Nomogram-Based Risk Model of Small (≤5 mm) Intracranial Aneurysm Rupture in an Eastern Asian Study - Lou, Haiyan; Nie, Kehui; Yang, Jun; Zhang, Tiesong; Wang, Jincheng; Fan, Weijian; Gu, Chenjie; Yan, Min; Chen, Tao; Zhang, Tingting; Min, Junxia; Zhan, Renya; et al. (Frontiers in Aging Neuroscience, 2022)
Background and purpose: Risk stratification of small unruptured intracranial aneurysms (<=5 mm) is important for clinical decision-making and management. The aim of this study was to develop an individualized rupture risk model of small intracranial aneurysms in eastern Asian population. Methods: This study retrospectively enrolled 343 patients with ruptured (n=96) and unruptured (n=285) small IAs. Clinical data and aneurysmal morphology were taken into consideration, regression analysis was performed to identify significant variables, and these variables were then incorporated into predictive nomogram. Diagnostic performance of the nomogram was evaluated using area under the receiver operating characteristic curve (AUC) and calibration plot. Clinical effectiveness was validated by decision curve analysis (DCA). The PHASES score calculated for each case was used for comparison. Results: The nomogram achieved an AUC of 0.849 (95% CI:0.805-0.893), with a sensitivity of 86.5% , a specificity of 70.7% and accuracy of 74.7%, which was superior to PHASES score system (AUC=0.693, sensitivity=83.6%, specificity=48.8%, accuracy=57.5%). A good agreement between predicted rupture risk and actual rupture status in the small aneurysms was observed, and DCA illustrated a benefit of using the nomogram when decisions needed to be made clinically. Conclusions: The nomogram based on clinical and morphological risk factors can be useful in assisting clinicians for individualized assessments and benefit-risk balancing in patients with small IAs (<=5 mm).