Literature DB >> 23378483

Monitoring futility in a two-by-two factorial design: the SPS3 experience.

Leslie A McClure1, Christopher S Coffey, George Howard.   

Abstract

BACKGROUND: For studies with two-by-two factorial designs, the complexity of determining an appropriate futility analysis plan is increased as compared to studies where patients are randomized to one treatment. Issues that must be addressed include the possibility of a significant interaction and the need to determine how to proceed given evidence of futility in one arm. Suggested approaches include a two-stage plan, which first assesses futility of the interaction term and proceeds to examine the main effects, given sufficient evidence that no interaction is present, and variations on one-stage plans, which assume the trial will not be stopped for futility in the interaction.
PURPOSE: To discuss different approaches to monitoring futility in two-by-two factorial clinical trials and compare their properties.
METHODS: We utilized a simulation study, designed to mimic the Secondary Prevention of Small Subcortical Strokes (SPS3) Study, to determine which approach to monitoring futility in two-by-two factorial studies had the most desirable statistical properties.
RESULTS: We found that in most scenarios typical of clinical trials, monitoring futility in each arm simultaneously was superior to or as good as monitoring the interaction and then assessing futility in each arm only when the interaction was deemed futile. Monitoring each arm simultaneously lead to early stopping more often when no treatment effect was present, and lower average sample numbers (ASNs). The exception to this was the unlikely case when a qualitative interaction was present. LIMITATIONS: We assumed that one-sided tests were to be performed, and only assessed some of the possible methods for monitoring futility under the study design.
CONCLUSIONS: Futility monitoring in two-by-two factorial studies should proceed by assessing each arm simultaneously, rather than monitoring the interaction first. If sizeable interactions are anticipated, study design, rather than study monitoring, should account for this.

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Mesh:

Year:  2013        PMID: 23378483      PMCID: PMC3731445          DOI: 10.1177/1740774512474374

Source DB:  PubMed          Journal:  Clin Trials        ISSN: 1740-7745            Impact factor:   2.486


  7 in total

1.  The Secondary Prevention of Small Subcortical Strokes (SPS3) study.

Authors:  Oscar R Benavente; Carole L White; Lesly Pearce; Pablo Pergola; Ana Roldan; Marie-France Benavente; Christopher Coffey; Leslie A McClure; Jeff M Szychowski; Robin Conwit; Patricia A Heberling; George Howard; Carlos Bazan; Gabriela Vidal-Pergola; Robert Talbert; Robert G Hart
Journal:  Int J Stroke       Date:  2011-01-26       Impact factor: 5.266

2.  Guidelines for monitoring efficacy and toxicity responses in clinical trials.

Authors:  R J Cook; V T Farewell
Journal:  Biometrics       Date:  1994-12       Impact factor: 2.571

3.  Bayesian sequential monitoring designs for single-arm clinical trials with multiple outcomes.

Authors:  P F Thall; R M Simon; E H Estey
Journal:  Stat Med       Date:  1995-02-28       Impact factor: 2.373

4.  On the design and analysis of randomized clinical trials with multiple endpoints.

Authors:  D I Tang; N L Geller; S J Pocock
Journal:  Biometrics       Date:  1993-03       Impact factor: 2.571

5.  Early stopping of prevention trials when multiple outcomes are of interest: a discussion.

Authors:  S B Green; L S Freedman
Journal:  Stat Med       Date:  1994 Jul 15-30       Impact factor: 2.373

6.  An aid to data monitoring in long-term clinical trials.

Authors:  M Halperin; K K Lan; J H Ware; N J Johnson; D L DeMets
Journal:  Control Clin Trials       Date:  1982-12

7.  Testing for qualitative interactions between treatment effects and patient subsets.

Authors:  M Gail; R Simon
Journal:  Biometrics       Date:  1985-06       Impact factor: 2.571

  7 in total
  2 in total

1.  A 2 × 2 factorial design for the combination therapy of minocycline and remote ischemic perconditioning: efficacy in a preclinical trial in murine thromboembolic stroke model.

Authors:  Md Nasrul Hoda; Susan C Fagan; Mohammad B Khan; Kumar Vaibhav; Aizaz Chaudhary; Phillip Wang; Krishnan M Dhandapani; Jennifer L Waller; David C Hess
Journal:  Exp Transl Stroke Med       Date:  2014-10-09

2.  Advantages of Bayesian monitoring methods in deciding whether and when to stop a clinical trial: an example of a neonatal cooling trial.

Authors:  Claudia Pedroza; Jon E Tyson; Abhik Das; Abbot Laptook; Edward F Bell; Seetha Shankaran
Journal:  Trials       Date:  2016-07-22       Impact factor: 2.279

  2 in total

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