Literature DB >> 8516592

Sequential monitoring of clinical trials: the role of information and Brownian motion.

K K Lan1, D M Zucker.   

Abstract

Sequential monitoring has been a topic of major interest in clinical trials methodology over the past two decades. This paper presents a unified conceptual framework for sequential monitoring that covers a wide variety of monitoring procedures in a wide variety of clinical trial settings. The central elements of this framework consist of a suitable concept of statistical information and a scheme for using this concept as a basis for summarizing the accumulating results of a trial in a standardized form, through a stochastic process that can be shown to approximate classical Brownian motion. The ideas are developed in a simple step-by-step fashion and illustrated by several practical examples.

Mesh:

Year:  1993        PMID: 8516592     DOI: 10.1002/sim.4780120804

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  10 in total

1.  Nonparametric sequential evaluation of diagnostic biomarkers.

Authors:  Aiyi Liu; Chengqing Wu; Enrique F Schisterman
Journal:  Stat Med       Date:  2008-05-10       Impact factor: 2.373

2.  Continuous covariate imbalance and conditional power for clinical trial interim analyses.

Authors:  Jody D Ciolino; Renee' H Martin; Wenle Zhao; Edward C Jauch; Michael D Hill; Yuko Y Palesch
Journal:  Contemp Clin Trials       Date:  2014-03-07       Impact factor: 2.226

3.  Survival trial design and monitoring using historical controls.

Authors:  Jianrong Wu; Xiaoping Xiong
Journal:  Pharm Stat       Date:  2016-06-15       Impact factor: 1.894

4.  Rationale and design of a phase II clinical trial of aspirin and simvastatin for the treatment of pulmonary arterial hypertension: ASA-STAT.

Authors:  Steven M Kawut; Emilia Bagiella; Daichi Shimbo; David J Lederer; Nadine Al-Naamani; Kari E Roberts; R Graham Barr; Wendy Post; Evelyn M Horn; Russell Tracy; Paul Hassoun; Reda Girgis
Journal:  Contemp Clin Trials       Date:  2010-12-10       Impact factor: 2.226

5.  Robot-assisted therapy for long-term upper-limb impairment after stroke.

Authors:  Albert C Lo; Peter D Guarino; Lorie G Richards; Jodie K Haselkorn; George F Wittenberg; Daniel G Federman; Robert J Ringer; Todd H Wagner; Hermano I Krebs; Bruce T Volpe; Christopher T Bever; Dawn M Bravata; Pamela W Duncan; Barbara H Corn; Alysia D Maffucci; Stephen E Nadeau; Susan S Conroy; Janet M Powell; Grant D Huang; Peter Peduzzi
Journal:  N Engl J Med       Date:  2010-04-16       Impact factor: 91.245

6.  Group sequential design for historical control trials using error spending functions.

Authors:  Jianrong Wu; Yimei Li
Journal:  J Biopharm Stat       Date:  2019-11-12       Impact factor: 1.051

7.  Multicenter randomized trial of robot-assisted rehabilitation for chronic stroke: methods and entry characteristics for VA ROBOTICS.

Authors:  Albert C Lo; Peter Guarino; Hermano I Krebs; Bruce T Volpe; Christopher T Bever; Pamela W Duncan; Robert J Ringer; Todd H Wagner; Lorie G Richards; Dawn M Bravata; Jodie K Haselkorn; George F Wittenberg; Daniel G Federman; Barbara H Corn; Alysia D Maffucci; Peter Peduzzi
Journal:  Neurorehabil Neural Repair       Date:  2009-06-18       Impact factor: 3.919

8.  Flexible stopping boundaries when changing primary endpoints after unblinded interim analyses.

Authors:  Liddy M Chen; Joseph G Ibrahim; Haitao Chu
Journal:  J Biopharm Stat       Date:  2014       Impact factor: 1.051

9.  Group Sequential Survival Trial Design and Monitoring Using the Log-Rank Test.

Authors:  Jianrong Wu; Xiaoping Xiong
Journal:  Stat Biopharm Res       Date:  2017-03-02       Impact factor: 1.452

10.  A flexible futility monitoring method with time-varying conditional power boundary.

Authors:  William R Clarke
Journal:  Clin Trials       Date:  2010-04-27       Impact factor: 2.486

  10 in total

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