Predicting major bleeding in patients with noncardioembolic stroke on antiplatelets

Nina A. Hilkens, Ale Algra, Hans Christoph Diener, Johannes B. Reitsma, Philip M. Bath, L. Csiba, Werner Hacke, L. Jaap Kappelle, Peter J. Koudstaal, Didier Leys, Jean Louis Mas, Ralph L. Sacco, Pierre Amarenco, Leila Sissani, Jacoba P. Greving

Research output: Contribution to journalArticle

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Abstract

Objective: To develop and externally validate a prediction model for major bleeding in patients with a TIA or ischemic stroke on antiplatelet agents. Methods: We combined individual patient data from 6 randomized clinical trials (CAPRIE, ESPS-2, MATCH, CHARISMA, ESPRIT, and PRoFESS) investigating antiplatelet therapy after TIA or ischemic stroke. Cox regression analyses stratified by trial were performed to study the association between predictors and major bleeding. A risk prediction model was derived and validated in the PERFORM trial. Performance was assessed with the c statistic and calibration plots. Results: Major bleeding occurred in 1,530 of the 43,112 patients during 94,833 person-years of follow-up. The observed 3-year risk of major bleeding was 4.6% (95% confidence interval [CI] 4.4%-4.9%). Predictors were male sex, smoking, type of antiplatelet agents (aspirin-clopidogrel), outcome on modified Rankin Scale ≥3, prior stroke, high blood pressure, lower body mass index, elderly, Asian ethnicity, and diabetes (S 2 TOP-BLEED). The S 2 TOP-BLEED score had a c statistic of 0.63 (95% CI 0.60-0.64) and showed good calibration in the development data. Major bleeding risk ranged from 2% in patients aged 45-54 years without additional risk factors to more than 10% in patients aged 75-84 years with multiple risk factors. In external validation, the model had a c statistic of 0.61 (95% CI 0.59-0.63) and slightly underestimated major bleeding risk. Conclusions: The S 2 TOP-BLEED score can be used to estimate 3-year major bleeding risk in patients with a TIA or ischemic stroke who use antiplatelet agents, based on readily available characteristics. The discriminatory performance may be improved by identifying stronger predictors of major bleeding.

Original languageEnglish
Pages (from-to)936-943
Number of pages8
JournalNeurology
Volume89
Issue number9
DOIs
Publication statusPublished - Aug 29 2017

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Stroke
Hemorrhage
Platelet Aggregation Inhibitors
clopidogrel
Confidence Intervals
Calibration
Aspirin
Body Mass Index
Randomized Controlled Trials
Smoking
Regression Analysis
Hypertension

ASJC Scopus subject areas

  • Clinical Neurology

Cite this

Hilkens, N. A., Algra, A., Diener, H. C., Reitsma, J. B., Bath, P. M., Csiba, L., ... Greving, J. P. (2017). Predicting major bleeding in patients with noncardioembolic stroke on antiplatelets. Neurology, 89(9), 936-943. https://doi.org/10.1212/WNL.0000000000004289

Predicting major bleeding in patients with noncardioembolic stroke on antiplatelets. / Hilkens, Nina A.; Algra, Ale; Diener, Hans Christoph; Reitsma, Johannes B.; Bath, Philip M.; Csiba, L.; Hacke, Werner; Jaap Kappelle, L.; Koudstaal, Peter J.; Leys, Didier; Mas, Jean Louis; Sacco, Ralph L.; Amarenco, Pierre; Sissani, Leila; Greving, Jacoba P.

In: Neurology, Vol. 89, No. 9, 29.08.2017, p. 936-943.

Research output: Contribution to journalArticle

Hilkens, NA, Algra, A, Diener, HC, Reitsma, JB, Bath, PM, Csiba, L, Hacke, W, Jaap Kappelle, L, Koudstaal, PJ, Leys, D, Mas, JL, Sacco, RL, Amarenco, P, Sissani, L & Greving, JP 2017, 'Predicting major bleeding in patients with noncardioembolic stroke on antiplatelets', Neurology, vol. 89, no. 9, pp. 936-943. https://doi.org/10.1212/WNL.0000000000004289
Hilkens, Nina A. ; Algra, Ale ; Diener, Hans Christoph ; Reitsma, Johannes B. ; Bath, Philip M. ; Csiba, L. ; Hacke, Werner ; Jaap Kappelle, L. ; Koudstaal, Peter J. ; Leys, Didier ; Mas, Jean Louis ; Sacco, Ralph L. ; Amarenco, Pierre ; Sissani, Leila ; Greving, Jacoba P. / Predicting major bleeding in patients with noncardioembolic stroke on antiplatelets. In: Neurology. 2017 ; Vol. 89, No. 9. pp. 936-943.
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AU - Hilkens, Nina A.

AU - Algra, Ale

AU - Diener, Hans Christoph

AU - Reitsma, Johannes B.

AU - Bath, Philip M.

AU - Csiba, L.

AU - Hacke, Werner

AU - Jaap Kappelle, L.

AU - Koudstaal, Peter J.

AU - Leys, Didier

AU - Mas, Jean Louis

AU - Sacco, Ralph L.

AU - Amarenco, Pierre

AU - Sissani, Leila

AU - Greving, Jacoba P.

PY - 2017/8/29

Y1 - 2017/8/29

N2 - Objective: To develop and externally validate a prediction model for major bleeding in patients with a TIA or ischemic stroke on antiplatelet agents. Methods: We combined individual patient data from 6 randomized clinical trials (CAPRIE, ESPS-2, MATCH, CHARISMA, ESPRIT, and PRoFESS) investigating antiplatelet therapy after TIA or ischemic stroke. Cox regression analyses stratified by trial were performed to study the association between predictors and major bleeding. A risk prediction model was derived and validated in the PERFORM trial. Performance was assessed with the c statistic and calibration plots. Results: Major bleeding occurred in 1,530 of the 43,112 patients during 94,833 person-years of follow-up. The observed 3-year risk of major bleeding was 4.6% (95% confidence interval [CI] 4.4%-4.9%). Predictors were male sex, smoking, type of antiplatelet agents (aspirin-clopidogrel), outcome on modified Rankin Scale ≥3, prior stroke, high blood pressure, lower body mass index, elderly, Asian ethnicity, and diabetes (S 2 TOP-BLEED). The S 2 TOP-BLEED score had a c statistic of 0.63 (95% CI 0.60-0.64) and showed good calibration in the development data. Major bleeding risk ranged from 2% in patients aged 45-54 years without additional risk factors to more than 10% in patients aged 75-84 years with multiple risk factors. In external validation, the model had a c statistic of 0.61 (95% CI 0.59-0.63) and slightly underestimated major bleeding risk. Conclusions: The S 2 TOP-BLEED score can be used to estimate 3-year major bleeding risk in patients with a TIA or ischemic stroke who use antiplatelet agents, based on readily available characteristics. The discriminatory performance may be improved by identifying stronger predictors of major bleeding.

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