Archive for March 25, 2015

Reassessment of HIV-1 Acute Phase Infectivity: Accounting for Heterogeneity and Study Design with Simulated Cohorts

Plos Medicine MARCH 17, 2015

Steve E. Bellan 1 , Jonathan Dushoff 2, Alison P. Galvani 3-4, Lauren Ancel Meyers5-6

1 Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas,

United States of America,

2 Department of Biology, McMaster University, Hamilton, Ontario, Canada,

3 Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America,

4 Department of Ecology and Evolution, Yale University, New Haven, Connecticut, United States of America, 5 Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America,

6 The Santa Fe Institute, Santa Fe, New Mexico, United States of America

Background

The infectivity of the HIV-1 acute phase has been directly measured only once, from a retrospectively identified cohort of serodiscordant heterosexual couples in Rakai, Uganda. Analyses of this cohort underlie the widespread view that the acute phase is highly infectious, even more so than would be predicted from its elevated viral load, and that transmission occurring shortly after infection may therefore compromise interventions that rely on diagnosis and treatment, such as antiretroviral treatment as prevention (TasP). Here, we re-estimate the duration and relative infectivity of the acute phase, while accounting for several possible sources of bias in published estimates, including the retrospective cohort exclusion criteria and unmeasured heterogeneity in risk.

Methods and Findings

We estimated acute phase infectivity using two approaches. First, we combined viral load trajectories and viral load-infectivity relationships to estimate infectivity trajectories over the course of infection, under the assumption that elevated acute phase infectivity is caused by elevated viral load alone. Second, we estimated the relative hazard of transmission during the acute phase versus the chronic phase (RHacute) and the acute phase duration (dacute) by fitting a couples transmission model to the Rakai retrospective cohort using approximate Bayesian computation. Our model fit the data well and accounted for characteristics overlooked by previous analyses, including individual heterogeneity in infectiousness and susceptibility and the retrospective cohort’s exclusion of couples that were recorded as serodiscordant only once before being censored by loss to follow-up, couple dissolution, or study termination. Finally, we replicated two highly cited analyses of the Rakai data on simulated data to identify biases underlying the discrepancies between previous estimates and our own.

From the Rakai data, we estimated RHacute = 5.3 (95% credibility interval [95% CrI]: 0.79–57) and dacute = 1.7 mo (95% CrI: 0.55–6.8). The wide credibility intervals reflect an inability to distinguish a long, mildly infectious acute phase from a short, highly infectious acute phase, given the 10-mo Rakai observation intervals. The total additional risk, measured as excess hazard-months attributable to the acute phase (EHMacute) can be estimated more precisely: EHMacute = (RHacute – 1) × dacute, and should be interpreted with respect to the 120 hazard-months generated by a constant untreated chronic phase infectivity over 10 y of infection. From the Rakai data, we estimated that EHMacute = 8.4 (95% CrI: -0.27 to 64). This estimate is considerably lower than previously published estimates, and consistent with our independent estimate from viral load trajectories, 5.6 (95% confidence interval: 3.3–9.1). We found that previous overestimates likely stemmed from failure to account for risk heterogeneity and bias resulting from the retrospective cohort study design.

Our results reflect the interaction between the retrospective cohort exclusion criteria and high (47%) rates of censorship amongst incident serodiscordant couples in the Rakai study due to loss to follow-up, couple dissolution, or study termination. We estimated excess physiological infectivity during the acute phase from couples data, but not the proportion of transmission attributable to the acute phase, which would require data on the broader population’s sexual network structure.

Conclusions

Previous EHMacute estimates relying on the Rakai retrospective cohort data range from 31 to 141. Our results indicate that these are substantial overestimates of HIV-1 acute phase infectivity, biased by unmodeled heterogeneity in transmission rates between couples and by inconsistent censoring. Elevated acute phase infectivity is therefore less likely to undermine TasP interventions than previously thought. Heterogeneity in infectiousness and susceptibility may still play an important role in intervention success and deserves attention in future analyses

FULL TEXT

http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001801

 

PDF

http://www.plosmedicine.org/article/fetchObject.action?uri=info:doi/10.1371/journal.pmed.1001801&representation=PDF

March 25, 2015 at 8:32 am

Clinical characteristics and outcomes of prosthetic joint infection caused by small colony variant staphylococci.

MBio. 2014 Sep 30;5(5):e01910-14.

Tande AJ1, Osmon DR2, Greenwood-Quaintance KE3, Mabry TM4, Hanssen AD4, Patel R.

Abstract

Small colony variants (SCVs) are naturally occurring subpopulations of bacteria.

The clinical characteristics and treatment outcomes of patients with prosthetic joint infection (PJI) caused by staphylococcal SCVs are unknown.

This study was a retrospective series of 113 patients with staphylococcal PJI, with prospective testing of archived sonicate fluid samples.

SCVs were defined using two-investigator review. Treatment failure was defined as

(i) subsequent revision surgery for any reason,

(ii) PJI after the index surgery,

(iii) prosthesis nonreimplantation due to ongoing infection, or

(iv) amputation of the affected limb.

There were 38 subjects (34%) with SCVs and 75 (66%) with only normal-phenotype (NP) bacteria.

Subjects with SCVs were more likely to have been on chronic antimicrobials prior to surgery (P = 0.048), have had prior surgery for PJI (P = 0.03), have had a longer duration of symptoms (P = 0.0003), and have had a longer time since joint implantation (P = 0.007), compared to those with only NP bacteria.

Over a median follow-up of 30.6 months, 9 subjects (24%) with SCVs and 23 (32%) with only NP bacteria experienced treatment failure (P = 0.51).

Subjects infected with Staphylococcus aureus were more likely to fail than were those infected with Staphylococcus epidermidis (hazard ratio [HR], 4.03; 95% confidence interval [CI], 1.80 to 9.04).

While frequently identified in subjects with PJI and associated with several potential predisposing factors, SCVs were not associated with excess treatment failure compared to NP infections in this study, where they were primarily managed with two-stage arthroplasty exchange.

IMPORTANCE:

Bacteria with the small colony variant (SCV) phenotype are described in small case series as causing persistent or relapsing infection, but there are insufficient data to suggest that they should be managed differently than infection with normal-phenotype bacteria. In an effort to investigate the clinical importance of this phenotype, we determined whether SCVs were present in biofilms dislodged from the surfaces of arthroplasties of patients with staphylococcal prosthetic joint infection and assessed the clinical outcomes associated with detection of SCVs. We found that prosthetic joint infection caused by SCV staphylococci was associated with a longer duration of symptoms and more prior treatment for infection but not with an increased rate of treatment failure, compared to infection caused by normal-phenotype staphylococci.

PDF

http://mbio.asm.org/content/5/5/e01910-14.full.pdf+html

March 25, 2015 at 8:26 am


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