Titre
Using Trial Sequential Analysis for estimating the sample sizes of further trials: example using smoking cessation intervention.
Type
article
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Périodique
Auteur(s)
Claire, R.
Auteure/Auteur
Gluud, C.
Auteure/Auteur
Berlin, I.
Auteure/Auteur
Coleman, T.
Auteure/Auteur
Leonardi-Bee, J.
Auteure/Auteur
Liens vers les personnes
Liens vers les unités
ISSN
1471-2288
Statut éditorial
Publié
Date de publication
2020-11-30
Volume
20
Numéro
1
Première page
284
Peer-reviewed
Oui
Langue
anglais
Notes
Publication types: Journal Article ; Randomized Controlled Trial ; Research Support, Non-U.S. Gov't
Publication Status: epublish
Publication Status: epublish
Résumé
Assessing benefits and harms of health interventions is resource-intensive and often requires feasibility and pilot trials followed by adequately powered randomised clinical trials. Data from feasibility and pilot trials are used to inform the design and sample size of the adequately powered randomised clinical trials. When a randomised clinical trial is conducted, results from feasibility and pilot trials may be disregarded in terms of benefits and harms.
We describe using feasibility and pilot trial data in the Trial Sequential Analysis software to estimate the required sample size for one or more trials investigating a behavioural smoking cessation intervention. We show how data from a new, planned trial can be combined with data from the earlier trials using trial sequential analysis methods to assess the intervention's effects.
We provide a worked example to illustrate how we successfully used the Trial Sequential Analysis software to arrive at a sensible sample size for a new randomised clinical trial and use it in the argumentation for research funds for the trial.
Trial Sequential Analysis can utilise data from feasibility and pilot trials as well as other trials, to estimate a sample size for one or more, similarly designed, future randomised clinical trials. As this method uses available data, estimated sample sizes may be smaller than they would have been using conventional sample size estimation methods.
We describe using feasibility and pilot trial data in the Trial Sequential Analysis software to estimate the required sample size for one or more trials investigating a behavioural smoking cessation intervention. We show how data from a new, planned trial can be combined with data from the earlier trials using trial sequential analysis methods to assess the intervention's effects.
We provide a worked example to illustrate how we successfully used the Trial Sequential Analysis software to arrive at a sensible sample size for a new randomised clinical trial and use it in the argumentation for research funds for the trial.
Trial Sequential Analysis can utilise data from feasibility and pilot trials as well as other trials, to estimate a sample size for one or more, similarly designed, future randomised clinical trials. As this method uses available data, estimated sample sizes may be smaller than they would have been using conventional sample size estimation methods.
PID Serval
serval:BIB_07E76CB458A6
PMID
Open Access
Oui
Date de création
2020-12-07T13:36:07.889Z
Date de création dans IRIS
2025-05-20T14:40:44Z
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Nom
33256626_BIB_07E76CB458A6.pdf
Version du manuscrit
published
Licence
https://creativecommons.org/licenses/by/4.0
Taille
1.03 MB
Format
Adobe PDF
PID Serval
serval:BIB_07E76CB458A6.P001
URN
urn:nbn:ch:serval-BIB_07E76CB458A69
Somme de contrôle
(MD5):5dab1e4b469a80ac68aa78f47e72f4a1