Evidence map›Paper›PMID 33952195›Full record

Trial reportBMC medical research methodology2021

Evaluation by simulation of clinical trial designs for evaluation of treatment during a viral haemorrhagic fever outbreak.

Pauline Manchon, Drifa Belhadi, France Mentré, Cédric Laouénan

Abstract readClinical Trial
In one paragraph

Trial report in BMC medical research methodology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Pauline Manchon *INSERM, Centre d'Investigation clinique-Epidémiologie Clinique 1425, Hôpital Bichat, F-75018, Paris, France. pauline.manchon@aphp.fr.ORCID 0000-0002-5162-1128
Drifa Belhadi *INSERM, Centre d'Investigation clinique-Epidémiologie Clinique 1425, Hôpital Bichat, F-75018, Paris, France.
France MentréINSERM, Centre d'Investigation clinique-Epidémiologie Clinique 1425, Hôpital Bichat, F-75018, Paris, France.
Cédric LaouénanINSERM, Centre d'Investigation clinique-Epidémiologie Clinique 1425, Hôpital Bichat, F-75018, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundViral haemorrhagic fevers are characterized by irregular outbreaks with high mortality rate. Difficulties arise when implementing therapeutic trials in this context. The outbreak duration is hard to predict and can be short compared to delays of trial launch and number of subject needed (NSN) recruitment. Our objectives were to compare, using clinical trial simulation, different trial designs for experimental treatment evaluation in various outbreak scenarios.

methodsFour type of designs were compared: fixed or group-sequential, each being single- or two-arm. The primary outcome was 14-day survival rate. For single-arm designs, results were compared to a pre-trial historical survival rate p

resultsUnder H

conclusionsAt an outbreak beginning, group-sequential two-arm trials should be preferred, as the infected cases number increases allowing to conduct a strong randomized control trial. Group-sequential designs allow early termination of trials in cases of harmful experimental treatment. After the epidemic peak, fixed single-arm design should be preferred, as the cases number decreases but this assumes a high level of confidence on the pre-trial historical survival rate.

Indexed as

Hemorrhagic Fevers, ViralClinical Trials as TopicComputer SimulationDisease OutbreaksHumansResearch DesignSample SizeClinical trial designSimulation studyViral haemorrhagic fever outbreak

Identifiers

PMID33952195
PMCPMC8099711

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Registered trials

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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.