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Managing clustering effects and learning effects in the design and analysis of multicentre randomised trials: a survey to establish current practice
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Managing clustering effects and learning effects in the design and analysis of multicentre randomised trials: a survey to establish current practice
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Journal Article
Managing clustering effects and learning effects in the design and analysis of multicentre randomised trials: a survey to establish current practice
2020
Overview
Background
Patient outcomes can depend on the treating centre, or health professional, delivering the intervention. A health professional’s skill in delivery improves with experience, meaning that outcomes may be associated with learning. Considering differences in intervention delivery at trial design will ensure that any appropriate adjustments can be made during analysis. This work aimed to establish practice for the allowance of clustering and learning effects in the design and analysis of randomised multicentre trials.
Methods
A survey that drew upon quotes from existing guidelines, references to relevant publications and example trial scenarios was delivered. Registered UK Clinical Research Collaboration Registered Clinical Trials Units were invited to participate.
Results
Forty-four Units participated (
N
= 50). Clustering was managed through design by stratification, more commonly by centre than by treatment provider. Managing learning by design through defining a minimum expertise level for treatment provider was common (89%). One-third reported experience in expertise-based designs. The majority of Units had adjusted for clustering during analysis, although approaches varied. Analysis of learning was rarely performed for the main analysis (
n
= 1), although it was explored by other means. The insight behind the approaches used within and reasons for, or against, alternative approaches were provided.
Conclusions
Widespread awareness of challenges in designing and analysing multicentre trials is identified. Approaches used, and opinions on these, vary both across and within Units, indicating that approaches are dependent on the type of trial. Agreeing principles to guide trial design and analysis across a range of realistic clinical scenarios should be considered.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
/ Humans
/ Medicine
/ Multicenter Studies as Topic - economics
/ Multicenter Studies as Topic - methods
/ Multicenter Studies as Topic - statistics & numerical data
/ Practice Guidelines as Topic
/ Randomized Controlled Trials as Topic - economics
/ Randomized Controlled Trials as Topic - methods
/ Randomized Controlled Trials as Topic - statistics & numerical data
/ Statistics for Life Sciences
/ Surgery
/ Surgical Procedures, Operative
/ Survey
/ Surveys
/ Trials, Clinical Trials Unit, Clinical trial, Randomised controlled trial, Complex intervention
