Introduction Overall, intra-arterial treatment (IAT) proved to be beneficial in patients with acute ischaemic stroke due to a proximal occlusion in the anterior circulation. However, heterogeneity in treatment benefit may be relevant for personalised clinical decision-making. Our aim is to improve selection of patients for IAT by predicting individual treatment benefit or harm. Methods and analysis We will use data collected in the Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands (MR CLEAN) trial to analyse the effect of baseline characteristics on outcome and treatment effect. A multivariable proportional odds model with interaction terms will be developed to predict the outcome for each individual patient, both with and without IAT. Model performance will be expressed as discrimination and calibration, after bootstrap resampling and shrinkage of regression coefficients, to correct for optimism. External validation will be conducted on data of patients in the Interventional Management of Stroke III trial (IMS III). Primary outcome will be the modified Rankin Scale (mRS) at 90 days after stroke. Ethics and dissemination The proposed study will provide an internationally applicable clinical decision aid for IAT. Findings will be disseminated widely through peer-reviewed publications, conference presentations and in an online web application tool. Formal ethical approval was not required as primary data were already collected. Trial registration numbers ISRCTN10888758; Post-results and NCT00359424; Post-resultsc.

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Keywords decision aid, intra-arterial therapy, ischaemic stroke, mechanical thrombectomy, personalised treatment, prediction model
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Journal BMJ Open
Mulder, M.J.H.L, Venema, E, Roozenbeek, B, Broderick, J.P, Yeatts, S.D, Khatri, P, … Lingsma, H.F. (2017). Towards personalised intra-arterial treatment of patients with acute ischaemic stroke: A study protocol for development and validation of a clinical decision aid. BMJ Open, 7(3). doi:10.1136/bmjopen-2016-013699