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Meta-Analysis
. 2019 Feb 8;20(1):107.
doi: 10.1186/s13063-019-3222-x.

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

Azmil H Abdul-Rahim  1 , David Alexander Dickie  2 , Johann R Selvarajah  3   4 , Kennedy R Lees  2 , Terence J Quinn  2 ; VISTA Collaborators
Collaborators, Affiliations
Meta-Analysis

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

Azmil H Abdul-Rahim et al. Trials. .

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 .

Keywords: Aetiology; Classification; Stroke.

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Competing interests

The authors declare that they have no competing interests.

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Figures

Fig. 1
Fig. 1
Effect of stroke classification on trial sample size: aggregate analyses. VISTA Virtual International Stroke Trials Archive, CE cardioembolic
See this image and copyright information in PMC

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