18 research outputs found
Influence of Hepatitis C Virus Infection on HIV-1 Disease Progression and Response to Highly Active Antiretroviral Therapy
ObjectiveTo assess hepatitis C virus (HCV) antibody prevalence in the EuroSIDA cohort, along with survival, human immunodeficiency virus (HIV)-1 disease progression, virologic response (plasma HIV-1 RNA load of <500 copies/mL), and CD4 cell count recovery by HCV serostatus in patients initiating highly active antiretroviral therapy (HAART) ResultsHCV serostatus at or before enrollment was available for 5957 patients; 1960 (33%) and 3997 (67%) were HCV seropositive and seronegative, respectively. No association between an increased incidence of acquired immunodeficiency syndrome-defining illnesses or death and HCV serostatus was seen after adjustment for other prognostic risk factors known at baseline (adjusted incidence rate ratio [IRR], 0.97 [95% confidence interval {CI}, 0.81-1.16]). However, there was a large increase in the incidence of liver disease-related deaths in HCV-seropositive patients in adjusted models (IRR, 11.71 [95% CI, 6.42-21.34]). Among 2260 patients of known HCV serostatus initiating HAART, after adjustment, there was no significant difference between HCV-seropositive and -seronegative patients with respect to virologic response (relative hazard [RH], 1.13 [95% CI, 0.84-1.51]) and immunologic response, whether measured as a ⩾50% increase (RH, 0.94 [95% CI, 0.77-1.16]) or a ⩾50 cells/μL increase (RH, 0.92 [95% CI, 0.77-1.11]) in CD4 cell count after HAART initiation ConclusionsHCV serostatus did not affect the risk of HIV-1 disease progression, but the risk of liver disease-related deaths was markedly increased in HCV-seropositive patients. The overall virologic and immunologic responses to HAART were not affected by HCV serostatu
The association between serum biomarkers and disease outcome in influenza A(H1N1)pdm09 virus infection: results of two international observational cohort studies
BACKGROUND
Prospective studies establishing the temporal relationship between the degree of inflammation and human influenza disease progression are scarce. To assess predictors of disease progression among patients with influenza A(H1N1)pdm09 infection, 25 inflammatory biomarkers measured at enrollment were analyzed in two international observational cohort studies.
METHODS
Among patients with RT-PCR-confirmed influenza A(H1N1)pdm09 virus infection, odds ratios (ORs) estimated by logistic regression were used to summarize the associations of biomarkers measured at enrollment with worsened disease outcome or death after 14 days of follow-up for those seeking outpatient care (FLU 002) or after 60 days for those hospitalized with influenza complications (FLU 003). Biomarkers that were significantly associated with progression in both studies (p<0.05) or only in one (p<0.002 after Bonferroni correction) were identified.
RESULTS
In FLU 002 28/528 (5.3%) outpatients had influenza A(H1N1)pdm09 virus infection that progressed to a study endpoint of complications, hospitalization or death, whereas in FLU 003 28/170 (16.5%) inpatients enrolled from the general ward and 21/39 (53.8%) inpatients enrolled directly from the ICU experienced disease progression. Higher levels of 12 of the 25 markers were significantly associated with subsequent disease progression. Of these, 7 markers (IL-6, CD163, IL-10, LBP, IL-2, MCP-1, and IP-10), all with ORs for the 3(rd) versus 1(st) tertile of 2.5 or greater, were significant (p<0.05) in both outpatients and inpatients. In contrast, five markers (sICAM-1, IL-8, TNF-α, D-dimer, and sVCAM-1), all with ORs for the 3(rd) versus 1(st) tertile greater than 3.2, were significantly (p≤.002) associated with disease progression among hospitalized patients only.
CONCLUSIONS
In patients presenting with varying severities of influenza A(H1N1)pdm09 virus infection, a baseline elevation in several biomarkers associated with inflammation, coagulation, or immune function strongly predicted a higher risk of disease progression. It is conceivable that interventions designed to abrogate these baseline elevations might affect disease outcome
Influence of Hepatitis C Virus Infection on HIV‐1 Disease Progression and Response to Highly Active Antiretroviral Therapy
Raltegravir non-inferior to nucleoside based regimens in second-line therapy with lopinavir/ritonavir over 96 weeks: A randomised open label study for the treatment of HIV-1 infection
Objective: To determine the durability over 96 weeks of safety and efficacy of lopinavir/ritonavir (LPV/r) and raltegravir (RAL) which was demonstrated to have non-inferior efficacy relative to a regimen of LPV/r with nucleoside/nucleotide reverse transcriptase inhibitors (N(t)RTIs) (Control) in primary analysis at 48 weeks. Design: Open label, centrally randomised trial. Setting: Recruitment was from 37 primary and secondary care sites from Africa, Asia, Australia, Europe and Latin America. Subjects: 541 HIV-1 infected adults virologically failing first-line non-NRTI + 2N(t)RTI, with no previous exposure to protease inhibitors or integrase strand transfer inhibitors were analysed, 425 completed 96 weeks follow up on randomised therapy. Intervention: Randomisation was 1:1 to Control or RAL. Main outcome measures: Differences between the proportion of participants with plasma HIV-1 RNA (VL) <200 copies/mL by intention to treat were compared with a non-inferiority margin of -12%. Differences in biochemical, haematological and metabolic changes were assessed using T-tests. Results: VL <200 copies/mL at 96 weeks was: RAL 80.4%, Control 76.0%(difference: 4.4 [95%CI -2.6, 11.3]) andmet non-inferiority criteria. The RAL arm had a significantly higher mean change (difference Control-RAL; 95%CI) in haemoglobin (-2.9; -5.7, -1.1), total lymphocytes (-0.2; -0.3, -0.0), total cholesterol (-0.5; -0.8, -0.3), HDL cholesterol (-0.1; -0.1, -0.0) and LDL cholesterol (-0.3; -0.5, -0.2). Conclusion: At 96 weeks, both RAL and Control maintained efficacy greater than 75% and continued to demonstrate similar safety profiles. These results support the use of a combination LPV/r and RAL regimen as an option following failure of 1st line NNRTI + 2N(t)RTIs. Trial Registration: ClinicalTrials.gov NCT00931463
Virologic response at Week 96, by randomised arm, study population and screening strata.
<p>RAL = lopinavir/ritonavir+raltegravir Control = lopinavir/ritonavir+2/3 nucleoside/nucleotide reverse transcriptase inhibitors. *grey circle = screening plasma viral load strata, P interaction = 0.81, bars are 95%confidence intervals (CI).</p
Mean change from baseline in CD4+ T cells/mm<sup>3</sup> over 96 weeks by randomised arm.
<p>RAL = lopinavir/ritonavir+raltegravir Control = lopinavir/ritonavir+2/3 nucleoside/nucleotide reverse transcriptase inhibitors. (Control- - - RAL ---, bars indicate standard deviation).</p
Absolute mean cholesterol fractions and ratio over 96 weeks by randomised arm.
<p>(A) total cholesterol, (B) high density lipoprotein (HDL) cholesterol, (C) low density lipoprotein (LDL) cholesterol, (D) Total:HDL cholesterol ratio. RAL = lopinavir/ritonavir+raltegravir Control = lopinavir/ritonavir+2/3 nucleoside/nucleotide reverse transcriptase inhibitors. (Control - - - RAL ---, bars indicate standard deviation).</p
Clinical outcomes by randomised arm.
<p>*Grade 3/4 adverse events summarised by MedDRA System Organ Class which were reported by 5 or more people</p><p>py: person years</p><p>Clinical outcomes by randomised arm.</p
Biomarker study designs.
<p>The respective study designs and distribution of patients with and without severe disease outcomes in the outpatient case-control study FLU 002 (A) and in the hospitalization cohort study FLU 003 (B).</p
FLU 002 Patients: Odds Ratios of Progression for the Highest Versus Lowest Tertile of Each Biomarker.
*<p>Odds ratio & p-value for highest vs lowest tertile, from conditional logistic model with matching on age, duration of symptoms and country of enrollment.</p>**<p>As above, p-value for log<sub>10</sub>-transformed biomarker.</p