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

Azmil H. Abdul-Rahim, David Alexander Dickie, Johann R. Selvarajah, Kennedy R. Lees, Terence J. Quinn, K. R. Lees, A. Alexandrov, P. M. Bath, E. Berge, E. Bluhmki, N. Bornstein, C. Chen, L. Claesson, S. M. Davis, G. Donnan, H. C. Diener, M. Fisher, M. Ginsberg, B. Gregson, J. GrottaW. Hacke, M. G. Hennerici, M. Hommel, M. Kaste, P. Lyden, J. Marler, K. Muir, N. Venketasubramanian, R. Sacco, A. Shuaib, P. Teal, N. G. Wahlgren, S. Warach, C. Weimar

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Article number107
JournalTrials
Volume20
Issue number1
DOIs
StatePublished - Feb 8 2019

Fingerprint

Sample Size
Meta-Analysis
Stroke
Observer Variation
Anticoagulants
Recurrence
Survival
Clinical Protocols
Databases
Therapeutics

Keywords

  • Aetiology
  • Classification
  • Stroke

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Pharmacology (medical)

Cite this

Abdul-Rahim, A. H., Dickie, D. A., Selvarajah, J. R., Lees, K. R., Quinn, T. J., Lees, K. R., ... Weimar, C. (2019). Stroke aetiological classification reliability and effect on trial sample size: Systematic review, meta-analysis and statistical modelling. Trials, 20(1), [107]. https://doi.org/10.1186/s13063-019-3222-x

Stroke aetiological classification reliability and effect on trial sample size : Systematic review, meta-analysis and statistical modelling. / Abdul-Rahim, Azmil H.; Dickie, David Alexander; Selvarajah, Johann R.; Lees, Kennedy R.; Quinn, Terence J.; Lees, K. R.; Alexandrov, A.; Bath, P. M.; Berge, E.; Bluhmki, E.; Bornstein, N.; Chen, C.; Claesson, L.; Davis, S. M.; Donnan, G.; Diener, H. C.; Fisher, M.; Ginsberg, M.; Gregson, B.; Grotta, J.; Hacke, W.; Hennerici, M. G.; Hommel, M.; Kaste, M.; Lyden, P.; Marler, J.; Muir, K.; Venketasubramanian, N.; Sacco, R.; Shuaib, A.; Teal, P.; Wahlgren, N. G.; Warach, S.; Weimar, C.

In: Trials, Vol. 20, No. 1, 107, 08.02.2019.

Research output: Contribution to journalArticle

Abdul-Rahim, AH, Dickie, DA, Selvarajah, JR, Lees, KR, Quinn, TJ, Lees, KR, Alexandrov, A, Bath, PM, Berge, E, Bluhmki, E, Bornstein, N, Chen, C, Claesson, L, Davis, SM, Donnan, G, Diener, HC, Fisher, M, Ginsberg, M, Gregson, B, Grotta, J, Hacke, W, Hennerici, MG, Hommel, M, Kaste, M, Lyden, P, Marler, J, Muir, K, Venketasubramanian, N, Sacco, R, Shuaib, A, Teal, P, Wahlgren, NG, Warach, S & Weimar, C 2019, 'Stroke aetiological classification reliability and effect on trial sample size: Systematic review, meta-analysis and statistical modelling', Trials, vol. 20, no. 1, 107. https://doi.org/10.1186/s13063-019-3222-x
Abdul-Rahim, Azmil H. ; Dickie, David Alexander ; Selvarajah, Johann R. ; Lees, Kennedy R. ; Quinn, Terence J. ; Lees, K. R. ; Alexandrov, A. ; Bath, P. M. ; Berge, E. ; Bluhmki, E. ; Bornstein, N. ; Chen, C. ; Claesson, L. ; Davis, S. M. ; Donnan, G. ; Diener, H. C. ; Fisher, M. ; Ginsberg, M. ; Gregson, B. ; Grotta, J. ; Hacke, W. ; Hennerici, M. G. ; Hommel, M. ; Kaste, M. ; Lyden, P. ; Marler, J. ; Muir, K. ; Venketasubramanian, N. ; Sacco, R. ; Shuaib, A. ; Teal, P. ; Wahlgren, N. G. ; Warach, S. ; Weimar, C. / Stroke aetiological classification reliability and effect on trial sample size : Systematic review, meta-analysis and statistical modelling. In: Trials. 2019 ; Vol. 20, No. 1.
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title = "Stroke aetiological classification reliability and effect on trial sample size: Systematic review, meta-analysis and statistical modelling",
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",
author = "Abdul-Rahim, {Azmil H.} and Dickie, {David Alexander} and Selvarajah, {Johann R.} and Lees, {Kennedy R.} and Quinn, {Terence J.} and Lees, {K. R.} and A. Alexandrov and Bath, {P. M.} and E. Berge and E. Bluhmki and N. Bornstein and C. Chen and L. Claesson and Davis, {S. M.} and G. Donnan and Diener, {H. C.} and M. Fisher and M. Ginsberg and B. Gregson and J. Grotta and W. Hacke and Hennerici, {M. G.} and M. Hommel and M. Kaste and P. Lyden and J. Marler and K. Muir and N. Venketasubramanian and R. Sacco and A. Shuaib and P. Teal and Wahlgren, {N. G.} and S. Warach and C. Weimar",
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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.

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

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