TY - JOUR
T1 - Stroke aetiological classification reliability and effect on trial sample size
T2 - Systematic review, meta-analysis and statistical modelling
AU - Abdul-Rahim, Azmil H.
AU - Dickie, David Alexander
AU - Selvarajah, Johann R.
AU - Lees, Kennedy R.
AU - Quinn, Terence J.
AU - Lees, K. R.
AU - Alexandrov, A.
AU - Bath, P. M.
AU - Berge, E.
AU - Bluhmki, E.
AU - Bornstein, N.
AU - Chen, C.
AU - Claesson, L.
AU - Davis, S. M.
AU - Donnan, G.
AU - Diener, H. C.
AU - Fisher, M.
AU - Ginsberg, M.
AU - Gregson, B.
AU - Grotta, J.
AU - Hacke, W.
AU - Hennerici, M. G.
AU - Hommel, M.
AU - Kaste, M.
AU - Lyden, P.
AU - Marler, J.
AU - Muir, K.
AU - Venketasubramanian, N.
AU - Sacco, R.
AU - Shuaib, A.
AU - Teal, P.
AU - Wahlgren, N. G.
AU - Warach, S.
AU - Weimar, C.
N1 - Publisher Copyright:
© 2019 The Author(s).
PY - 2019/2/8
Y1 - 2019/2/8
N2 - 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.
AB - 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.
KW - Aetiology
KW - Classification
KW - Stroke
UR - http://www.scopus.com/inward/record.url?scp=85061285007&partnerID=8YFLogxK
U2 - 10.1186/s13063-019-3222-x
DO - 10.1186/s13063-019-3222-x
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AN - SCOPUS:85061285007
SN - 1745-6215
VL - 20
JO - Trials
JF - Trials
IS - 1
M1 - 107
ER -