Evidence map›Paper›PMID 27119536›Full record

ArticlePLoS pathogens2016

Real-Time Predictions of Reservoir Size and Rebound Time during Antiretroviral Therapy Interruption Trials for HIV.

Alison L Hill, Daniel I S Rosenbloom, Edward Goldstein, Emily Hanhauser, Daniel R Kuritzkes, Robert F Siliciano, Timothy J Henrich

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PLoS pathogens, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 72 papers.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed
9.2field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

72 citing papers in PubMed, 103 citations in OpenAlex.

  1. Trial
  2. Allogeneic Hematopoietic Cell Transplant for HIV Patients with Hematologic Malignancies: The BMT CTN-0903/AMC-080 Trial.Biology of blood and marrow transplantation : journal of the American Society for Blood and Marrow Transplantation · 2019
    Trial
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12 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 6 institutions in 1 country.

Alison L HillProgram for Evolutionary Dynamics, Department of Mathematics, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.
Daniel I S RosenbloomDepartment of Biomedical Informatics, Columbia University Medical Center, New York, New York, United States of America.
Edward GoldsteinCenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.
Emily HanhauserDivision of Infectious Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
Daniel R KuritzkesDivision of Infectious Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
Robert F SilicianoDepartment of Medicine, Johns Hopkins University School of Medicine and Howard Hughes Medical Institute, Baltimore, Maryland, United States of America.
Timothy J HenrichDivision of Experimental Medicine, Department of Medicine, University of California, San Francisco, California, United States of America.
Brigham and Women's Hospital · USCenter for Disease Dynamics, Economics & Policy · USColumbia University Irving Medical Center · USHarvard University · USHoward Hughes Medical Institute · USUniversity of California, San Francisco · US

Funding

Vaccine Response and Immunotherapeutics SWGP30AI094189 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Richard E. Chaisson · 2012 to 2026
$67.0M
Using NK Cells to eliminate the latent HIV reservoirU19AI096113 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI OTT, MELANIE MARIA · 2011 to 2015
$39.5M
Viral reservoirs and sanctuaries in HAART - treated patients: role and mechanismsU19AI096109 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DEEKS, STEVEN GRANT, MCCUNE, JOSEPH M · 2011 to 2015
$29.5M
Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIPSITCH, MARC · 2009 to 2018
$26.4M
LATENT VIRAL RESERVOIRS IN HIV1 INFECTIONR01AI043222 · NIAID · JOHNS HOPKINS UNIVERSITY · PI SILICIANO, ROBERT F · 1998 to 2013
$3.5M
Quantification and prediction of treatment efficacy for HIV cure strategiesDP5OD019851 · OD · JOHNS HOPKINS UNIVERSITY · PI HILL, ALISON LYNN · 2014 to 2018
$2.1M
Uncovering Evolutionary History using the Topology of Genomic Data with Applications to HIVR01GM117591 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI RABADAN, RAUL · 2015 to 2018
$1.3M
Impact of Chemotherapy and Stem Cell Transplant on HIV-1 Reservoir DynamicsK23AI098480 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HENRICH, TIMOTHY JENSEN · 2012 to 2016
$673k
Howard Hughes Medical InstituteNIAID NIH HHS K23 AI098480NIAID NIH HHS P30 AI094189NIAID NIH HHS R01 AI043222NIAID NIH HHS U19 AI096109NIAID NIH HHS U19 AI096113NIGMS NIH HHS R01 GM117591NIGMS NIH HHS U54 GM088558NIH HHS DP5 OD019851
6 · The paper itself

Abstract

Monitoring the efficacy of novel reservoir-reducing treatments for HIV is challenging. The limited ability to sample and quantify latent infection means that supervised antiretroviral therapy (ART) interruption studies are generally required. Here we introduce a set of mathematical and statistical modeling tools to aid in the design and interpretation of ART-interruption trials. We show how the likely size of the remaining reservoir can be updated in real-time as patients continue off treatment, by combining the output of laboratory assays with insights from models of reservoir dynamics and rebound. We design an optimal schedule for viral load sampling during interruption, whereby the frequency of follow-up can be decreased as patients continue off ART without rebound. While this scheme can minimize costs when the chance of rebound between visits is low, we find that the reservoir will be almost completely reseeded before rebound is detected unless sampling occurs at least every two weeks and the most sensitive viral load assays are used. We use simulated data to predict the clinical trial size needed to estimate treatment effects in the face of highly variable patient outcomes and imperfect reservoir assays. Our findings suggest that large numbers of patients-between 40 and 150-will be necessary to reliably estimate the reservoir-reducing potential of a new therapy and to compare this across interventions. As an example, we apply these methods to the two "Boston patients", recipients of allogeneic hematopoietic stem cell transplants who experienced large reductions in latent infection and underwent ART-interruption. We argue that the timing of viral rebound was not particularly surprising given the information available before treatment cessation. Additionally, we show how other clinical data can be used to estimate the relative contribution that remaining HIV+ cells in the recipient versus newly infected cells from the donor made to the residual reservoir that eventually caused rebound. Together, these tools will aid HIV researchers in the evaluating new potentially-curative strategies that target the latent reservoir.

Indexed as

Models, TheoreticalAdultAnti-HIV AgentsBayes TheoremFemaleHIV InfectionsHumansMaleViral LoadVirus LatencyAnti-HIV Agents

Identifiers

PMID27119536
PMCPMC4847932
OpenAlexW2343897169

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.