Prediction model for 3-year rupture risk of unruptured cerebral aneurysms in Japanese patients

Unruptured Cerebral Aneurysm Study Japan Investigators

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103 Citations (Scopus)


Objective To build a prediction model that estimates the 3-year rupture risk of unruptured saccular cerebral aneurysms. Methods Survival analysis was done using each aneurysm as the unit for analysis. Derivation data were from the Unruptured Cerebral Aneurysm Study (UCAS) in Japan. It consists of patients with unruptured cerebral aneurysms enrolled between 2000 and 2004 at neurosurgical departments at tertiary care hospitals in Japan. The model was presented as a scoring system, and aneurysms were classified into 4 risk grades by predicted 3-year rupture risk: I, < 1%; II, 1 to 3%; III, 3 to 9%, and IV, >9%. The discrimination property and calibration plot of the model were evaluated with external validation data. They were a combination of 3 Japanese cohort studies: UCAS II, the Small Unruptured Intracranial Aneurysm Verification study, and the study at Jikei University School of Medicine. Results The derivation data include 6,606 unruptured cerebral aneurysms in 5,651 patients. During the 11,482 aneurysm-year follow-up period, 107 ruptures were observed. The predictors chosen for the scoring system were patient age, sex, and hypertension, along with aneurysm size, location, and the presence of a daughter sac. The 3-year risk of rupture ranged from <1% to >15% depending on the individual characteristics of patients and aneurysms. External validation indicated good discrimination and calibration properties. Interpretation A simple scoring system that only needs easily available patient and aneurysmal information was constructed. This can be used in clinical decision making regarding management of unruptured cerebral aneurysms.

Original languageEnglish
Pages (from-to)1050-1059
Number of pages10
JournalAnnals of Neurology
Issue number6
Publication statusPublished - Jun 1 2015

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology


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