98%
921
2 minutes
20
Background And Objectives: Digital phenotyping (DP) enables objective measurements of patient behavior and may be a useful tool in assessments of quality-of-life and functional status in neuro-oncology patients. We aimed to identify trends in mobility among patients with glioblastoma (GBM) using DP.
Methods: A total of 15 patients with GBM enrolled in a DP study were included. The Beiwe application was used to passively collect patient smartphone global positioning system data during the study period. We estimated step count, time spent at home, total distance traveled, and number of places visited in the preoperative, immediate postoperative, and late postoperative periods. Mobility trends for patients with GBM after surgery were calculated by using local regression and were compared with preoperative values and with values derived from a nonoperative spine disease group.
Results: One month postoperatively, median values for time spent at home and number of locations visited by patients with GBM decreased by 1.48 h and 2.79 locations, respectively. Two months postoperatively, these values further decreased by 0.38 h and 1.17 locations, respectively. Compared with the nonoperative spine group, values for time spent at home and the number of locations visited by patients with GBM 1 month postoperatively were less than control values by 0.71 h and 2.79 locations, respectively. Two months postoperatively, time spent at home for patients with GBM was higher by 1.21 h and locations visited were less than nonoperative spine group values by 1.17. Immediate postoperative values for distance traveled, maximum distance from home, and radius of gyration for patients with GBM increased by 0.346 km, 2.24 km, and 1.814 km, respectively, compared with preoperative values.
Conclusions: :Trends in patients with GBM mobility throughout treatment were quantified through the use of DP in this study. DP has the potential to quantify patient behavior and recovery objectively and with minimal patient burden.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1227/neu.0000000000003051 | DOI Listing |
Radiol Case Rep
November 2025
Department of Neurosurgery, Hitachi General Hospital, 2-1-1 Jonancho, Hitachi 317-0077, Japan.
Epithelioid glioblastoma (eGBM) is a rare subtype of glioblastoma, generally associated with a poorer prognosis than conventional GBM despite maximum resection and standard chemoradiotherapy. Here, we report a case of a 78-year-old man who presented with left hemiplegia and a well-circumscribed right frontal lobe lesion on imaging, initially suspected to be a metastatic brain tumor. Surgical resection revealed a firm, clearly demarcated mass.
View Article and Find Full Text PDFJ Neurooncol
September 2025
Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Purpose: Glioblastoma (GBM) remains one of the most aggressive primary brain tumors with poor survival outcomes and a lack of approved therapies. A promising novel approach for GBM is the application of photodynamic therapy (PDT), a localized, light-activated treatment using tumor-selective photosensitizers. This narrative review describes the mechanisms, delivery systems, photosensitizers, and available evidence regarding the potential of PDT as a novel therapeutic approach for GBM.
View Article and Find Full Text PDFJ Neurooncol
September 2025
Department of Brain and Neurosciences, Division of Neurosurgery, Faculty of Medicine, Tottori University, Tottori, Japan.
Introduction: Hypertension, the most common adverse events associated with bevacizumab (BEV) treatment, has been proposed as a potential biomarker of treatment response in glioblastoma (GBM) patients. This study aimed to evaluate whether the timing of hypertension serves as a prognostic value in GBM patients.
Methods: This retrospective study consisting of 56 GBM patients treated with initial BEV between 2013 and 2024.
Brain Behav
September 2025
Department of Neurosurgery, First Medical Center of the Chinese PLA General Hospital, Beijing, People's Republic of China.
Background: The gut microbiota plays a crucial role in the development of glioma. With the evolution of artificial intelligence technology, applying AI to analyze the vast amount of data from the gut microbiome indicates the potential that artificial intelligence and computational biology hold in transforming medical diagnostics and personalized medicine.
Methods: We conducted metagenomic sequencing on stool samples from 42 patients diagnosed with glioma after operation and 30 non-intracranial tumor patients and developed a Gradient Boosting Machine (GBM) machine learning model to predict the glioma patients based on the gut microbiome data.
Adv Pharm Bull
July 2025
R.C. Patel Institute of Pharmaceutical Education and Research, Industrial Pharmacy Laboratory, Department of Pharmaceutics, Shirpur 425405, Maharashtra, India.
Treatment of glioblastoma multiforme (GBM) has been a great challenge before medical fraternity since last century owing to a median survival of less than 15 months, despite of intensive therapy. Neurosurgeries, intense chemotherapy, advanced radiotherapy, and targeted therapies have bought some extension to the life of GBM patients. Combination and targeted therapies could bring a concrete approach to tackle the complexities of GBM treatment.
View Article and Find Full Text PDF