Development of preoperative and postoperative models to predict recurrence in postoperative glioma patients: a longitudinal cohort study

Glioma recurrence, subsequent to maximal safe resection, remains a pivotal challenge. This study aimed to identify key clinical predictors influencing recurrence and develop predictive models to enhance neurological diagnostics and therapeutic strategies. This longitudinal cohort study with a substa...

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Bibliographic Details
Published in:BMC cancer 2024-02, Vol.24 (1), p.274-274, Article 274
Main Authors: Qiao, Wanyu, Wang, Yi, Luo, Chen, Wu, Jinsong, Qin, Guoyou, Zhang, Jie, Yao, Ye
Format: Article
Language:English
Subjects:
Age
Analysis
Brain cancer
Brain Neoplasms - pathology
Cancer
Care and treatment
Chemotherapy
Cohort Studies
Cox regression
Datasets
Diagnosis
Glioblastoma
Glioblastoma - complications
Glioma
Glioma - pathology
Gliomas
Humans
Longitudinal Studies
Medical prognosis
Medical research
Medicine, Experimental
Mortality
Nomograms
Patients
Pediatrics
Postoperative care
Postoperative glioma recurrence
Prediction models
Predictive model
Proportional Hazards Models
Radiation therapy
Regression analysis
Relapse
Retrospective Studies
Risk factors
Surgery
Tumors
Variables
Citations: Items that this one cites
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Summary:Glioma recurrence, subsequent to maximal safe resection, remains a pivotal challenge. This study aimed to identify key clinical predictors influencing recurrence and develop predictive models to enhance neurological diagnostics and therapeutic strategies. This longitudinal cohort study with a substantial sample size (n = 2825) included patients with non-recurrent glioma who were pathologically diagnosed and had undergone initial surgical resection between 2010 and 2018. Logistic regression models and stratified Cox proportional hazards models were established with the top 15 clinical variables significantly influencing outcomes screened by the least absolute shrinkage and selection operator (LASSO) method. Preoperative and postoperative models predicting short-term (within 6 months) postoperative recurrence in glioma patients were developed to explore the risk factors associated with short- and long-term recurrence in glioma patients. Preoperative and postoperative logistic models predicting short-term recurrence had accuracies of 0.78 and 0.87, respectively. A range of biological and early symptomatic characteristics linked to short- and long-term recurrence have been pinpointed. Age, headache, muscle weakness, tumor location and Karnofsky score represented significant odd ratios (t > 2.65, p  4.12, p 
ISSN:1471-2407
1471-2407
DOI:10.1186/s12885-024-11996-2