Evidence map›Paper›PMID 26768570›Full record

ArticleClinical trials (London, England)2016

Design and analysis considerations in the Ebola_Tx trial evaluating convalescent plasma in the treatment of Ebola virus disease in Guinea during the 2014-2015 outbreak.

Tansy Edwards, Malcolm G Semple, Anja De Weggheleire, Yves Claeys, Maaike De Crop, Joris Menten, Raffaella Ravinetto, Sarah Temmerman, Lutgarde Lynen, Elhadj Ibrahima Bah and 3 more

Abstract readComparative Study
In one paragraph

Article in Clinical trials (London, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

13 authors.

Tansy EdwardsMRC Tropical Epidemiology Group, London School of Hygiene & Tropical Medicine, London, UK tansy.edwards@lshtm.ac.uk.
Malcolm G SempleInstitute of Translational Medicine, University of Liverpool, Liverpool, UK.
Anja De WeggheleireInstitute of Tropical Medicine, Antwerp, Belgium.
Yves ClaeysInstitute of Tropical Medicine, Antwerp, Belgium.
Maaike De CropInstitute of Tropical Medicine, Antwerp, Belgium.
Joris MentenInstitute of Tropical Medicine, Antwerp, Belgium.
Raffaella RavinettoInstitute of Tropical Medicine, Antwerp, Belgium.
Sarah TemmermanInstitute of Tropical Medicine, Antwerp, Belgium.
Lutgarde LynenInstitute of Tropical Medicine, Antwerp, Belgium.
Elhadj Ibrahima BahService des maladies infectieuses et tropicales, de L'Hôpital National Donka, Conakry, Guinea.
Peter G SmithMRC Tropical Epidemiology Group, London School of Hygiene & Tropical Medicine, London, UK.
Johan van GriensvenInstitute of Tropical Medicine, Antwerp, Belgium.
Ebola_Tx Consortium

Funding

Medical Research Council MR/K012126/1
6 · The paper itself

Abstract

The Ebola virus disease outbreak in 2014-2015 led to a huge caseload with a high case fatality rate. No specific treatments were available beyond supportive care for conditions such as dehydration and shock. Evaluation of treatment with convalescent plasma from Ebola survivors was identified as a priority. We evaluated this intervention in an emergency setting, where randomization was unacceptable. The original trial design was an open-label study comparing patients receiving convalescent plasma and supportive care to patients receiving supportive care alone. The comparison group comprised patients recruited at the start of the trial before convalescent plasma became available, as well as patients presenting during the trial for whom there was insufficient blood group-compatible plasma or no staffing capacity to provide additional transfusions. However, during the trial, convalescent plasma was available to treat all new patients. The design was changed to use a comparator group comprising patients previously treated at the same Ebola treatment center prior to the start of the trial. In the analysis, it was planned to adjust for any differences in prognostic variables between intervention and comparison groups, specifically baseline polymerase chain reaction cycle threshold and age. In addition, adjustment was planned for other potential confounders, identified in the analysis, such as patient presenting symptoms and time to treatment seeking. Because plasma treatment started up to 3 days after diagnosis and we could not define a similar time-point for the comparator group, patients who died before the third day after confirmation of diagnosis were excluded from both intervention and comparison groups in a per-protocol analysis. Some patients received additional experimental treatments soon after plasma treatment, and these were excluded. We also analyzed mortality including all patients from the time of confirmed diagnosis, irrespective of whether those in the trial series actually received plasma, as an intention-to-treat analysis. Per-protocol and intention-to-treat approaches gave similar conclusions. An important caveat in the interpretation of the findings is that it is unlikely that all potential sources of confounding, such as any variation in supportive care over time, were eliminated. Protocols and electronic data capture systems have now been extensively field-tested for emergency evaluation of treatment with convalescent plasma. Ongoing studies seek to quantify the level of neutralizing antibodies in different plasma donations to determine whether this influences the response and survival of treated patients.

Indexed as

Blood Component TransfusionConvalescencePlasmaResearch DesignClinical ProtocolsClinical Trials as TopicCombined Modality TherapyDisease OutbreaksGuineaHemorrhagic Fever, EbolaHumansIntention to Treat Analysisconvalescent plasmaEbolaGuineatrial design

Identifiers

PMID26768570
PMCPMC4738238

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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.