Prognostic relevance of radiological findings on early postoperative MRI for 187 consecutive glioblastoma patients receiving standard therapy.

Several prognostic factors are known to influence survival for patients treated with IDH-wildtype glioblastoma, but unknown factors may remain. We aimed to investigate the prognostic implications of early postoperative MRI findings. A total of 187 glioblastoma patients treated with standard therapy were consecutively included. Patients either underwent a biopsy or surgery followed by an early postoperative MRI. Progression-free survival (PFS) and overall survival (OS) were analysed for known prognostic factors and MRI-derived candidate factors: resection status as defined by the response assessment in neuro-oncology (RANO)-working group (no contrast-enhancing residual tumour, non-measurable contrast-enhancing residual tumour, or measurable contrast-enhancing residual tumour) with biopsy as reference, contrast enhancement patterns (no enhancement, thin linear, thick linear, diffuse, nodular), and the presence of distant tumours. In the multivariate analysis, patients with no contrast-enhancing residual tumour or non-measurable contrast-enhancing residual tumour on the early postoperative MRI displayed a significantly improved progression-free survival compared with patients receiving only a biopsy. Only patients with non-measurable contrast-enhancing residual tumour showed improved overall survival in the multivariate analysis. Contrast enhancement patterns were not associated with survival. The presence of distant tumours was significantly associated with both poor progression-free survival and overall survival and should be considered incorporated into prognostic models.

Indirect functional connectivity does not predict overall survival in glioblastoma.

BACKGROUND: Lesion network mapping (LNM) is a popular framework to assess clinical syndromes following brain injury. The classical approach involves embedding lesions from patients into a normative functional connectome and using the corresponding functional maps as proxies for disconnections. However, previous studies indicated limited predictive power of this approach in behavioral deficits. We hypothesized similarly low predictiveness for overall survival (OS) in glioblastoma (GBM). METHODS: A retrospective dataset of patients with GBM was included (n = 99). Lesion masks were registered in the normative space to compute disconnectivity maps. The brain functional normative connectome consisted in data from 173 healthy subjects obtained from the Human Connectome Project. A modified version of the LNM was then applied to core regions of GBM masks. Linear regression, classification, and principal component (PCA) analyses were conducted to explore the relationship between disconnectivity and OS. OS was considered both as continuous and categorical (low, intermediate, and high survival) variable. RESULTS: The results revealed no significant associations between OS and network disconnection strength when analyzed at both voxel-wise and classification levels. Moreover, patients stratified into different OS groups did not exhibit significant differences in network connectivity patterns. The spatial similarity among the first PCA of network maps for each OS group suggested a lack of distinctive network patterns associated with survival duration. CONCLUSIONS: Compared with indirect structural measures, functional indirect mapping does not provide significant predictive power for OS in patients with GBM. These findings are consistent with previous research that demonstrated the limitations of indirect functional measures in predicting clinical outcomes, underscoring the need for more comprehensive methodologies and a deeper understanding of the factors influencing clinical outcomes in this challenging disease.

Profiling of Tumor-Infiltrating Immune Cells and Their Impact on Survival in Glioblastoma Patients Undergoing Immunotherapy with Dendritic Cells.

Glioblastomas (GBM) are the most common primary malignant brain tumors, comprising 2% of all cancers in adults. Their location and cellular and molecular heterogeneity, along with their highly infiltrative nature, make their treatment challenging. Recently, our research group reported promising results from a prospective phase II clinical trial involving allogeneic vaccination with dendritic cells (DCs). To date, six out of the thirty-seven reported cases remain alive without tumor recurrence. In this study, we focused on the characterization of infiltrating immune cells observed at the time of surgical resection. An analytical model employing a neural network-based predictive algorithm was used to ascertain the potential prognostic implications of immunological variables on patients' overall survival. Counterintuitively, immune phenotyping of tumor-associated macrophages (TAMs) has revealed the extracellular marker PD-L1 to be a positive predictor of overall survival. In contrast, the elevated expression of CD86 within this cellular subset emerged as a negative prognostic indicator. Fundamentally, the neural network algorithm outlined here allows a prediction of the responsiveness of patients undergoing dendritic cell vaccination in terms of overall survival based on clinical parameters and the profile of infiltrated TAMs observed at the time of tumor excision.

Artificial neural network identified a 20-gene panel in predicting immunotherapy response and survival benefits after anti-PD1/PD-L1 treatment in glioblastoma patients.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are a promising immunotherapy approach, but glioblastoma clinical trials have not yielded satisfactory results. OBJECTIVE: To screen glioblastoma patients who may benefit from immunotherapy. METHODS: Eighty-one patients receiving anti-PD1/PD-L1 treatment from a large-scale clinical trial and 364 patients without immunotherapy from The Cancer Genome Atlas (TCGA) were included. Patients in the ICI-treated cohort were divided into responders and nonresponders according to overall survival (OS), and the most critical responder-relevant features were screened using random forest (RF). We constructed an artificial neural network (ANN) model and verified its predictive value with immunotherapy response and OS. RESULTS: We defined two groups of ICI-treated glioblastoma patients with large differences in survival benefits as nonresponders (OS ≤6 months, n = 18) and responders (OS ≥17 months, n = 8). No differentially mutated genes were observed between responders and nonresponders. We performed RF analysis to select the most critical responder-relevant features and developed an ANN with 20 input variables, five hidden neurons and one output neuron. Receiver operating characteristic analysis and the DeLong test demonstrated that the ANN had the best performance in predicting responders, with an AUC of 0.97. Survival analysis indicated that ANN-predicted responders had significantly better OS rates than nonresponders. CONCLUSION: The 20-gene panel developed by the ANN could be a promising biomarker for predicting immunotherapy response and prognostic benefits in ICI-treated GBM patients and may guide oncologists to accurately select potential responders for the preferential use of ICIs.

mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses.

BACKGROUND: Glioblastoma multiforme (GBM) is a type of fast-growing brain glioma associated with a very poor prognosis. This study aims to identify key genes whose expression is associated with the overall survival (OS) in patients with GBM. METHODS: A systematic review was performed using PubMed, Scopus, Cochrane, and Web of Science up to Journey 2024. Two researchers independently extracted the data and assessed the study quality according to the New Castle Ottawa scale (NOS). The genes whose expression was found to be associated with survival were identified and considered in a subsequent bioinformatic study. The products of these genes were also analyzed considering protein-protein interaction (PPI) relationship analysis using STRING. Additionally, the most important genes associated with GBM patients' survival were also identified using the Cytoscape 3.9.0 software. For final validation, GEPIA and CGGA (mRNAseq_325 and mRNAseq_693) databases were used to conduct OS analyses. Gene set enrichment analysis was performed with GO Biological Process 2023. RESULTS: From an initial search of 4104 articles, 255 studies were included from 24 countries. Studies described 613 unique genes whose mRNAs were significantly associated with OS in GBM patients, of which 107 were described in 2 or more studies. Based on the NOS, 131 studies were of high quality, while 124 were considered as low-quality studies. According to the PPI network, 31 key target genes were identified. Pathway analysis revealed five hub genes (IL6, NOTCH1, TGFB1, EGFR, and KDR). However, in the validation study, only, the FN1 gene was significant in three cohorts. CONCLUSION: We successfully identified the most important 31 genes whose products may be considered as potential prognosis biomarkers as well as candidate target genes for innovative therapy of GBM tumors.

Anti-epileptic drug use during adjuvant chemo-radiotherapy is associated with poorer survival in patients with glioblastoma: A nationwide population-based cohort study.

INTRODUCTION: There are emerging but inconsistent evidences about anti-epileptic drugs (AEDs) as radio- or chemo-sensitizers to improve survival in glioblastoma patients. We conducted a nationwide population-based study to evaluate the impact of concurrent AED during post-operative chemo-radiotherapy on outcome. MATERIAL AND METHODS: A total of 1057 glioblastoma patients were identified by National Health Insurance Research Database and Cancer Registry in 2008-2015. Eligible criteria included those receiving surgery, adjuvant radiotherapy and temozolomide, and without other cancer diagnoses. Survival between patients taking concurrent AED for 14 days or more during chemo-radiotherapy (AED group) and those who did not (non-AED group) were compared, and subgroup analyses for those with valproic acid (VPA), levetiracetam (LEV), or phenytoin were performed. Multivariate analyses were used to adjust for confounding factors. RESULTS: There were 642 patients in the AED group, whereas 415 in the non-AED group. The demographic data was balanced except trend of more patients in the AED group had previous drug history of AEDs (22.6% vs. 18%, P 0.078). Overall, the AED group had significantly increased risk of mortality (HR = 1.18, P 0.016) compared to the non-AED group. Besides, an adverse dose-dependent relationship on survival was also demonstrated in the AED group (HR = 1.118, P 0.0003). In subgroup analyses, the significant detrimental effect was demonstrated in VPA group (HR = 1.29,P 0.0002), but not in LEV (HR = 1.18, P 0.079) and phenytoin (HR = 0.98, P 0.862). CONCLUSIONS: Improved survival was not observed in patients with concurrent AEDs during chemo-radiotherapy. Our real-world data did not support prophylactic use of AEDs for glioblastoma patients.

Diagnostic and Prognostic Value of Circulating DNA Fragments in Glioblastoma Multiforme Patients.

Novel blood-circulating molecules, as potential biomarkers for glioblastoma multiforme (GBM) diagnosis and monitoring, are attracting particular attention due to limitations of imaging modalities and invasive tissue biopsy procedures. This study aims to assess the diagnostic and prognostic values of circulating cell-free DNA (cfDNA) in relation to inflammatory status in GBM patients and to determine the concentration and average size of DNA fragments typical of tumour-derived DNA fractions. Preoperative plasma samples from 40 patients (GBM 65.0 ± 11.3 years) and 40 healthy controls (HC 70.4 ± 5.4 years) were compared. The cfDNA concentrations and lengths were measured using the electrophoresis platform, and inflammatory indices (NLR, PLR, LMR, and SII) were calculated from complete blood cell analysis. More fragmented cfDNA and 4-fold higher 50-700 bp cfDNA concentrations were detected in GBM patients than in healthy controls. The average cfDNA size in the GBM group was significantly longer (median 336 bp) than in the HC group (median 271 bp). Optimal threshold values were 1265 pg/µL for 50-700 bp cfDNA (AUC = 0.857) and 290 bp for average cfDNA size (AUC = 0.814). A Kaplan-Meier survival curves analysis also demonstrated a higher mortality risk in the GBM group with a cut-off >303 bp cfDNA. This study is the first to have revealed glioblastoma association with high levels of cfDNA > 1000 pg/µL of 50-700 bp in length, which can be aggravated by immunoinflammatory reactivity.

D-Loop Mutations as Prognostic Markers in Glioblastoma-A Pilot Study.

Glioblastoma, a highly aggressive brain tumor, poses significant treatment challenges. A deeper investigation into its molecular complexity is essential for the identification of novel prognostic biomarkers and therapeutic strategies, potentially improving patient outcomes in terms of survival and quality of life. While nuclear DNA mutations have been extensively studied, the role of mitochondrial DNA (mtDNA) mutations, specifically in the D-loop region, remains poorly understood. This prospective case-control study aimed to assess the prognostic significance of the mtDNA D-loop m.16126T>C variant in glioblastoma patients. Immunohistochemistry and droplet digital PCR (ddPCR) were employed for mutation analysis, complemented by statistical analyses and a literature review. The study cohort comprised 22 glioblastoma patients (mean age 59.36 ± 14.17, 12 (54.55%) females), and 25 controls (59.48 ± 13.22, 12 (80%) females). The D-loop m.16126T>C variant was observed in four (18%) of the glioblastoma samples and was associated with shorter median survival (9.5 vs. 18 months; p = 0.016, log-rank test). This study underscores the importance of investigating mtDNA, especially D-loop variants, in glioblastoma, suggesting its potential as a prognostic biomarker and, therefore, its possible therapeutic targets, warranting further exploration.

Potential Diagnostic and Clinical Significance of Selected Genetic Alterations in Glioblastoma.

Glioblastoma is currently considered the most common and, unfortunately, also the most aggressive primary brain tumor, with the highest morbidity and mortality rates. The average survival of patients diagnosed with glioblastoma is 14 months, and only 2% of patients survive 3 years after surgery. Based on our clinical experience and knowledge from extensive clinical studies, survival is mainly related to the molecular biological properties of glioblastoma, which are of interest to the general medical community. Our study examined a total of 71 retrospective studies published from 2016 through 2022 and available on PubMed that deal with mutations of selected genes in the pathophysiology of GBM. In conclusion, we can find other mutations within a given gene group that have different effects on the prognosis and quality of survival of a patient with glioblastoma. These mutations, together with the associated mutations of other genes, as well as intratumoral heterogeneity itself, offer enormous potential for further clinical research and possible application in therapeutic practice.

Molecular characterization and survival analysis of a cohort of glioblastoma, IDH-wildtype.

Glioblastoma, IDH-wild type, the most common malignant primary central nervous system tumor, represents a formidable challenge in clinical management due to its poor prognosis and limited therapeutic responses. With an evolving understanding of its underlying biology, there is an urgent need to identify prognostic molecular groups that can be subject to targeted therapy. This study established a cohort of 124 sequential glioblastomas from a tertiary hospital and aimed to find correlations between molecular features and survival outcomes. Comprehensive molecular characterization of the cohort revealed prevalent alterations as previously described, such as TERT promoter mutations and involvement of the PI3K-Akt-mTOR, CK4/6-CDKN2A/B-RB1, and p14ARF-MDM2-MDM4-p53 pathways. MGMT promoter methylation is a significant predictor of improved overall survival, aligned with previous data. Conversely, age showed a marginal association with higher mortality. Multivariate analysis to account for the effect of MGMT promoter methylation and age showed that, in contrast to other published series, this cohort demonstrated improved survival for tumors harboring PTEN mutations, and that there was no observed difference for most other molecular alterations, including EGFR amplification, RB1 loss, or the coexistence of EGFR amplification and deletion/exon skipping (EGFRvIII). Despite limitations in sample size, this study contributes data to the molecular landscape of glioblastomas, prompting further investigations to examine these findings more closely in larger cohorts.

Analysis of the sodium pump subunit ATP1A3 in glioma patients: Potential value in prognostic prediction and immunotherapy.

The ATP1A3 gene is associated with the development and progression of neurological diseases. However, the pathological function and therapeutic value of ATP1A3 in glioblastoma (GBM) remains unknown. In this study, we tried to explore the correlation between the ATP1A3 gene expression and immune features in GBM samples. We found that ATP1A3 gene expression levels showed significant negative correlation with immune checkpoints such as PD-L1, CTLA-4 and IDO1. Next, ATP1A3 gene expression levels showed significant negative correlation with the anti-cancer immune cell process, the immune score and stromal score. By grouping ATP1A3 expression levels, we found that that immunomodulator-related genes and tumor-associated immune cell effector gene expression levels were associated with lower ATP1A3 expression. In addition, immunotherapy prediction pathway activity and a majority of the anti-cancer immune cell process activity levels were also showed to be correlated with lower ATP1A3 gene expression. Further, nine prognostic factors were identified by prognostic analysis, and a GBM prognostic model (risk score) was established. We applied the model to the TCGA GBM training set sample and the GSE4412 validation set sample and found that patients in the high risk score subgroup had significantly shorter survival time, demonstrating the prognostic value and prognostic efficacy of the risk score. Furthermore, ATP1A3 overexpression has also been found to sensitize cancer cells to anti-PD-1 therapy. In conclusion, we showed that ATP1A3 is a highly promising treatment target in GBM and the risk score is an independent prognostic factor for cancer and can be used to help guide the prediction of survival time in patients with GBM.

Simultaneous boost radiotherapy versus conventional dose radiotherapy for patients with newly diagnosed glioblastoma: a multi-institutional analysis.

We compared survival outcomes of high-dose concomitant boost radiotherapy (HDCBRT) and conventional dose radiotherapy (CRT) for newly diagnosed glioblastoma (GB). Patients treated with intensity-modulated radiation therapy for newly diagnosed GB were included. In HDCBRT, specific targets received 69, 60, and 51 Gy in 30 fractions, while 60 Gy in 30 fractions was administered with a standard radiotherapy method in CRT. Overall survival (OS) and progression-free survival (PFS) were compared using the Log-rank test, followed by multivariate Cox analysis. The inverse probability of treatment weighting (IPTW) method was also applied to each analysis. Among 102 eligible patients, 45 received HDCBRT and 57 received CRT. With a median follow-up of 16 months, the median survival times of OS and PFS were 21 and 9 months, respectively. No significant differences were observed in OS or PFS in the Kaplan-Meier analyses. In the multivariate analysis, HDCBRT correlated with improved OS (hazard ratio, 0.49; 95% confidence interval, 0.27-0.90; P = 0.021), and this result remained consistent after IPTW adjustments (P = 0.028). Conversely, dose suppression due to the proximity of normal tissues and IMRT field correlated with worse OS and PFS (P = 0.008 and 0.049, respectively). A prospective study with a stricter protocol is warranted to validate the efficacy of HDCBRT for GB.

Clinical role of NDRG2-based methylation status on survival pattern of glioblastoma.

OBJECTIVES: Gliobalstoma is the most common primary brain tumor in adults with an extensive genetic and transcriptional heterogeneity, still identification of the role of DNA methylation, as one of epigenetic alterations, is emerged. Authors aimed to study the clinical role of N-myc downstream-regulated gene 2 (NDRG2) -based methylation among GBM patients versus benign neurological diseases (BND), investigate its prognostic role and its relation with survival outcomes. METHODS: A total of 78 FFPE specimens were recruited as follows: GBM (n = 58) and BND (n = 20) then analyzed for NDRG2 methylation using Methyl II quantitative PCR system. The sensitivity and specificity of methylation was detected using receiver operating characteristic (ROC) curve and the relation with clinicopathological criteria for GBM and response to treatment were studied. Survival patterns; progression free survival (PFS) and overall survival (OS) were analyzed using Kaplan-Meier analyses. RESULTS: Mean methylation NDRG2 level was significantly increased in GBM patients as compared to BND and its sensitivity and specificity were 96.55% and 95%, respectively with area under curve (AUC) equals 0.973. Among the clinical characteristic factors, mean methylation level reported significant difference with ECOG and tumor site. Survival out comes revealed that NDRG2 methylation increased with worse PFS and OS at significant level (long rank test X2 = 13.3, p < .0001; and X2 = 7.1, p = .008, respectively). CONCLUSION: Current findings highlight the importance of studying DNA methylation of NDRG2 as a key factor to understand the role of epigenetic alterations in GBM.

The FKBP51s Splice Isoform Predicts Unfavorable Prognosis in Patients with Glioblastoma.

The primary treatment for glioblastoma (GBM) is removing the tumor mass as defined by MRI. However, MRI has limited diagnostic and predictive value. Tumor-associated macrophages (TAM) are abundant in GBM tumor microenvironment (TME) and are found in peripheral blood (PB). FKBP51 expression, with its canonical and spliced isoforms, is constitutive in immune cells and aberrant in GBM. Spliced FKBP51s supports M2 polarization. To find an immunologic signature that combined with MRI could advance in diagnosis, we immunophenotyped the macrophages of TME and PB from 37 patients with GBM using FKBP51s and classical M1-M2 markers. We also determined the tumor levels of FKBP51s, PD-L1, and HLA-DR. Tumors expressing FKBP51s showed an increase in various M2 phenotypes and regulatory T cells in PB, indicating immunosuppression. Tumors expressing FKBP51s also activated STAT3 and were associated with reduced survival. Correlative studies with MRI and tumor/macrophages cocultures allowed to interpret TAMs. Tumor volume correlated with M1 infiltration of TME. Cocultures with spheroids produced M1 polarization, suggesting that M1 macrophages may infiltrate alongside cancer stem cells. Cocultures of adherent cells developed the M2 phenotype CD163/FKBP51s expressing pSTAT6, a transcription factor enabling migration and invasion. In patients with recurrences, increased counts of CD163/FKBP51s monocyte/macrophages in PB correlated with callosal infiltration and were accompanied by a concomitant decrease in TME-infiltrating M1 macrophages. PB PD-L1/FKBP51s connoted necrotic tumors. In conclusion, FKBP51s identifies a GBM subtype that significantly impairs the immune system. Moreover, FKBP51s marks PB macrophages associated with MRI features of glioma malignancy that can aid in patient monitoring. SIGNIFICANCE: Our research suggests that by combining imaging with analysis of monocyte/macrophage subsets in patients with GBM, we can enhance our understanding of the disease and assist in its treatment. We discovered a similarity in the macrophage composition between the TME and PB, and through association with imaging, we could interpret macrophages. In addition, we identified a predictive biomarker that drew more attention to immune suppression of patients with GBM.

Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics.

Background: Extracting multiregional radiomic features from multiparametric MRI for predicting pretreatment survival in isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) patients is a promising approach. Methods: MRI data from 49 IDH wild-type glioblastoma patients pre-treatment were utilized. Diffusion and perfusion maps were generated, and tumor subregions segmented. Radiomic features were extracted for each tissue type and map. Feature selection on 1862 radiomic features identified 25 significant features. The Cox proportional-hazards model with LASSO regularization was used to perform survival analysis. Internal and external validation used a 38-patient training cohort and an 11-patient validation cohort. Statistical significance was set at p < 0.05. Results: Age and six radiomic features (shape and first and second order) from T1W, diffusion, and perfusion maps contributed to the final model. Findings suggest that a small necrotic subregion, inhomogeneous vascularization in the solid non-enhancing subregion, and edema-related tissue damage in the enhancing and edema subregions are linked to poor survival. The model's C-Index was 0.66 (95% C.I. 0.54-0.80). External validation demonstrated good accuracy (AUC > 0.65) at all time points. Conclusions: Radiomics analysis, utilizing segmented perfusion and diffusion maps, provide predictive indicators of survival in IDH wild-type glioblastoma patients, revealing associations with microstructural and vascular heterogeneity in the tumor.

Supramaximal resection: retrospective study on IDH-wildtype Glioblastomas based on the new RANO-Resect classification.

BACKGROUND: The prognostic value of the extent of resection in the management of Glioblastoma is a long-debated topic, recently widened by the 2022 RANO-Resect Classification, which advocates for the resection of the non-enhancing disease surrounding the main core of tumors (supramaximal resection, SUPR) to achieve additional survival benefits. We conducted a retrospective analysis to corroborate the role of SUPR by the RANO-Resect Classification in a single center, homogenous cohort of patients. METHODS: Records of patients operated for WHO-2021 Glioblastomas at our institution between 2007 and 2018 were retrospectively reviewed; volumetric data of resected lesions were computed and classified by RANO-Resect criteria. Survival and correlation analyses were conducted excluding patients below near-total resection. RESULTS: 117 patients met the inclusion criteria, encompassing 45 near-total resections (NTR), 31 complete resections (CR), and 41 SUPR. Median progression-free and overall survival were 11 and 15 months for NTR, 13 and 17 months or CR, 20 and 24 months for SUPR, respectively (p < 0.001), with inverse correlation observed between survival and FLAIR residual volume (r -0.28). SUPR was not significantly associated with larger preoperative volumes or higher rates of postoperative deficits, although it was less associated with preoperative neurological deficits (OR 3.37, p = 0.003). The impact of SUPR on OS varied between MGMT unmethylated (HR 0.606, p = 0.044) and methylated (HR 0.273, p = 0.002) patient groups. CONCLUSIONS: Results of the present study support the validity of supramaximal resection by the new RANO-Resect classification, also highlighting a possible surgical difference between tumors with methylated and unmethylated MGMT promoter.

Exploring management and outcomes of elderly patients with glioblastoma using data from two randomised trials (GEINO1401/EX-TEM).

PURPOSE: The impact of age on optimal management of glioblastoma remains unclear. A recent combined analysis of two randomised trials, GEINO14-01 and EX-TEM, found no benefit from extending post-radiation temozolomide in newly diagnosed glioblastoma. Here, we explore the impact of age. METHODS: Relevant intergroup statistics were used to identify differences in tumour, treatment and outcome characteristics based on age with elderly patients (EP) defined as age 65 years and over. Survival was estimated using the Kaplan Meier method. RESULTS: Of the combined 205 patients, 57 (28%) were EP. Of these, 95% were ECOG 0-1 and 65% underwent macroscopic resection compared with 97% and 61% of younger patients (YP) respectively. There were numerically less MGMT-methylated (56% vs. 63%, p = 0.4) and IDH-mutated (4% vs. 13%, p = 0.1) tumours in EP vs. YP. Following surgery, EP were more likely to receive short course chemoradiation (17.5% vs. 6%, p = 0.017). At recurrence, EP tended to receive or best supportive care (28.3% vs. 15.4%, p = 0.09) or non-surgical options (96.2% vs. 84.6%, p = 0.06), but were less likely to receive bevacizumab (23.1% vs. 49.5%, p < 0.01). Median PFS was similar at 9.3months in EP and 8.5months in YP, with similar median OS at 20months. CONCLUSION: In this trial population of predominantly fit EP, survival was similar to YP despite a proportion receiving less aggressive therapy at diagnosis and recurrence. Advancing age does not appear to be an adverse prognostic factor for glioblastoma when patients are fit for treatment, and a less aggressive approach in selected patients may not compromise outcomes.

Exploring the impact of primary care utilization and health information exchange upon treatment patterns and clinical outcomes of glioblastoma patients.

PURPOSE: There is limited literature describing care coordination for patients with glioblastoma (GBM). We aimed to investigate the impact of primary care and electronic health information exchange (HIE) between neurosurgeons, oncologists, and primary care providers (PCP) on GBM treatment patterns, postoperative outcomes, and survival. METHODS: We identified adult GBM patients undergoing primary resection at our institution (2007-2020). HIE was defined as shared electronic medical information between PCPs, oncologists, and neurosurgeons. Multivariate logistic regression analyses were used to determine the effect of PCPs and HIE upon initiation and completion of adjuvant therapy. Kaplan-Meier and multivariate Cox regression models were used to evaluate overall survival (OS). RESULTS: Among 374 patients (mean age ± SD: 57.7 ± 13.5, 39.0% female), 81.0% had a PCP and 62.4% had electronic HIE. In multivariate analyses, having a PCP was associated with initiation (OR: 7.9, P < 0.001) and completion (OR: 4.4, P < 0.001) of 6 weeks of concomitant chemoradiation, as well as initiation (OR: 4.0, P < 0.001) and completion (OR: 3.0, P = 0.007) of 6 cycles of maintenance temozolomide thereafter. Having a PCP (median OS [95%CI]: 14.6[13.1-16.1] vs. 10.8[8.2-13.3] months, P = 0.005) and HIE (15.40[12.82-17.98] vs. 13.80[12.51-15.09] months, P = 0.029) were associated with improved OS relative to counterparts in Kaplan-Meier analysis and in multivariate Cox regression analysis (hazard ratio [HR] = 0.7, [95% CI] 0.5-1.0, P = 0.048). In multivariate analyses, chemoradiation (HR = 0.34, [95% CI] 0.2-0.7, P = 0.002) and maintenance temozolomide (HR = 0.5, 95%CI 0.3-0.8, P = 0.002) were associated with improved OS relative to counterparts. CONCLUSION: Effective care coordination between neurosurgeons, oncologists, and PCPs may offer a modifiable avenue to improve GBM outcomes.

Structural changes in corticospinal tract profiling via multishell diffusion models and their relation to overall survival in glioblastoma.

PURPOSE: Advanced MR fiber tracking imaging reflects fiber bundle invasion by glioblastoma, particularly of the corticospinal tract (CST), which is more susceptible as the largest downstream fiber tracts. We aimed to investigate whether CST features can predict the overall survival of glioblastoma. METHODS: In this prospective secondary analysis, 40 participants (mean age, 58 years; 16 male) pathologically diagnosed with glioblastoma were enrolled. Diffusion spectrum MRI was used for CST reconstruction. Fifty morphological and diffusion indicators (DTI, DKI, NODDI, MAP and Q-space) were used to characterize the CST. Optimal parameters capturing fiber bundle damage were obtained through various grouping methods. Eventually, the correlation with overall survival was determined by the hazard ratios (HRs) from various Cox proportional hazard model combinations. RESULTS: Only intracellular volume fraction (ICVF) and non-Gaussianity (NG) values on the affected tumor level were significant in all four groups or stratified comparisons (all P < .05). During the median follow-up 698 days, only the ICVF on the affected tumor level was independently associated with overall survival, even after adjusting for all classic prognostic factors (HR [95 % CI]: 0.611 [0.403, 0.927], P = .021). Moreover, stratification by the ICVF on the affected tumor level successfully predicted risk (P < .01) and improved the C-index of the multivariate model (from 0.695 to 0.736). CONCLUSIONS: This study demonstrates a relationship between NODDI-derived CST features, ICVF on the affected tumor level, and overall survival in glioblastoma. Independent of classical prognostic factors for glioblastoma, a lower ICVF on the affected tumor level might predict a lower overall survival.

Adjuvant re-irradiation vs. no early re-irradiation of resected recurrent glioblastoma: pooled comparative cohort analysis from two tertiary centers.

BACKGROUND: The optimal management strategy for recurrent glioblastoma (rGBM) remains uncertain, and the impact of re-irradiation (Re-RT) on overall survival (OS) is still a matter of debate. This study included patients who achieved gross total resection (GTR) after a second surgery after recurrence, following the GlioCave criteria. METHODS: Inclusion criteria include being 18 years or older, having histologically confirmed locally recurrent IDHwt or IDH unknown GBM, achieving MRI-proven GTR after the second surgery, having a Karnofsky performance status of at least 60% after the second surgery, having a minimum interval of 6 months between the first radiotherapy and the second surgery, and a maximum of 8 weeks from second surgery to the start of Re-RT. RESULTS: A total of 44 patients have met the inclusion criteria. The median OS after the second surgery was 14 months. All patients underwent standard treatment after initial diagnosis, including maximum safe resection, adjuvant radiochemotherapy and adjuvant chemotherapy. Re-RT did not significantly impact OS. However, MGMT promoter methylation status and a longer interval (> 12 months) between treatments were associated with better OS. Multivariate analysis revealed the MGMT status as the only significant predictor of OS. CONCLUSION: Factors such as MGMT promoter methylation status and treatment interval play crucial roles in determining patient outcomes after second surgery. Personalized treatment strategies should consider these factors to optimize the management of rGBM. Prospective research is needed to define the value of re-RT after second surgery and to inform decision making in this situation.