Stroke aetiological classification reliability and effect on trial sample size: systematic review, meta-analysis and statistical modelling

Abdul-Rahim, A. H. , Dickie, D. A. , Selvarajah, J. R., Lees, K. R. and Quinn, T. J. (2019) Stroke aetiological classification reliability and effect on trial sample size: systematic review, meta-analysis and statistical modelling. Trials, 20, 107. (doi: 10.1186/s13063-019-3222-x) (PMID:30736833) (PMCID:PMC6368715)

Abstract

Background: Inter-observer variability in stroke aetiological classification may have an effect on trial power and estimation of treatment effect. We modelled the effect of misclassification on required sample size in a hypothetical cardioembolic (CE) stroke trial. Methods: We performed a systematic review to quantify the reliability (inter-observer variability) of various stroke aetiological classification systems. We then modelled the effect of this misclassification in a hypothetical trial of anticoagulant in CE stroke contaminated by patients with non-cardioembolic (non-CE) stroke aetiology. Rates of misclassification were based on the summary reliability estimates from our systematic review. We randomly sampled data from previous acute trials in CE and non-CE participants, using the Virtual International Stroke Trials Archive. We used bootstrapping to model the effect of varying misclassification rates on sample size required to detect a between-group treatment effect across 5000 permutations. We described outcomes in terms of survival and stroke recurrence censored at 90 days. Results: From 4655 titles, we found 14 articles describing three stroke classification systems. The inter-observer reliability of the classification systems varied from ‘fair’ to ‘very good’ and suggested misclassification rates of 5% and 20% for our modelling. The hypothetical trial, with 80% power and alpha 0.05, was able to show a difference in survival between anticoagulant and antiplatelet in CE with a sample size of 198 in both trial arms. Contamination of both arms with 5% misclassified participants inflated the required sample size to 237 and with 20% misclassification inflated the required sample size to 352, for equivalent trial power. For an outcome of stroke recurrence using the same data, base-case estimated sample size for 80% power and alpha 0.05 was n = 502 in each arm, increasing to 605 at 5% contamination and 973 at 20% contamination. Conclusions: Stroke aetiological classification systems suffer from inter-observer variability, and the resulting misclassification may limit trial power. Trial registration: Protocol available at reviewregistry540.

• Item Type: Articles
• Additional Information: The project was supported by an unrestricted grant from the Neurosciences Foundation; DAD is supported by a Stroke Association post-doctoral fellowship; TJQ is supported by a joint Chief Scientist Office/Stroke Association Senior Clinical Lecturer Fellowship; JRS is supported by a National Health Service Research Scotland (NRS) Fellowship.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Abdul-Rahim, Dr Azmil and Quinn, Professor Terry and Lees, Professor Kennedy and Selvarajah, Dr Johann and Dickie, Dr David Alexander
• Authors: Abdul-Rahim, A. H., Dickie, D. A., Selvarajah, J. R., Lees, K. R., and Quinn, T. J.
• College/School: College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health; College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience; College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing
• Journal Name: Trials
• Publisher: BioMed Central
• ISSN: 1745-6215
• ISSN (Online): 1745-6215
• Copyright Holders: Copyright © 2019 The Authors
• First Published: First published in Trials 20: 107
• Publisher Policy: Reproduced under a Creative Commons License