Bevacizumab has demonstrated activity in patients with recurrent glioblastoma. However, the impact of prognostic factors associated with recurrent glioblastoma treated with cytotoxic agents has not been determined in patients treated with bevacizumab. To analyze the prognostic factors and clinical benefits of bevacizumab and irinotecan treatment in patients with recurrent glioblastoma. This monocentric study retrospectively analyzed all patients with recurrent glioblastoma who were treated with at least one cycle of bevacizumab and irinotecan at our institution from April 2007 to May 2010. Multivariate analysis was used to analyze prognostic factors for overall survival (OS) from the initiation of bevacizumab administration. Among the 100 patients that were identified (M/F: 65/35), the median age was 57.9 years (range: 18-76). Karnofsky Performance Status (KPS) was <70 in 44 patients and ≥ 70 in 56 patients; 83 % of the patients were on steroids. The median tumor area was 2012 mm². The median progression free survival was 3.9 months (CI 95 %: 3.4-4.3). The median OS was 6.5 months (CI 95 %: 5.6-7.4). Multivariate analysis revealed that OS was affected by KPS (p = 0.024), but not by gender, age, steroid treatment, number of previous lines of treatment, tumor size, or time from initial diagnosis. KPS was improved in 30 patients, including 14/44 patients with an initial KPS <70. The median duration of maintained functional independence (KPS ≥ 70) was 3.75 months (CI 95 %: 2.9-4.6). The median OS from initial diagnosis was 18.9 months (CI 95 %: 17.5-20.3). In patients with recurrent glioblastoma treated with bevacizumab, KPS was revealed as the only factor to impact OS. The clinical benefits associated with this regimen appear valuable. A positive impact of bevacizumab administration on OS of patients with glioblastoma multiforme is suggested.
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http://dx.doi.org/10.1007/s11060-013-1170-y | DOI Listing |
Eur Radiol
January 2025
Department of Neurointervention, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Objectives: This study aims to investigate the prognostic value of Temporal Muscle Thickness (TMT) in Chinese patients with newly diagnosed isocitrate dehydrogenase (IDH) wild-type glioblastoma.
Methods: Data were retrospectively collected from patients with isocitrate dehydrogenase wild-type genotype glioblastoma, who underwent surgical treatment and concurrent chemoradiotherapy at our center between May 2019 and May 2023. Multi-model and multivariate Cox regression were used to examine factors associated with overall and progression-free survival.
Clin Neurol Neurosurg
January 2025
Department of Neurological Surgery, Pauline Braathen Neurological Center, Cleveland Clinic Florida, Weston, FL, USA. Electronic address:
Early prediction of recurrence in high-grade glioma (HGG) is critical due to its aggressive nature and poor prognosis. Distinguishing true recurrence from treatment-related changes, such as radionecrosis, is a major diagnostic challenge. Machine learning (ML) offers a novel approach, leveraging advanced algorithms to analyze complex imaging data with high precision.
View Article and Find Full Text PDFCell Reprogram
January 2025
Department of Pharmacy, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
Glioblastoma multiforme (GBM) is a highly invasive brain tumor, and traditional treatments combining surgery with radiochemotherapy have limited effects, with tumor recurrence being almost inevitable. Given the lack of proliferative capacity in neurons, inducing terminal differentiation of GBM cells or glioma stem cells (GSCs) into neuron-like cells has emerged as a promising strategy. This approach aims to suppress their proliferation and self-renewal capabilities through differentiation.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
This study aimed to investigate the genetic association between glioblastoma (GBM) and unsupervised deep learning-derived imaging phenotypes (UDIPs). We employed a combination of genome-wide association study (GWAS) data, single-nucleus RNA sequencing (snRNA-seq), and scPagwas (pathway-based polygenic regression framework) methods to explore the genetic links between UDIPs and GBM. Two-sample Mendelian randomization analyses were conducted to identify causal relationships between UDIPs and GBM.
View Article and Find Full Text PDFFront Immunol
January 2025
Department of Oncology, Suining Central Hospital, Suining, Sichuan, China.
Glioblastoma(GBM) is a highly malignant primary central nervous system tumor that poses a significant threat to patient survival due to its treatment resistance and rapid recurrence.Current treatment options, including maximal safe surgical resection, radiotherapy, and temozolomide (TMZ) chemotherapy, have limited efficacy.In recent years, the role of glycolytic metabolic reprogramming in GBM has garnered increasing attention.
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