*Result*: Clinical Trial Simulation: Planning With the OCTAVE Framework, Implementation and Validation Principles.
Title:
Clinical Trial Simulation: Planning With the OCTAVE Framework, Implementation and Validation Principles.
Authors:
Lee KM; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK., Choodari-Oskooei B; MRC Clinical Trials Unit at UCL, University College London, London, UK., Grayling MJ; Statistics and Decision Sciences, Johnson & Johnson, High Wycombe, UK., Jacko P; Lancaster University, Lancaster, UK.; Berry Consultants, Abingdon, UK., Kimani PK; Warwick Medical School, University of Warwick, Coventry, UK., Mukherjee A; Population Health Sciences Institute, Newcastle University, Newcastle, UK., Pallmann P; Centre for Trials Research, Cardiff University, Cardiff, UK., Parke T; Berry Consultants, Abingdon, UK., Robertson DS; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK., Wang Z; Statistical Sciences Research Institute, University of Southampton, Southampton, UK., Yap C; Clinical Trials and Statistics Unit, The Institute of Cancer Research, London, UK., Jaki T; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.; University of Regensburg, Regensburg, Germany.
Source:
Statistics in medicine [Stat Med] 2026 Mar; Vol. 45 (6-7), pp. e70449.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Wiley Country of Publication: England NLM ID: 8215016 Publication Model: Print Cited Medium: Internet ISSN: 1097-0258 (Electronic) Linking ISSN: 02776715 NLM ISO Abbreviation: Stat Med Subsets: MEDLINE
Imprint Name(s):
Original Publication: Chichester ; New York : Wiley, c1982-
MeSH Terms:
References:
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Grant Information:
NIHR300051 National Institute for Health Research; NIHR301614 National Institute for Health Research; MC_UU_00002/14 UK Medical Research Council; MC_UU_00040/03 UK Medical Research Council; MC_UU_00004_09 UK Medical Research Council; United Kingdom HCRW_ HCRW_
Contributed Indexing:
Keywords: adaptive design; clinical trial simulation; complex innovative designs; computation; graphical tools; master protocol
Entry Date(s):
Date Created: 20260316 Date Completed: 20260316 Latest Revision: 20260318
Update Code:
20260318
PubMed Central ID:
PMC12989786
DOI:
10.1002/sim.70449
PMID:
41834608
Database:
MEDLINE
*Further Information*
*The adoption of complex innovative clinical trial designs has steadily increased in recent years. These are trial designs that have one or more unconventional features-often resulting in multiple stages-with the goal of improving on conventional single-stage, fixed-setting designs in terms of efficiency, for example, by reducing the required sample size or the time to establish findings about an intervention. The motivation for these designs may not be difficult to follow, but their set-up and implementation is usually more challenging. Statistical properties of these designs can also be difficult to compute. Clinical trial simulation (CTS), which uses software to generate artificial data for learning, can be conducted to identify the (optimal) setting of a clinical trial, evaluate the design's statistical properties under some hypothetical scenarios for sensitivity analysis, and compare different design set-ups and data analysis strategies, all of which contribute to a better understanding of the value of unconventional features before implementing the design in an actual clinical trial. Existing literature on simulation primarily focuses on the evaluation of statistical analysis methods, with less attention on the detailed specification and planning of CTS. This tutorial presents a new framework, called OCTAVE, for outlining the details of CTS, provides practical recommendations for their implementation, and addresses key computational considerations. The target audience is trial statisticians who are involved in designing and analyzing clinical trials. This tutorial covers a range of complex innovative designs, without the expectation that readers are familiar with the mentioned examples.
(© 2026 The Author(s). Statistics in Medicine published by John Wiley & Sons Ltd.)*