covariate. RESULTS: Of 4534 HIV-infected patients, 34 developed TB (165 per 100,000 person-years; 20,581 person-years of follow-up). Seventeen cases occurred among persons not on HAART or >30 days after HAART discontinuation (212 per 100,000 person-years; 8019 person-years of follow-up). Seventeen occurred among persons on HAART (135 per 100,000 person-years; 12,562 person-years of follow-up); 10 in the first 180 days (402 per 100,000 person-years; 2489 person-years of follow-up); and 7 after more than 180 days (69 per 100,000 person-years; 10,073 person-years of follow-up). After adjusting for the most recent CD4⁺ lymphocyte count, the risk of TB in the first 180 days of HAART exposure relative to no HAART was 0.68 (0.14-3.22, P = 0.63). CONCLUSIONS: In this low TB incidence setting, the TB rate in the first 180 days of HAART was almost twice as high as persons not on HAART. However, after adjusting for most recent CD4⁺ count, there was no significant difference in TB risk between these 2 groups. This suggests that low recent CD4⁺ lymphocyte count influences TB risk during the first 180 days of HAART.


Subject(s)
Anti-HIV Agents/adverse effects , Anti-HIV Agents/therapeutic use , Antiretroviral Therapy, Highly Active , HIV Infections/complications , HIV Infections/drug therapy , Tuberculosis/complications , Adult , CD4 Lymphocyte Count , Cohort Studies , Female , HIV Infections/immunology , Humans , Incidence , Male , Risk Factors , Tennessee/epidemiology , Tuberculosis/epidemiology
2.
J Infect Dis ; 199(7): 991-8, 2009 Apr 01.
Article in English | MEDLINE | ID: mdl-19220139

ABSTRACT

BACKGROUND: There are conflicting data regarding race, sex, and mortality among persons infected with human immunodeficiency virus (HIV). We studied all-cause mortality among persons in care during the highly-active antiretroviral therapy (HAART) era. METHODS: This retrospective cohort study included patients who made>or=1 clinic visit from January 1998 through December 2005. RESULTS: Of 2605 patients (with 6657 person-years of follow-up), 38% were black and 24% were female. The percentage of time in care while receiving HAART was lower for blacks than for nonblacks (47% vs. 76%; P<.001) and for females than for males (57% vs. 71%; P=.01). There were 253 deaths (38 per 1000 person-years). After adjustment for characteristics at baseline, death was associated with black race (hazard ratio [HR], 1.33; P .04), female sex (HR, 1.53; P .007), injection drug use (IDU) as a risk factor for HIV infection (HR, 1.61; P .009), older age (HR, 1.45 per 10 years; P<.001), a lower CD4 cell count (HR, 0.59 for 200 vs. 350 cells/mm3; P<.001) and a higher HIV type 1 RNA level (HR, 1.35; P<.001). After adjustment for the length of time that HAART was received, black race (HR, 1.00; P .99) and IDU (HR, 1.37; P .09) were no longer associated with death, but female sex was (HR, 1.62; P=.002). CONCLUSIONS: Race-associated differences in mortality likely resulted from HAART use. Women had an increased risk of death even after adjustment for HAART use. Addressing racial disparities will require improved HAART utilization. Increased mortality among women requires further study.


Subject(s)
Anti-HIV Agents/administration & dosage , Antiretroviral Therapy, Highly Active , HIV Infections/drug therapy , HIV Infections/mortality , Racial Groups , Adult , CD4 Lymphocyte Count , Cohort Studies , Female , HIV Infections/ethnology , Humans , Male , Multivariate Analysis , Proportional Hazards Models , Retrospective Studies , Sex Factors , Time Factors
3.
J Infect Dis ; 192(6): 950-7, 2005 Sep 15.
Article in English | MEDLINE | ID: mdl-16107946

ABSTRACT

BACKGROUND: The optimal timing of highly active antiretroviral therapy (HAART) in human immunodeficiency virus (HIV)-infected patients with > or = 200 absolute CD4 lymphocytes/mm3 is unknown. CD4 lymphocyte percentage could add prognostic information. METHODS: Persons who initiated HAART between 1 January 1998 and 1 January 2003, received > or = 30 days of therapy, and had baseline CD4 lymphocyte data available were included in the study. The log-rank test for time to event and Cox proportional hazards models were used to determine predictors of a new acquired immunodeficiency syndrome-defining illness or death. RESULTS: A total of 788 patients met the inclusion criteria. At baseline, subjects had a median of 225 CD4 lymphocytes/mm3 and 17% CD4 lymphocytes. Subjects with < 17% CD4 lymphocytes had earlier disease progression, compared with subjects with > or = 17%, both in the entire cohort (P<.0001) and of those subjects with > 350 absolute CD4 lymphocytes/mm3 at baseline (P=.03). CD4 lymphocyte percentage < 17% was the strongest predictor of disease progression among subjects in this latter group (hazard ratio, 3.57; P=.045). CONCLUSIONS: In this cohort, CD4 lymphocyte percentage predicted disease progression in HIV-infected subjects who initiated therapy with > 350 CD4 lymphocytes/mm3. This information may help identify persons who will derive the greatest benefit from initiation of HAART.


Subject(s)
Antiretroviral Therapy, Highly Active , CD4 Lymphocyte Count , CD4-Positive T-Lymphocytes , HIV Infections/immunology , HIV Infections/physiopathology , Adolescent , Adult , Aged , Cohort Studies , Disease Progression , Female , HIV Infections/diagnosis , HIV Infections/drug therapy , Humans , Lymphocyte Count , Male , Middle Aged , Prognosis , Proportional Hazards Models , Survival Analysis
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