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A review and re-interpretation of a group-sequential approach to sample size re-estimation in two-stage trials.

Bowden J, Mander A - Pharm Stat (2014)

Bottom Line: In this paper, we review the adaptive design methodology of Li et al. (Biostatistics 3:277-287) for two-stage trials with mid-trial sample size adjustment.We argue that it is closer in principle to a group sequential design, in spite of its obvious adaptive element.Several extensions are proposed that aim to make it even more attractive and transparent alternative to a standard (fixed sample size) trial for funding bodies to consider.

View Article: PubMed Central - PubMed

Affiliation: MRC Biostatistics Unit, Cambridge, UK.

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Stage one effect estimate versus total sample size using design 1. Dotted line shows the distribution of the estimate  when δ = 0.35.
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fig01: Stage one effect estimate versus total sample size using design 1. Dotted line shows the distribution of the estimate when δ = 0.35.

Mentions: Figure 1 plots the total number of patients needed as a function of under design 1. We see that at the interim, if , then only 125 patients per arm are required for the trial in total. The dotted line in Figure 1 shows the distribution of the estimate when δ = 0.35 to indicate the proportion of times the study would stop early for efficacy or futility at stage one, or continue to stage two with the specified sample size.


A review and re-interpretation of a group-sequential approach to sample size re-estimation in two-stage trials.

Bowden J, Mander A - Pharm Stat (2014)

Stage one effect estimate versus total sample size using design 1. Dotted line shows the distribution of the estimate  when δ = 0.35.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4288989&req=5

fig01: Stage one effect estimate versus total sample size using design 1. Dotted line shows the distribution of the estimate when δ = 0.35.
Mentions: Figure 1 plots the total number of patients needed as a function of under design 1. We see that at the interim, if , then only 125 patients per arm are required for the trial in total. The dotted line in Figure 1 shows the distribution of the estimate when δ = 0.35 to indicate the proportion of times the study would stop early for efficacy or futility at stage one, or continue to stage two with the specified sample size.

Bottom Line: In this paper, we review the adaptive design methodology of Li et al. (Biostatistics 3:277-287) for two-stage trials with mid-trial sample size adjustment.We argue that it is closer in principle to a group sequential design, in spite of its obvious adaptive element.Several extensions are proposed that aim to make it even more attractive and transparent alternative to a standard (fixed sample size) trial for funding bodies to consider.

View Article: PubMed Central - PubMed

Affiliation: MRC Biostatistics Unit, Cambridge, UK.

Show MeSH