Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

A recursive partitioning approach for subgroup identification in individual patient data meta-analysis

Tools
- Tools
+ Tools

Mistry, Dipesh, Stallard, Nigel and Underwood, Martin (2018) A recursive partitioning approach for subgroup identification in individual patient data meta-analysis. Statistics in Medicine, 37 (9). pp. 1550-1561. doi:10.1002/sim.7609

[img]
Preview
PDF
WRAP-recursive-partitioning-subgroupidentification-individual-Stallard-2018.pdf - Published Version - Requires a PDF viewer.
Available under License Creative Commons: Attribution-Noncommercial 4.0.

Download (566Kb) | Preview
[img] PDF
WRAP-recursive-partitioning-identitfication-individual-patient-Mistry-2017.pdf - Accepted Version
Embargoed item. Restricted access to Repository staff only - Requires a PDF viewer.

Download (761Kb)
Official URL: http://doi.org/10.1002/sim.7609

Request Changes to record.

Abstract

Background
Motivated by the setting of clinical trials in low back pain, this work investigated statistical methods to identify patient subgroups for which there is a large treatment effect (treatment by subgroup interaction). Statistical tests for interaction are often underpowered. Individual patient data (IPD) meta-analyses provide a framework with improved statistical power to investigate subgroups. However, conventional approaches to subgroup analyses applied in both a single trial setting and an IPD setting have a number of issues, one of them being that factors used to define subgroups are investigated one at a time. As individuals have multiple characteristics that may be related to response to treatment, alternative exploratory statistical methods are required.

Methods
Tree-based methods are a promising alternative that systematically searches the covariate space to identify subgroups defined by multiple characteristics. A tree method in particular, SIDES, is described and extended for application in an IPD meta-analyses setting by incorporating fixed-effects and random-effects models to account for between-trial variation. The performance of the proposed extension was assessed using simulation studies. The proposed method was then applied to an IPD low back pain dataset.

Results
The simulation studies found that the extended IPD-SIDES method performed well in detecting subgroups especially in the presence of large between-trial variation. The IPD-SIDES method identified subgroups with enhanced treatment effect when applied to the low back pain data.

Conclusions
This work proposes an exploratory statistical approach for subgroup analyses applicable in any research discipline where subgroup analyses in an IPD meta-analysis setting are of interest.

Item Type: Journal Article
Subjects: R Medicine > RA Public aspects of medicine
Divisions: Faculty of Medicine > Warwick Medical School > Health Sciences > Population, Evidence & Technologies (PET)
Faculty of Medicine > Warwick Medical School
Library of Congress Subject Headings (LCSH): Medical statistics, Recursive partitioning, Clinical trials, Backache -- Treatment, Decision trees
Journal or Publication Title: Statistics in Medicine
Publisher: John Wiley & Sons Ltd.
ISSN: 0277-6715
Official Date: 30 April 2018
Dates:
DateEvent
30 April 2018Published
31 January 2018Available
19 November 2017Accepted
Volume: 37
Number: 9
Page Range: pp. 1550-1561
DOI: 10.1002/sim.7609
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
RP-PG-0608-10076National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
UNSPECIFIEDScience City Research AllianceUNSPECIFIED
UNSPECIFIEDAdvantage West MidlandsUNSPECIFIED

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item
twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us