Evidence map›Paper›PMID 30408070›Full record

ArticlePloS one2018

HIV 2-LTR experiment design optimization.

LaMont Cannon, Cesar A Vargas-Garcia, Aditya Jagarapu, Michael J Piovoso, Ryan Zurakowski

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

LaMont CannonDepartment of Biomedical Engineering, University of Delaware, Newark, DE, United States of America.
Cesar A Vargas-GarciaDepartment of Electrical and Computer Engineering, University of Delaware, Newark, DE, United States of America.ORCID 0000-0002-4286-8882
Aditya JagarapuDepartment of Biomedical Engineering, University of Delaware, Newark, DE, United States of America.
Michael J PiovosoDepartment of Electrical and Computer Engineering, University of Delaware, Newark, DE, United States of America.
Ryan ZurakowskiDepartment of Biomedical Engineering, University of Delaware, Newark, DE, United States of America.ORCID 0000-0003-3726-3114

Funding

HIV 2-LTR Dynamics and Cryptic ViremiaR21AI110288 · NIAID · UNIVERSITY OF DELAWARE · PI ZURAKOWSKI, RYAN M · 2014 to 2015
$418k
Evidence of cryptic replication in dolutegravir intensification dataR03AI136710 · NIAID · UNIVERSITY OF DELAWARE · PI ZURAKOWSKI, RYAN M · 2018 to 2019
$155k
NIAID NIH HHS R03 AI136710NIAID NIH HHS R21 AI110288
6 · The paper itself

Abstract

Clinical trials are necessary in order to develop treatments for diseases; however, they can often be costly, time consuming, and demanding to the patients. This paper summarizes several common methods used for optimal design that can be used to address these issues. In addition, we introduce a novel method for optimizing experiment designs applied to HIV 2-LTR clinical trials. Our method employs Bayesian techniques to optimize the experiment outcome by maximizing the Expected Kullback-Leibler Divergence (EKLD) between the a priori knowledge of system parameters before the experiment and the a posteriori knowledge of the system parameters after the experiment. We show that our method is robust and performs equally well if not better than traditional optimal experiment design techniques.

Indexed as

AlgorithmsBayes TheoremClinical Trials as TopicComputer SimulationHIVHIV InfectionsHIV Long Terminal RepeatHumansImmunotherapy, AdoptiveMarkov ChainsModels, BiologicalModels, StatisticalMonte Carlo MethodResearch DesignRNA, ViralVirus ReplicationRNA, Viral

Identifiers

PMID30408070
PMCPMC6224063

What OpenQuestion holds

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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.