Background and Purpose- Clinical trials in spontaneous intracerebral hemorrhage (ICH) have used volume cutoffs as inclusion criteria to select populations in which the effects of interventions are likely to be the greatest. However, optimal volume cutoffs for predicting poor outcome in deep locations (thalamus versus basal ganglia) are unknown. Methods- We conducted a 2-phase study to determine ICH volume cutoffs for poor outcome (modified Rankin Scale score of 4-6) in the thalamus and basal ganglia. Cutoffs with optimal sensitivity and specificity for poor outcome were identified in the ERICH ([Ethnic/Racial Variations of ICH] study; derivation cohort) using receiver operating characteristic curves. The cutoffs were then validated in the ATACH-2 trial (Antihypertensive Treatment of Acute Cerebral Hemorrhage-2) by comparing the c-statistic of regression models for outcome (including dichotomized volume) in the validation cohort. Results- Of the 3000 patients enrolled in ERICH, 1564 (52%) had deep ICH, of whom 1305 (84%) had complete neuroimaging and outcome data (660 thalamic and 645 basal ganglia hemorrhages). Receiver operating characteristic curve analysis identified 8 mL in thalamic (area under the curve, 0.79; sensitivity, 73%; specificity, 78%) and 18 mL in basal ganglia ICH (area under the curve, 0.79; sensitivity, 70%; specificity, 83%) as optimal cutoffs for predicting poor outcome. The validation cohort included 834 (84%) patients with deep ICH and complete neuroimaging data enrolled in ATACH-2 (353 thalamic and 431 basal ganglia hemorrhages). In thalamic ICH, the c-statistic of the multivariable outcome model including dichotomized ICH volume was 0.80 (95% CI, 0.75-0.85) in the validation cohort. For basal ganglia ICH, the c-statistic was 0.81 (95% CI, 0.76-0.85) in the validation cohort. Conclusions- Optimal hematoma volume cutoffs for predicting poor outcome in deep ICH vary by the specific deep brain nucleus involved. Utilization of location-specific volume cutoffs may improve clinical trial design by targeting deep ICH patients that will obtain maximal benefit from candidate therapies.
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