Enrollment bias: frequency and impact on patient selection in endovascular stroke trials.

BackgroundSelection bias may have affected enrollment in first generation endovascular stroke trials. We investigate, evaluate, and quantify such bias for these trials at our institution.MethodsDemographic, clinical, imaging, and angiographic data were prospectively collected on a consecutive cohort of patients with acute ischemic stroke who were enrolled in formal trials of endovascular stroke therapy (EST) or received EST in clinical practice outside of a randomized trial for acute cerebral ischemia at a single tertiary referral center from September 2004 to December 2012.ResultsAmong patients considered appropriate for EST in practice, 47% were eligible for trials, with rates for individual trials ranging from 17% to 70%. Compared with trial ineligible patients treated with EST, trial eligible patients were younger (67 vs. 74 years; p<0.05), more often treated with intravenous tissue plasminogen activator (53% vs. 34%; p<0.01), and had shorter last known well to puncture times (328 vs. 367 min; p<0.05). Focusing on the largest trial with a non-interventional control arm, compared with trial eligible patients treated with EST outside the trial, enrolled patients presented later (274 vs. 163 min; p<0.001), had higher National Institutes of Health Stroke Scale scores (20 vs. 17; p<0.05), and larger strokes (diffusion weighted imaging volumes 49 vs. 18; p<0.001).ConclusionsThe majority of patients felt suitable for EST at our institution were excluded from recent trials. Formal entry criteria succeeded in selecting patients with better prognostic features, although many of these patients were treated outside of trials. Acknowledging and mitigating these biases will be crucial to ongoing investigations

Enrollment bias: frequency and impact on patient selection in endovascular stroke trials.

BackgroundSelection bias may have affected enrollment in first generation endovascular stroke trials. We investigate, evaluate, and quantify such bias for these trials at our institution.MethodsDemographic, clinical, imaging, and angiographic data were prospectively collected on a consecutive cohort of patients with acute ischemic stroke who were enrolled in formal trials of endovascular stroke therapy (EST) or received EST in clinical practice outside of a randomized trial for acute cerebral ischemia at a single tertiary referral center from September 2004 to December 2012.ResultsAmong patients considered appropriate for EST in practice, 47% were eligible for trials, with rates for individual trials ranging from 17% to 70%. Compared with trial ineligible patients treated with EST, trial eligible patients were younger (67 vs. 74 years; p<0.05), more often treated with intravenous tissue plasminogen activator (53% vs. 34%; p<0.01), and had shorter last known well to puncture times (328 vs. 367 min; p<0.05). Focusing on the largest trial with a non-interventional control arm, compared with trial eligible patients treated with EST outside the trial, enrolled patients presented later (274 vs. 163 min; p<0.001), had higher National Institutes of Health Stroke Scale scores (20 vs. 17; p<0.05), and larger strokes (diffusion weighted imaging volumes 49 vs. 18; p<0.001).ConclusionsThe majority of patients felt suitable for EST at our institution were excluded from recent trials. Formal entry criteria succeeded in selecting patients with better prognostic features, although many of these patients were treated outside of trials. Acknowledging and mitigating these biases will be crucial to ongoing investigations

Multiparametric Magnetic Resonance Imaging for Prediction of Parenchymal Hemorrhage in Acute Ischemic Stroke After Reperfusion Therapy.

Background and purposePatients with acute ischemic stroke are at increased risk of developing parenchymal hemorrhage (PH), particularly in the setting of reperfusion therapies. We have developed a predictive model to examine the risk of PH using combined magnetic resonance perfusion and diffusion parameters, including cerebral blood volume (CBV), apparent diffusion coefficient, and microvascular permeability (K2).MethodsVoxel-based values of CBV, K2, and apparent diffusion coefficient from the ischemic core were obtained using pretreatment magnetic resonance imaging data from patients enrolled in the MR RESCUE clinical trial (Mechanical Retrieval and Recanalization of Stroke Clots Using Embolectomy). The associations between PH and extreme values of imaging parameters were assessed in univariate and multivariate analyses. Receiver-operating characteristic curve analysis was performed to determine the optimal parameter(s) and threshold for predicting PH.ResultsIn 83 patients included in this analysis, 20 developed PH. Univariate analysis showed significantly lower 10th percentile CBV and 10th percentile apparent diffusion coefficient values and significantly higher 90th percentile K2 values within the infarction core of patients with PH. Using classification tree analysis, the 10th percentile CBV at threshold of 0.47 and 90th percentile K2 at threshold of 0.28 resulted in overall predictive accuracy of 88.7%, sensitivity of 90.0%, and specificity of 87.3%, which was superior to any individual or combination of other classifiers.ConclusionsOur results suggest that combined 10th percentile CBV and 90th percentile K2 is an independent predictor of PH in patients with acute ischemic stroke with diagnostic accuracy superior to individual classifiers alone. This approach may allow risk stratification for patients undergoing reperfusion therapies.Clinical trial registrationURL: https://www.clinicaltrials.gov. Unique identifier: NCT00389467

Multiparametric Magnetic Resonance Imaging for Prediction of Parenchymal Hemorrhage in Acute Ischemic Stroke After Reperfusion Therapy

Background and Purpose— Patients with acute ischemic stroke are at increased risk of developing parenchymal hemorrhage (PH), particularly in the setting of reperfusion therapies. We have developed a predictive model to examine the risk of PH using combined magnetic resonance perfusion and diffusion parameters, including cerebral blood volume (CBV), apparent diffusion coefficient, and microvascular permeability (K2). Methods— Voxel-based values of CBV, K2, and apparent diffusion coefficient from the ischemic core were obtained using pretreatment magnetic resonance imaging data from patients enrolled in the MR RESCUE clinical trial (Mechanical Retrieval and Recanalization of Stroke Clots Using Embolectomy). The associations between PH and extreme values of imaging parameters were assessed in univariate and multivariate analyses. Receiver-operating characteristic curve analysis was performed to determine the optimal parameter(s) and threshold for predicting PH. Results— In 83 patients included in this analysis, 20 developed PH. Univariate analysis showed significantly lower 10th percentile CBV and 10th percentile apparent diffusion coefficient values and significantly higher 90th percentile K2 values within the infarction core of patients with PH. Using classification tree analysis, the 10th percentile CBV at threshold of 0.47 and 90th percentile K2 at threshold of 0.28 resulted in overall predictive accuracy of 88.7%, sensitivity of 90.0%, and specificity of 87.3%, which was superior to any individual or combination of other classifiers. Conclusions— Our results suggest that combined 10th percentile CBV and 90th percentile K2 is an independent predictor of PH in patients with acute ischemic stroke with diagnostic accuracy superior to individual classifiers alone. This approach may allow risk stratification for patients undergoing reperfusion therapies. Clinical Trial Registration— URL: https://www.clinicaltrials.gov. Unique identifier: NCT00389467

Abstract 161: Prediction of Thrombolysis-induced Parenchymal Hemorrhage in Patients With Acute Ischemic Stroke: Use of MR Perfusion and Diffusion Biomarkers

Purpose: Ischemic stroke patients with low cerebral blood volume (CBV), low apparent diffusion coefficient (ADC) and increased microvascular permeability (K2) have increased risk of parenchymal hemorrhage (PH) after recanalization therapies. We have developed a predictive model to examine the risk of PH following revascularization therapies using combined MR perfusion and diffusion biomarkers. Methods: Voxel-based values of rCBV, K2, and ADC from the infarction core were obtained using pre-treatment MRI data from patients enrolled in the Mechanical Retrieval and Recanalization of Stroke Clots Using Embolectomy (MR RESCUE) clinical trial. Using histogram analyses the 10 th and 90 th percentile values were calculated for the rCBV, ADC, and K2 variables for each patient. The associations between PH and extreme values of CBV (10%rCBV), ADC (10%ADC), and K2 (90%K2) in each patient were assessed in univariate and multivariate analyses. Receiver operating characteristic (ROC) analysis was performed to determine the optimal parameter/s and threshold for predicting PH. Results: In 83 patients included in this analysis, 20 (24%, 13 PH1, 7 PH2) developed PH. Univariate analysis showed significantly lower 10%rCBV and 10%ADC values and significantly higher 90%K2 values in patients with PH. After controlling for age, baseline NIHSS, infarct volume, and status of recanalization, multivariate logistic regression analysis identified 10%rCBV (p=0.002) and 90%K2 (p=0.03), but not 10%ADC (p=0.07), as independent predictors of PH. For 10%RCBV, ROC analysis showed the greatest AUC (0.87) at a threshold 0.27 with sensitivity/specificity of 90%/60%. In a separate model, a combined K2-rCBV classifier remained the single independent predictor of PH (OR=33). Conclusion: Our results suggest that combined increased permeability and decreased rCBV derived from MR perfusion can be used for risk stratification in patients with AIS before undergoing revascularization therapies