Symptomatic Intracranial Hemorrhage After Endovascular Stroke Treatment: External Validation of Prediction Models.

BACKGROUND: Symptomatic intracranial hemorrhage (sICH) is a severe complication of reperfusion therapy for ischemic stroke. Multiple models have been developed to predict sICH or intracranial hemorrhage (ICH) after reperfusion therapy. We provide an overview of published models and validate their ability to predict sICH in patients treated with endovascular treatment in daily clinical practice. METHODS: We conducted a systematic search to identify models either developed or validated to predict sICH or ICH after reperfusion therapy (intravenous thrombolysis and/or endovascular treatment) for ischemic stroke. Models were externally validated in the MR CLEAN Registry (n=3180; Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands). The primary outcome was sICH according to the Heidelberg Bleeding Classification. Model performance was evaluated with discrimination (c-statistic, ideally 1; a c-statistic below 0.7 is considered poor in discrimination) and calibration (slope, ideally 1, and intercept, ideally 0). RESULTS: We included 39 studies describing 40 models. The most frequently used predictors were baseline National Institutes of Health Stroke Scale (NIHSS; n=35), age (n=22), and glucose level (n=22). In the MR CLEAN Registry, sICH occurred in 188/3180 (5.9%) patients. Discrimination ranged from 0.51 (SPAN-100 [Stroke Prognostication Using Age and National Institutes of Health Stroke Scale]) to 0.61 (SITS-SICH [Safe Implementation of Treatments in Stroke Symptomatic Intracerebral Hemorrhage] and STARTING-SICH [STARTING Symptomatic Intracerebral Hemorrhage]). Best calibrated models were IST-3 (intercept, -0.15 [95% CI, -0.01 to -0.31]; slope, 0.80 [95% CI, 0.50-1.09]), SITS-SICH (intercept, 0.15 [95% CI, -0.01 to 0.30]; slope, 0.62 [95% CI, 0.38-0.87]), and STARTING-SICH (intercept, -0.03 [95% CI, -0.19 to 0.12]; slope, 0.56 [95% CI, 0.35-0.76]). CONCLUSIONS: The investigated models to predict sICH or ICH discriminate poorly between patients with a low and high risk of sICH after endovascular treatment in daily clinical practice and are, therefore, not clinically useful for this patient population.

Outcome Prediction Models for Endovascular Treatment of Ischemic Stroke: Systematic Review and External Validation.

BACKGROUND AND PURPOSE: Prediction models for outcome of patients with acute ischemic stroke who will undergo endovascular treatment have been developed to improve patient management. The aim of the current study is to provide an overview of preintervention models for functional outcome after endovascular treatment and to validate these models with data from daily clinical practice. METHODS: We systematically searched within Medline, Embase, Cochrane, Web of Science, to include prediction models. Models identified from the search were validated in the MR CLEAN (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands) registry, which includes all patients treated with endovascular treatment within 6.5 hours after stroke onset in the Netherlands between March 2014 and November 2017. Predictive performance was evaluated according to discrimination (area under the curve) and calibration (slope and intercept of the calibration curve). Good functional outcome was defined as a score of 0-2 or 0-3 on the modified Rankin Scale depending on the model. RESULTS: After screening 3468 publications, 19 models were included in this validation. Variables included in the models mainly addressed clinical and imaging characteristics at baseline. In the validation cohort of 3156 patients, discriminative performance ranged from 0.61 (SPAN-100 [Stroke Prognostication Using Age and NIH Stroke Scale]) to 0.80 (MR PREDICTS). Best-calibrated models were THRIVE (The Totaled Health Risks in Vascular Events; intercept -0.06 [95% CI, -0.14 to 0.02]; slope 0.84 [95% CI, 0.75-0.95]), THRIVE-c (intercept 0.08 [95% CI, -0.02 to 0.17]; slope 0.71 [95% CI, 0.65-0.77]), Stroke Checkerboard score (intercept -0.05 [95% CI, -0.13 to 0.03]; slope 0.97 [95% CI, 0.88-1.08]), and MR PREDICTS (intercept 0.43 [95% CI, 0.33-0.52]; slope 0.93 [95% CI, 0.85-1.01]). CONCLUSIONS: The THRIVE-c score and MR PREDICTS both showed a good combination of discrimination and calibration and were, therefore, superior in predicting functional outcome for patients with ischemic stroke after endovascular treatment within 6.5 hours. Since models used different predictors and several models had relatively good predictive performance, the decision on which model to use in practice may also depend on simplicity of the model, data availability, and the comparability of the population and setting.

Surveillance of Unruptured Intracranial Aneurysms: Cost-Effectiveness Analysis for 3 Countries.

BACKGROUND AND OBJECTIVES: No consensus exists on adequate surveillance of conservatively managed unruptured intracranial aneurysms (UIAs). We aimed to determine optimal MRI surveillance strategies for the growth of UIAs using cost-effectiveness analysis. A secondary aim was to develop a clinical tool for personalizing UIA surveillance. METHODS: We designed a microsimulation model from a health care perspective simulating 100,000 55-year-old women to estimate costs and quality-adjusted life years (QALYs) over a lifetime horizon in the United States, the United Kingdom, and the Netherlands, using literature-derived model parameters. Country-specific costs and willingness-to-pay thresholds ($100,000/QALY for the United States, £30,000/QALY for the United Kingdom, and €80,000/QALY for the Netherlands) were used. Lifetime costs and QALYs were annually discounted at 3% for the United States, 3.5% for the United Kingdom, or 4% (costs) and 1.5% (QALYs) for the Netherlands. Strategies were no follow-up surveillance, follow-up with MRI in the first and fifth year after UIA discovery, every 5 years, every 2 years, or annually, or immediate intervention (i.e., clipping or coiling). Using the microsimulation model, we developed a tool for personalizing UIA surveillance for men and women, with different ages and varying aneurysm characteristics. Uncertainty in the input parameters was modeled with probabilistic sensitivity analysis. RESULTS: Among 55-year-old women, 2,222 individuals in the United States, 1,910 in the United Kingdom, and 2,040 in the Netherlands needed to undergo an annual MRI scan to prevent 1 case of subarachnoid hemorrhage per year. No surveillance MRI was most cost-effective in the United States (in 47% of the simulations) and United Kingdom (in 54% of simulations), whereas annual MRI was most cost-effective in the Netherlands (in 53% of simulations). In the United States and United Kingdom, annual surveillance or surveillance in the first and fifth year after discovery was cost-effective in patients <60 years and at increased risk of aneurysm growth. The optimal, personalized, surveillance strategies were summarized in a look-up table for use in clinical practice. DISCUSSION: Generally, the US and UK physicians should refrain from assigning patients, particularly older patients and those with few risk factors for aneurysm growth or rupture, to frequent MRI surveillance. In the Netherlands, annual follow-up is generally most cost-effective.