Evidence map›Paper›PMID 27367230›Full record

ArticlePloS one2016

How Can Viral Dynamics Models Inform Endpoint Measures in Clinical Trials of Therapies for Acute Viral Infections?

Carolin Vegvari, Christoforos Hadjichrysanthou, Emilie Cauët, Emma Lawrence, Anne Cori, Frank de Wolf, Roy M Anderson

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

18 citing papers in PubMed, 31 citations in OpenAlex.

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  18. Inhibition of Brazilian ZIKV strain replication in primary human placental chorionic cells and cervical cells treated with nitazoxanide.The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases
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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

7 authors at 2 institutions in 2 countries.

Carolin VegvariDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Christoforos HadjichrysanthouDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Emilie CauëtDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Emma LawrenceDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Anne CoriDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Frank de WolfJanssen Prevention Center, Leiden, The Netherlands.
Roy M AndersonDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Imperial College London · GBJanssen (Netherlands) · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute viral infections pose many practical challenges for the accurate assessment of the impact of novel therapies on viral growth and decay. Using the example of influenza A, we illustrate how the measurement of infection-related quantities that determine the dynamics of viral load within the human host, can inform investigators on the course and severity of infection and the efficacy of a novel treatment. We estimated the values of key infection-related quantities that determine the course of natural infection from viral load data, using Markov Chain Monte Carlo methods. The data were placebo group viral load measurements collected during volunteer challenge studies, conducted by Roche, as part of the oseltamivir trials. We calculated the values of the quantities for each patient and the correlations between the quantities, symptom severity and body temperature. The greatest variation among individuals occurred in the viral load peak and area under the viral load curve. Total symptom severity correlated positively with the basic reproductive number. The most sensitive endpoint for therapeutic trials with the goal to cure patients is the duration of infection. We suggest laboratory experiments to obtain more precise estimates of virological quantities that can supplement clinical endpoint measurements.

Indexed as

Clinical Trials as TopicEndpoint DeterminationModels, BiologicalAcute DiseaseAntiviral AgentsHumansMarkov ChainsMonte Carlo MethodViral LoadVirus DiseasesAntiviral Agents

Identifiers

PMID27367230
PMCPMC4930163
OpenAlexW2472041019

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.