Direct oral anticoagulants vs. low-molecular-weight heparin for pulmonary embolism in patients with glioblastoma.

Glioblastoma (GBM) is a cancer type with high thrombogenic potential and GBM patients are therefore at a particularly high risk for thrombotic events. To date, only limited data on anticoagulation management after pulmonary embolism (PE) in GBM is available and the sporadic use of DOACs remains off-label. A retrospective cohort analysis of patients with GBM and postoperative, thoracic CT scan confirmed PE was performed. Clinical course, follow-up at 6 and 12 months and the overall survival (OS) were evaluated using medical charts and neuroradiological data. Out of 584 GBM patients, 8% suffered from postoperative PE. Out of these, 30% received direct oral anticoagulants (DOACs) and 70% low-molecular-weight heparin (LMWH) for therapeutic anticoagulation. There was no significant difference in major intracranial hemorrhage (ICH), re-thrombosis, or re-embolism between the two cohorts. Although statistically non-significant, a tendency to reduced mRS at 6 and 12 months was observed in the LMWH cohort. Furthermore, patients receiving DOACs had a statistical benefit in OS. In our analysis, DOACs showed a satisfactory safety profile in terms of major ICH, re-thrombosis, and re-embolism compared to LMWH in GBM patients with postoperative PE. Prospective, randomized trials are urgent to evaluate DOACs for therapeutic anticoagulation in GBM patients with PE.

Impact of Rural vs. Urban Residence on Survival Rates of Patients with Glioblastoma: A Tertiary Care Center Experience.

Purpose: Although the association between residential location and survival in patients with different cancer types has been established, the conclusions are contentious, and the underlying mechanisms remain unknown. Here, we reviewed the impact of residence on the survival of patients with glioblastoma (GBM). Methods: We conducted a retrospective study to compare the impact of rural and urban residence on the survival rates of patients with GBM diagnosed in Riyadh City and outside Riyadh. All patients in this study were treated in a tertiary care hospital, and their survival rates were analyzed in relation to their residence and other related factors, namely radiotherapy timing. Results: Overall, 125 patients were included: 61 from Riyadh City and 64 from outside. The majority of patients in both groups were aged >50 years (p = 0.814). There was no statistically significant difference between the groups in the Eastern Cooperative Oncology Group Performance Status (p = 0.430), seizure (p = 0.858), or initiation timing of radiotherapy (p = 0.781). Furthermore, the median survival rate in the Riyadh group versus the other group was 14.4 months and 12.2 months, respectively, with no statistical significance (p = 0.187). Conclusions: Our study showed that residential location had no significant effect on GBM prognosis. However, further studies with a larger sample size are required to delineate the other factors of referral within the healthcare system to facilitate the management of these patients within a specific timeframe.

Therapeutic Anticoagulation Impacts MR Morphologic Recurrence Patterns in Glioblastoma-A Matched-Pair Analysis.

BACKGROUND: Glioblastoma (GBM) patients are at particularly high risk for thrombotic complications. In the event of a postoperative pulmonary embolism, therapeutic anticoagulation (tAC) is indispensable. The impact of therapeutic anticoagulation on recurrence pattern in GBM is currently unknown. METHODS: We conducted a matched-pair cohort analysis of 57 GBM patients with or without tAC that were matched for age, sex, gross total resection and MGMT methylation status in a ratio of 1:2. Patients' characteristics and clinical course were evaluated using medical charts. MRI characteristics were evaluated by two independent authors blinded to the AC status. RESULTS: The morphologic MRI appearance in first GBM recurrence showed a significantly higher presence of multifocal, midline crossing and sharp demarcated GBM recurrence patterns in patients with therapeutic tAC compared to the matched control group. Although statistically non-significant, the therapeutic tAC cohort showed increased survival. CONCLUSION: Therapeutic anticoagulation induced significant morphologic changes in GBM recurrences. The underlying pathophysiology is discussed in this article but remains to be further elucidated.

Ten-year survival in glioblastoma patient with neurofibromatosis type 1: illustrative case.

BACKGROUND: Gliomas are commonly detected in patients with neurofibromatosis type 1 (NF1) at an early age. Few patients with NF1 are diagnosed with glioblastoma. The course of management, response to therapy, and prognosis of such patients are unknown. Few reports have shown longer-than-average survival rates for patients with NF1 with glioblastoma. OBSERVATIONS: A 27-year-old man with NF1 presented with symptoms of high intracranial pressure. Imaging and pathology showed left frontotemporal glioblastoma. Gross total resection was achieved, and concurrent chemoradiotherapy was administered. Recurrence of tumor was detected 48 months later, and the patient underwent tumor debulking and concurrent chemoradiotherapy. The patient received first-, second-, and third-line chemotherapy (temozolomide, bevacizumab, bevacizumab/irinotecan) with good tolerance and has survived >10 years since then with good functional status. LESSONS: This case demonstrates >10 years overall survival of glioblastoma in a patient with NF1. Reports of patients with NF1 with longer survival may be attributed to the young age at diagnosis and relatively better tolerance for therapy. It might also support the growing evidence of a unique subset of glioblastoma associated with NF1 and opens the door for a more molecular targeted therapy in the future.

Survival prediction in glioblastoma on post-contrast magnetic resonance imaging using filtration based first-order texture analysis: Comparison of multiple machine learning models.

OBJECTIVE: Magnetic resonance texture analysis (MRTA) is a relatively new technique that can be a valuable addition to clinical and imaging parameters in predicting prognosis. In the present study, we investigated the efficacy of MRTA for glioblastoma survival using T1 contrast-enhanced (CE) images for texture analysis. METHODS: We evaluated the diagnostic performance of multiple machine learning models based on first-order histogram statistical parameters derived from T1-weighted CE images in the survival stratification of glioblastoma multiforme (GBM). Retrospective evaluation of 85 patients with GBM was performed. Thirty-six first-order texture parameters at six spatial scale filters (SSF) were extracted on the T1 CE axial images for the whole tumor using commercially available research software. Several machine learning classification models (in four broad categories: linear, penalized linear, non-linear, and ensemble classifiers) were evaluated to assess the survival prediction performance using optimal features. Principal component analysis was used prior to fitting the linear classifiers in order to reduce the dimensionality of the feature inputs. Fivefold cross-validation was used to partition the data iteratively into training and testing sets. The area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance. RESULTS: The neural network model was the highest performing model with the highest observed AUC (0.811) and cross-validated AUC (0.71). The most important variable was the age at diagnosis, with mean and mean of positive pixels (MPP) for SSF = 0 being the second and third most important, followed by skewness for SSF = 0 and SSF = 4. CONCLUSIONS: First-order texture features, when combined with age at presentation, show good accuracy in predicting GBM survival.