A randomized, placebo-controlled trial of patient education for acute low back pain (PREVENT trial)

• Verfasst von: Traeger, Adrian C. [VerfasserIn]
• Verfasst von: Henschke, Nicholas [VerfasserIn]
• Titel: A randomized, placebo-controlled trial of patient education for acute low back pain (PREVENT trial)
• Titelzusatz: statistical analysis plan
• Verf.angabe: Adrian C. Traeger, Ian W. Skinner, Markus Hübscher, Hopin Lee, G. Lorimer Moseley, Michael K. Nicholas, Nicholas Henschke, Kathryn M. Refshauge, Fiona M. Blyth, Chris J. Main, Julia M. Hush, Garry Pearce, Serigne Lo, James H. McAuley
• E-Jahr: 2017
• Jahr: 14 April 2017
• Umfang: 5 S.
• Fussnoten: Gesehen am 26.07.2018
• Titel Quelle: Enthalten in: Brazilian journal of physical therapy
• Ort Quelle: Amsterdam : Elsevier, 2013
• Jahr Quelle: 2017
• Band/Heft Quelle: 21(2017), 3, Seite 219-223
• DOI: doi:10.1016/j.bjpt.2017.04.005
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Low back pain
• Sach-SW: Patient education
• Sach-SW: Preventive medicine
• Sach-SW: Primary care
• K10plus-PPN: 1577962257

Abstract

Background: Statistical analysis plans increase the transparency of decisions made in the analysis of clinical trial results. The purpose of this paper is to detail the planned analyses for the PREVENT trial, a randomized, placebo-controlled trial of patient education for acute low back pain. Results: We report the pre-specified principles, methods, and procedures to be adhered to in the main analysis of the PREVENT trial data. The primary outcome analysis will be based on Mixed Models for Repeated Measures (MMRM), which can test treatment effects at specific time points, and the assumptions of this analysis are outlined. We also outline the treatment of secondary outcomes and planned sensitivity analyses. We provide decisions regarding the treatment of missing data, handling of descriptive and process measure data, and blinded review procedures. Conclusions: Making public the pre-specified statistical analysis plan for the PREVENT trial minimizes the potential for bias in the analysis of trial data, and in the interpretation and reporting of trial results.