Cargando…

Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study

BACKGROUND AND PURPOSE: Approximately 15%–45% of patients with unruptured intracranial aneurysms have multiple intracranial aneurysms (MIAs). Determining which one is most likely to rupture is extremely important for treatment decision making for MIAs patients. This study aimed to develop and valida...

Descripción completa

Detalles Bibliográficos
Autores principales: Feng, Xin, Tong, Xin, Peng, Fei, Niu, Hao, Qi, Peng, Lu, Jun, Zhao, Yang, Jin, Weitao, Wu, Zhongxue, Zhao, Yuanli, Liu, Aihua, Wang, Daming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485246/
https://www.ncbi.nlm.nih.gov/pubmed/33547231
http://dx.doi.org/10.1136/svn-2020-000480
_version_ 1784577494846799872
author Feng, Xin
Tong, Xin
Peng, Fei
Niu, Hao
Qi, Peng
Lu, Jun
Zhao, Yang
Jin, Weitao
Wu, Zhongxue
Zhao, Yuanli
Liu, Aihua
Wang, Daming
author_facet Feng, Xin
Tong, Xin
Peng, Fei
Niu, Hao
Qi, Peng
Lu, Jun
Zhao, Yang
Jin, Weitao
Wu, Zhongxue
Zhao, Yuanli
Liu, Aihua
Wang, Daming
author_sort Feng, Xin
collection PubMed
description BACKGROUND AND PURPOSE: Approximately 15%–45% of patients with unruptured intracranial aneurysms have multiple intracranial aneurysms (MIAs). Determining which one is most likely to rupture is extremely important for treatment decision making for MIAs patients. This study aimed to develop and validate a nomogram to evaluate the per-aneurysm rupture risk of MIAs patients. METHODS: A total of 1671 IAs from 700 patients with MIAs were randomly dichotomised into derivation and validation sets. Multivariate logistic regression analysis was used to select predictors and construct a nomogram model for aneurysm rupture risk assessment in the derivation set. The discriminative accuracy, calibration performance and clinical usefulness of this nomogram were assessed. We also developed a multivariate model for a subgroup of 158 subarachnoid haemorrhage (SAH) patients and compared its performance with the nomogram model. RESULTS: Multivariate analyses identified seven variables that were significantly associated with IA rupture (history of SAH, alcohol consumption, female sex, aspect ratio >1.5, posterior circulation, irregular shape and bifurcation location). The clinical and morphological-based MIAs (CMB-MIAs) nomogram model showed good calibration and discrimination (derivation set: area under the curve (AUC)=0.740 validation set: AUC=0.772). Decision curve analysis demonstrated that the nomogram was clinically useful. Compared with the nomogram model, the AUC of multivariate model developed from SAH patients had lower value of 0.730. CONCLUSIONS: This CMB-MIAs nomogram for MIAs rupture risk is the first to be developed and validated in a large multi-institutional cohort. This nomogram could be used in decision-making and risk stratification in MIAs patients.
format Online
Article
Text
id pubmed-8485246
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BMJ Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-84852462021-10-08 Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study Feng, Xin Tong, Xin Peng, Fei Niu, Hao Qi, Peng Lu, Jun Zhao, Yang Jin, Weitao Wu, Zhongxue Zhao, Yuanli Liu, Aihua Wang, Daming Stroke Vasc Neurol Original Research BACKGROUND AND PURPOSE: Approximately 15%–45% of patients with unruptured intracranial aneurysms have multiple intracranial aneurysms (MIAs). Determining which one is most likely to rupture is extremely important for treatment decision making for MIAs patients. This study aimed to develop and validate a nomogram to evaluate the per-aneurysm rupture risk of MIAs patients. METHODS: A total of 1671 IAs from 700 patients with MIAs were randomly dichotomised into derivation and validation sets. Multivariate logistic regression analysis was used to select predictors and construct a nomogram model for aneurysm rupture risk assessment in the derivation set. The discriminative accuracy, calibration performance and clinical usefulness of this nomogram were assessed. We also developed a multivariate model for a subgroup of 158 subarachnoid haemorrhage (SAH) patients and compared its performance with the nomogram model. RESULTS: Multivariate analyses identified seven variables that were significantly associated with IA rupture (history of SAH, alcohol consumption, female sex, aspect ratio >1.5, posterior circulation, irregular shape and bifurcation location). The clinical and morphological-based MIAs (CMB-MIAs) nomogram model showed good calibration and discrimination (derivation set: area under the curve (AUC)=0.740 validation set: AUC=0.772). Decision curve analysis demonstrated that the nomogram was clinically useful. Compared with the nomogram model, the AUC of multivariate model developed from SAH patients had lower value of 0.730. CONCLUSIONS: This CMB-MIAs nomogram for MIAs rupture risk is the first to be developed and validated in a large multi-institutional cohort. This nomogram could be used in decision-making and risk stratification in MIAs patients. BMJ Publishing Group 2021-02-05 /pmc/articles/PMC8485246/ /pubmed/33547231 http://dx.doi.org/10.1136/svn-2020-000480 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Feng, Xin
Tong, Xin
Peng, Fei
Niu, Hao
Qi, Peng
Lu, Jun
Zhao, Yang
Jin, Weitao
Wu, Zhongxue
Zhao, Yuanli
Liu, Aihua
Wang, Daming
Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study
title Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study
title_full Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study
title_fullStr Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study
title_full_unstemmed Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study
title_short Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study
title_sort development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485246/
https://www.ncbi.nlm.nih.gov/pubmed/33547231
http://dx.doi.org/10.1136/svn-2020-000480
work_keys_str_mv AT fengxin developmentandvalidationofanovelnomogramtopredictaneurysmruptureinpatientswithmultipleintracranialaneurysmsamulticentreretrospectivestudy
AT tongxin developmentandvalidationofanovelnomogramtopredictaneurysmruptureinpatientswithmultipleintracranialaneurysmsamulticentreretrospectivestudy
AT pengfei developmentandvalidationofanovelnomogramtopredictaneurysmruptureinpatientswithmultipleintracranialaneurysmsamulticentreretrospectivestudy
AT niuhao developmentandvalidationofanovelnomogramtopredictaneurysmruptureinpatientswithmultipleintracranialaneurysmsamulticentreretrospectivestudy
AT qipeng developmentandvalidationofanovelnomogramtopredictaneurysmruptureinpatientswithmultipleintracranialaneurysmsamulticentreretrospectivestudy
AT lujun developmentandvalidationofanovelnomogramtopredictaneurysmruptureinpatientswithmultipleintracranialaneurysmsamulticentreretrospectivestudy
AT zhaoyang developmentandvalidationofanovelnomogramtopredictaneurysmruptureinpatientswithmultipleintracranialaneurysmsamulticentreretrospectivestudy
AT jinweitao developmentandvalidationofanovelnomogramtopredictaneurysmruptureinpatientswithmultipleintracranialaneurysmsamulticentreretrospectivestudy
AT wuzhongxue developmentandvalidationofanovelnomogramtopredictaneurysmruptureinpatientswithmultipleintracranialaneurysmsamulticentreretrospectivestudy
AT zhaoyuanli developmentandvalidationofanovelnomogramtopredictaneurysmruptureinpatientswithmultipleintracranialaneurysmsamulticentreretrospectivestudy
AT liuaihua developmentandvalidationofanovelnomogramtopredictaneurysmruptureinpatientswithmultipleintracranialaneurysmsamulticentreretrospectivestudy
AT wangdaming developmentandvalidationofanovelnomogramtopredictaneurysmruptureinpatientswithmultipleintracranialaneurysmsamulticentreretrospectivestudy