Literature DB >> 34999949

Preoperative nonmedical predictors of functional impairment after brain tumor surgery.

Silvia Schiavolin1, Arianna Mariniello2, Morgan Broggi3, Francesco DiMeco3, Paolo Ferroli3, Matilde Leonardi2.   

Abstract

PURPOSE: To identify the preoperative nonmedical predictors of functional impairment after brain tumor surgery.
METHODS: Patients were evaluated before brain tumor surgery and after 3 months. The cognitive evaluation included MOCA for the general cognitive status, TMT for attention and executive functions, ROWL-IR and ROWL-DR for memory, and the F-A-S for verbal fluency. Anxiety, depression, social support, resilience, personality, disability, and quality of life were evaluated with the following patient-reported outcome measures (PROMs): HADS, OSS-3, RS-14, TIPI, WHODAS-12, and EORTC-QLQ C30. Functional status was measured with KPS. Regression analyses were performed to identify preoperative nonmedical predictors of functional impairment; PROMs and cognitive tests were compared with the normative values.
RESULTS: A total of 149 patients were enrolled (64 glioma; 85 meningioma). Increasing age, lower education, higher disability, and lower ROWL-DR scores were predictors of functional impairment in glioma patients while higher TMT scores and disability were predictors in meningioma patients. In multiple regression, only a worse performance in TMT remains a predictor in meningioma patients. Cognitive tests were not significantly worse than normative values, while psychosocial functioning was impaired.
CONCLUSION: TMT could be used in the preoperative evaluation and as a potential predictor in the research field on outcome predictors. Psychosocial functioning should be studied further and considered in a clinical context to identify who need major support and to plan tailored interventions.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Brain tumor; Cognitive function; Craniotomy; Outcome; Prediction; Psychosocial functioning

Mesh:

Year:  2022        PMID: 34999949     DOI: 10.1007/s00520-021-06732-6

Source DB:  PubMed          Journal:  Support Care Cancer        ISSN: 0941-4355            Impact factor:   3.359


  31 in total

1.  Prediction Score for Postoperative Neurologic Complications after Brain Tumor Craniotomy: A Multicenter Observational Study.

Authors:  Raphaël Cinotti; Nicolas Bruder; Mohamed Srairi; Catherine Paugam-Burtz; Hélène Beloeil; Julien Pottecher; Thomas Geeraerts; Vincent Atthar; Anaïs Guéguen; Thibault Triglia; Julien Josserand; Doris Vigouroux; Simon Viquesnel; Karim Lakhal; Michel Galliez; Yvonnick Blanloeil; Aurélie Le Thuaut; Fanny Feuillet; Bertrand Rozec; Karim Asehnoune
Journal:  Anesthesiology       Date:  2018-12       Impact factor: 7.892

2.  Pre-and Post-Surgical Health-Related Quality of Life Evaluation of Spheno-orbital Meningioma Patients Based on EORTC QLQ-C30 Questionnaire at Dr. Cipto Mangunkusumo General Hospital.

Authors:  Renindra Ananda Aman; Kumara Wisyesa; Aryandhito Widhi Nugroho; Syaiful Ichwan; David Tandian; Samsul Ashari; Setyo Widi Nugroh
Journal:  Acta Neurol Taiwan       Date:  2020-12-30

3.  Life after surgical resection of a low-grade glioma: A prospective cross-sectional study evaluating health-related quality of life.

Authors:  Ken X Teng; Benjamin Price; Shubhum Joshi; Lobna Alukaidey; Ameer Shehab; Kristy Mansour; Gurvinder S Toor; Rosemary Angliss; Katharine Drummond
Journal:  J Clin Neurosci       Date:  2021-04-22       Impact factor: 1.961

4.  Predicting functional impairment in brain tumor surgery: the Big Five and the Milan Complexity Scale.

Authors:  Paolo Ferroli; Morgan Broggi; Silvia Schiavolin; Francesco Acerbi; Valentina Bettamio; Dario Caldiroli; Alberto Cusin; Emanuele La Corte; Matilde Leonardi; Alberto Raggi; Marco Schiariti; Sergio Visintini; Angelo Franzini; Giovanni Broggi
Journal:  Neurosurg Focus       Date:  2015-12       Impact factor: 4.047

5.  Factors influencing quality of life in patients with benign primary brain tumors: prior to and following surgery.

Authors:  Shiow-Luan Tsay; Jui-Yen Chang; Patsy Yates; Kuan-Chia Lin; Shu-Yuan Liang
Journal:  Support Care Cancer       Date:  2010-11-24       Impact factor: 3.603

6.  The conditional probability of survival of patients with primary malignant brain tumors: surveillance, epidemiology, and end results (SEER) data.

Authors:  F G Davis; B J McCarthy; S Freels; V Kupelian; M L Bondy
Journal:  Cancer       Date:  1999-01-15       Impact factor: 6.860

Review 7.  Machine Learning and Neurosurgical Outcome Prediction: A Systematic Review.

Authors:  Joeky T Senders; Patrick C Staples; Aditya V Karhade; Mark M Zaki; William B Gormley; Marike L D Broekman; Timothy R Smith; Omar Arnaout
Journal:  World Neurosurg       Date:  2017-10-03       Impact factor: 2.104

Review 8.  Outcome prediction in brain tumor surgery: a literature review on the influence of nonmedical factors.

Authors:  Silvia Schiavolin; Alberto Raggi; Chiara Scaratti; Claudia Toppo; Fabiola Silvaggi; Davide Sattin; Morgan Broggi; Paolo Ferroli; Matilde Leonardi
Journal:  Neurosurg Rev       Date:  2020-05-07       Impact factor: 3.042

9.  Health-Related Quality of Life in Brain Tumor Patients Treated with Surgery: Preliminary Result of a Single Institution.

Authors:  Chang-Wook Kim; Jin-Deok Joo; Young-Hoon Kim; Jung Ho Han; Chae-Yong Kim
Journal:  Brain Tumor Res Treat       Date:  2016-10-31

10.  Predicting surgical outcome in patients with glioblastoma multiforme using pre-operative magnetic resonance imaging: development and preliminary validation of a grading system.

Authors:  Hani J Marcus; Sophie Williams; Archie Hughes-Hallett; Sophie J Camp; Dipankar Nandi; Lewis Thorne
Journal:  Neurosurg Rev       Date:  2017-02-15       Impact factor: 3.042

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