Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome

BACKGROUND: Despite previous identification of pre-operative clinical and radiological predictors of post-operative paediatric cerebellar mutism syndrome (CMS), a unifying pre-operative risk stratification model for use during surgical consent is currently lacking. The aim of the project is to devel...

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Main Authors: Liu, Jo-Fen, Dineen, Robert A., Avula, Shivaram, Chambers, Tom, Dutta, Manali, Jaspan, Tim, MacArthur, Donald C., Howarth, Simon, Soria, Daniele, Quinlan, Philip, Harave, Srikrishna, Ong, Chan Chang, Mallucci, Conor L., Kumar, Ram, Pizer, Barry, Walker, David A.
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Published: Taylor & Francis 2018
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Online Access:https://eprints.nottingham.ac.uk/51348/
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author Liu, Jo-Fen
Dineen, Robert A.
Avula, Shivaram
Chambers, Tom
Dutta, Manali
Jaspan, Tim
MacArthur, Donald C.
Howarth, Simon
Soria, Daniele
Quinlan, Philip
Harave, Srikrishna
Ong, Chan Chang
Mallucci, Conor L.
Kumar, Ram
Pizer, Barry
Walker, David A.
author_facet Liu, Jo-Fen
Dineen, Robert A.
Avula, Shivaram
Chambers, Tom
Dutta, Manali
Jaspan, Tim
MacArthur, Donald C.
Howarth, Simon
Soria, Daniele
Quinlan, Philip
Harave, Srikrishna
Ong, Chan Chang
Mallucci, Conor L.
Kumar, Ram
Pizer, Barry
Walker, David A.
author_sort Liu, Jo-Fen
building Nottingham Research Data Repository
collection Online Access
description BACKGROUND: Despite previous identification of pre-operative clinical and radiological predictors of post-operative paediatric cerebellar mutism syndrome (CMS), a unifying pre-operative risk stratification model for use during surgical consent is currently lacking. The aim of the project is to develop a simple imaging-based pre-operative risk scoring scheme to stratify patients in terms of post-operative CMS risk. METHODS: Pre-operative radiological features were recorded for a retrospectively assembled cohort of 89 posterior fossa tumour patients from two major UK treatment centers (age 2-23yrs; gender 28 M, 61 F; diagnosis: 38 pilocytic astrocytoma, 32 medulloblastoma, 12 ependymoma, 1 high grade glioma, 1 pilomyxoid astrocytoma, 1 atypical teratoid rhabdoid tumour, 1 hemangioma, 1 neurilemmoma, 2 oligodendroglioma). Twenty-six (29%) developed post-operative CMS. Based upon results from univariate analysis and C4.5 decision tree, stepwise logistic regression was used to develop the optimal model and generate risk scores. RESULTS: Univariate analysis identified five significant risk factors and C4.5 decision tree analysis identified six predictors. Variables included in the final model are MRI primary location, bilateral middle cerebellar peduncle involvement (invasion and/or compression), dentate nucleus invasion and age at imaging >12.4 years. This model has an accuracy of 88.8% (79/89). Using risk score cut-off of 203 and 238, respectively, allowed discrimination into low (38/89, predicted CMS probability <3%), intermediate (17/89, predicted CMS probability 3-52%) and high-risk (34/89, predicted CMS probability ≥52%). CONCLUSIONS: A risk stratification model for post-operative paediatric CMS could flag patients at increased or reduced risk pre-operatively which may influence strategies for surgical treatment of cerebellar tumours. Following future testing and prospective validation, this risk scoring scheme will be proposed for use during the surgical consenting process.
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spelling nottingham-513482024-08-15T15:26:32Z https://eprints.nottingham.ac.uk/51348/ Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome Liu, Jo-Fen Dineen, Robert A. Avula, Shivaram Chambers, Tom Dutta, Manali Jaspan, Tim MacArthur, Donald C. Howarth, Simon Soria, Daniele Quinlan, Philip Harave, Srikrishna Ong, Chan Chang Mallucci, Conor L. Kumar, Ram Pizer, Barry Walker, David A. BACKGROUND: Despite previous identification of pre-operative clinical and radiological predictors of post-operative paediatric cerebellar mutism syndrome (CMS), a unifying pre-operative risk stratification model for use during surgical consent is currently lacking. The aim of the project is to develop a simple imaging-based pre-operative risk scoring scheme to stratify patients in terms of post-operative CMS risk. METHODS: Pre-operative radiological features were recorded for a retrospectively assembled cohort of 89 posterior fossa tumour patients from two major UK treatment centers (age 2-23yrs; gender 28 M, 61 F; diagnosis: 38 pilocytic astrocytoma, 32 medulloblastoma, 12 ependymoma, 1 high grade glioma, 1 pilomyxoid astrocytoma, 1 atypical teratoid rhabdoid tumour, 1 hemangioma, 1 neurilemmoma, 2 oligodendroglioma). Twenty-six (29%) developed post-operative CMS. Based upon results from univariate analysis and C4.5 decision tree, stepwise logistic regression was used to develop the optimal model and generate risk scores. RESULTS: Univariate analysis identified five significant risk factors and C4.5 decision tree analysis identified six predictors. Variables included in the final model are MRI primary location, bilateral middle cerebellar peduncle involvement (invasion and/or compression), dentate nucleus invasion and age at imaging >12.4 years. This model has an accuracy of 88.8% (79/89). Using risk score cut-off of 203 and 238, respectively, allowed discrimination into low (38/89, predicted CMS probability <3%), intermediate (17/89, predicted CMS probability 3-52%) and high-risk (34/89, predicted CMS probability ≥52%). CONCLUSIONS: A risk stratification model for post-operative paediatric CMS could flag patients at increased or reduced risk pre-operatively which may influence strategies for surgical treatment of cerebellar tumours. Following future testing and prospective validation, this risk scoring scheme will be proposed for use during the surgical consenting process. Taylor & Francis 2018-02-12 Article PeerReviewed Liu, Jo-Fen, Dineen, Robert A., Avula, Shivaram, Chambers, Tom, Dutta, Manali, Jaspan, Tim, MacArthur, Donald C., Howarth, Simon, Soria, Daniele, Quinlan, Philip, Harave, Srikrishna, Ong, Chan Chang, Mallucci, Conor L., Kumar, Ram, Pizer, Barry and Walker, David A. (2018) Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome. British Journal of Neurosurgery . ISSN 0268-8697 Cerebellar mutism; paediatric brain tumours; posterior fossa syndrome; posterior fossa tumours; pre-operative risk assessment https://www.tandfonline.com/doi/full/10.1080/02688697.2018.1431204 doi:10.1080/02688697.2018.1431204 doi:10.1080/02688697.2018.1431204
spellingShingle Cerebellar mutism; paediatric brain tumours; posterior fossa syndrome; posterior fossa tumours; pre-operative risk assessment
Liu, Jo-Fen
Dineen, Robert A.
Avula, Shivaram
Chambers, Tom
Dutta, Manali
Jaspan, Tim
MacArthur, Donald C.
Howarth, Simon
Soria, Daniele
Quinlan, Philip
Harave, Srikrishna
Ong, Chan Chang
Mallucci, Conor L.
Kumar, Ram
Pizer, Barry
Walker, David A.
Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome
title Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome
title_full Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome
title_fullStr Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome
title_full_unstemmed Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome
title_short Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome
title_sort development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome
topic Cerebellar mutism; paediatric brain tumours; posterior fossa syndrome; posterior fossa tumours; pre-operative risk assessment
url https://eprints.nottingham.ac.uk/51348/
https://eprints.nottingham.ac.uk/51348/
https://eprints.nottingham.ac.uk/51348/