OBJECTIVE: To describe the unique aspects of and the lessons learned in planning and conducting a pooled analysis of multiple trials evaluating interventions to reduce functional decline in hospitalized older persons. Specific examples from the Hospital Outcomes Project for the Elderly (HOPE) meta-analysis are discussed. DESIGN: A prospective meta-analysis (PMA) that compiled and pooled data from concurrently conducted clinical trials testing related but distinct interventions. SETTING: The Data Coordinating Center for the prospective meta-analysis coordinated the collection and analysis of common outcome data from five university-affiliated hospitals and one community hospital conducting the clinical trials. PARTICIPANTS: Acutely ill hospitalized elderly participants at least 65 to 75 years old. INTERVENTIONS: Treatments being evaluated included exercise, physical therapy, a multidisciplinary geriatric care unit, a multidisciplinary in-hospital intervention with post-discharge care, a nursing-based geriatric care program, and a program to improve detection and evaluation of delirious patients. CONCLUSION: The prospective meta-analysis provides selected advantages over independently conducted clinical trials and retrospective meta-analyses. It does, however, pose special design and operational challenges that must be addressed well before initiation of the individual trials. Specific issues of concern include: maintaining scientific integrity of both the individual trials and the PMA; reaching consensus on PMA goals, what data to collect, how and when to collect them and how to maintain uniformly high quality data across all sites; defining the role of the Data Coordinating Center in a multicenter project that utilizes different trials and protocols; and establishing policies concerning analyses of the pooled data, publication of pooled analyses, and ownership of the pooled database.
OBJECTIVE: To describe the unique aspects of and the lessons learned in planning and conducting a pooled analysis of multiple trials evaluating interventions to reduce functional decline in hospitalized older persons. Specific examples from the Hospital Outcomes Project for the Elderly (HOPE) meta-analysis are discussed. DESIGN: A prospective meta-analysis (PMA) that compiled and pooled data from concurrently conducted clinical trials testing related but distinct interventions. SETTING: The Data Coordinating Center for the prospective meta-analysis coordinated the collection and analysis of common outcome data from five university-affiliated hospitals and one community hospital conducting the clinical trials. PARTICIPANTS: Acutely ill hospitalized elderly participants at least 65 to 75 years old. INTERVENTIONS: Treatments being evaluated included exercise, physical therapy, a multidisciplinary geriatric care unit, a multidisciplinary in-hospital intervention with post-discharge care, a nursing-based geriatric care program, and a program to improve detection and evaluation of delirious patients. CONCLUSION: The prospective meta-analysis provides selected advantages over independently conducted clinical trials and retrospective meta-analyses. It does, however, pose special design and operational challenges that must be addressed well before initiation of the individual trials. Specific issues of concern include: maintaining scientific integrity of both the individual trials and the PMA; reaching consensus on PMA goals, what data to collect, how and when to collect them and how to maintain uniformly high quality data across all sites; defining the role of the Data Coordinating Center in a multicenter project that utilizes different trials and protocols; and establishing policies concerning analyses of the pooled data, publication of pooled analyses, and ownership of the pooled database.
Authors: Richard G Roetzheim; Karen M Freund; Don K Corle; David M Murray; Frederick R Snyder; Andrea C Kronman; Pascal Jean-Pierre; Peter C Raich; Alan Ec Holden; Julie S Darnell; Victoria Warren-Mears; Steven Patierno Journal: Clin Trials Date: 2012-01-24 Impact factor: 2.486
Authors: David K Turok; Eve Espey; Alison B Edelman; Pamela S Lotke; Eva H Lathrop; Stephanie B Teal; Janet C Jacobson; Sara E Simonsen; Kenneth F Schulz Journal: Trials Date: 2011-04-29 Impact factor: 2.279