Selection of patients for intra-arterial treatment for acute ischaemic stroke: development and validation of a clinical decision tool in two randomised trials

Abstract

Objective To improve the selection of patients with acute ischaemic stroke for intra-arterial treatment using a clinical decision tool to predict individual treatment benefit.Design Multivariable regression modelling with data from two randomised controlled clinical trials.Setting 16 hospitals in the Netherlands (derivation cohort) and 58 hospitals in the United States, Canada, Australia, and Europe (validation cohort).Participants 500 patients from the Multicenter Randomised Clinical Trial of Endovascular Treatment for Acute Ischaemic Stroke in the Netherlands trial (derivation cohort) and 260 patients with intracranial occlusion from the Interventional Management of Stroke III trial (validation cohort).Main outcome measures The primary outcome was the modified Rankin Scale (mRS) score at 90 days after stroke. We constructed an ordinal logistic regression model to predict outcome and treatment benefit, defined as the difference between the predicted probability of good functional outcome (mRS score 0-2) with and without intra-arterial treatment.Results 11 baseline clinical and radiological characteristics were included in the model. The externally validated C statistic was 0.69 (95% confidence interval 0.64 to 0.73) for the ordinal model and 0.73 (0.67 to 0.79) for the prediction of good functional outcome, indicating moderate discriminative ability. The mean predicted treatment benefit varied between patients in the combined derivation and validation cohort from -2.3% to 24.3%. There was benefit of intra-arterial treatment predicted for some individual patients from groups in which no treatment effect was found in previous subgroup analyses, such as those with no or poor collaterals.Conclusion The proposed clinical decision tool combines multiple baseline clinical and radiological characteristics and shows large variations in treatment benefit between patients. The tool is clinically useful as it aids in distinguishing between individual patients who may experience benefit from intra-arterial treatment for acute ischaemic stroke and those who will not.Trial registration clinicaltrials.gov NCT00359424 (IMS III) and isrctn.com ISRCTN10888758 (MR CLEAN).

Conflict of interest statement

Competing interests: All authors have completed the ICMJE uniform disclosure form. JPB received study medication for intra-arterial tissue type plasminogen activator from Genentech and catheters were supplied by EKOS Corporation, Concentric Medical, and Cordis. His research is funded by the Department of Neurology and Rehabilitation Medicine. He is remunerated by Genentech for his role on the Steering Committee for A Study of the Efficacy and Safety of Activase (Alteplase) in Patients With Mild Stroke (PRISMS) trial. SDY is remunerated by Genentech for her statistical role in the PRISMS trial. PK is remunerated by Genentech for her role as lead principal investigator of the PRISMS trial and by Penumbra for her role as neurology principal investigator of the Assess the Penumbra System in the Treatment of Acute Stroke trial. She has also received royalties from UpToDate and consulted for Grand Rounds, St Jude Medical, and Biogen. BJE is remunerated for his role as CE mark reviewer by DEKRA and by Novartis for educational lectures. Erasmus MC received funds from Stryker for consultations by DWJD and AL and for training courses by BJE, and from Bracco Imaging for consultations by DWJD. The Academic Medical Centre received funds from Stryker for consultations by CBLMM and YBWEMR. Maastricht University Medical Centre received funds from Stryker and Codman for consultations by WHZ.

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Figures

Fig 1 Univariable interaction effects in derivation cohort (n=500). Interaction with treatment is expressed as log odds for good functional outcome (modified Rankin Scale score 0-2) with and without intra-arterial treatment on the y axis. Variables on x axis are expressed continuously (time to groin puncture) or categorically (previous stroke, atrial fibrillation, and collateral score)

Fig 2 Calibration plot for predicted good functional outcome, defined as modified Rankin Scale (mRS) score 0-2, in validation cohort (n=260). The calibration slope reflects the strength of predictors. The calibration intercept reflects the calibration in the large, indicating whether predicted probabilities are systematically too low or too high. The overall observed proportion of patients with mRS score 0-2 in the validation cohort was higher as to be expected using our model. The linear bar chart shows the distribution of patients with (=1) or without (=0) an observed outcome of mRS score 0-2. Discrimination between low and high likelihood of good functional outcome was moderate (C statistic 0.73, 95% confidence interval 0.67 to 0.79)

Fig 3 (A) Predicted probabilities of good functional outcome (modified Rankin Scale (mRS) score 0-2) for all individual patients in combined derivation and validation cohort (n=760). Each dot represents one individual patient, with the probability of good functional outcome (mRS score 0-2) without intra-arterial treatment (IAT) expressed on x axis, and probability for good functional outcome with IAT on y axis. Above the diagonal line the predicted probability of good functional outcome with IAT is higher than that without IAT. The farther above this line, the larger the predicted effect of treatment. (B) Patients highlighted with no or poor collaterals (score 0-1). (C) Patients highlighted with low Alberta Stroke Program Early CT score (ASPECTS, score 0-5)

Fig 4 A stylised representation of the clinical decision tool. Baseline characteristics and predicted probabilities of good functional outcome (modified Rankin Scale (mRS) score 0-2) for two examples (see introduction). ASPECT=Alberta Stroke Program Early Computed Tomography Score; IAT=intra-arterial treatment; NIHSS=National Institutes of Health Stroke Scale; ICA=internal carotid artery; CTA=computed tomography angiography