High grade gliomas (HGGs) have remained particularly difficult to treat with no noteworthy improvements reported in the past years. This lack of progress is partly because of the invasive nature displayed by HGGs, which are able to easily infiltrate the surrounding parenchyma, making complete surgical resection impossible. Additionally, HGGs present a significant number of genetic and epigenetic alterations with an enormous impact on heterogeneity, inter and intracellular signaling, immune system dampening, resistance to treatment and proliferation. The current therapeutic standard, first established in 2005, has a low therapeutic index and presents a large number of side effects 1).
Amongst some the most important causes for the poor outcome are the immune privileged status of the brain and the immune suppressing attributes of the tumor and its microenvironment. Initially, it was thought that the Blood Brain Barrier was the reason behind this phenomenon; however, this theory has been disproven 2) 3) 4).
Glioblastoma patients who were readmitted within 30 days had significantly shorter survival than nonreadmitted patients. Future studies that attempt to decrease readmissions and evaluate the impact of reducing readmissions on patient outcomes are needed 5).
The outcome of patients with anaplastic gliomas varies considerably depending on single molecular markers, such as mutations of the isocitrate dehydrogenase (IDH) genes, as well as molecular classifications based on epigenetic or genetic profiles.
Despite advances in treatment, the median patient survival is 12 to 15 months 7).
Malignant brain tumor, including the most common type glioblastoma, are histologically heterogeneous and invasive tumors known as the most devastating neoplasms with high morbidity and mortality. Despite multimodal treatment including surgery, radiotherapy, chemotherapy, and immunotherapy, the disease inevitably recurs and is fatal. This lack of curative options has motivated researchers to explore new treatment strategies and to develop new drug delivery systems (DDSs); however, the unique anatomical, physiological, and pathological features of brain tumors greatly limit the effectiveness of conventional chemotherapy 8).
The current standard of care in glioblastoma is not very effective, resulting in tumor recurrence with patients rarely surviving over 2 years. This tumor recurrence is attributed to the presence of chemo and radiation resistant glioma stem cells (GSCs).
The hallmark of glioblastoma multiforme (GBM) is its penchant for relentless progression. The median progression free survival (PFS) is 4.4 to 8.4 months in patients with newly diagnosed GBM following the current standard of care, safely obtained maximal resection at initial surgery followed by concomitant temozolomide (TMZ) and radiotherapy and adjuvant TMZ.
Glioblastoma multiforme is the most aggressive type of primary brain tumors, but there is a small percentage of patients who have a long-term survival and some exceptional cases who survive decades after surgical removal of tumor 9)
Currently, the best that can be offered is a modest 14-month overall median survival in patients undergoing maximum safe resection plus adjuvant chemoradiotherapy. 10).
Less than 10% of patients live longer than 5 years from diagnosis 11).
Prognostic factors involved in survival include age, performance status, grade, specific markers (MGMT methylation, mutation of IDH1, IDH2 or TERT, 1p19q codeletion, overexpression of EGFR, etc.) and, likely, the extent of resection. Certain adjuncts to surgery, especially cortical mapping and 5-ALA fluorescence, favor higher rates of gross total resection with apparent positive impact on survival. Recurrent tumors can be offered re-intervention, participation in clinical trials, anti-angiogenic agent or local electric field therapy, without an evident impact on survival. Molecular-targeted therapies, immunotherapy and gene therapy are promising tools currently under research 12).
Kawano et al., observed a gradual improvement in glioblastoma multiforme outcome, presumably because of improvements in therapeutic modalities for surgery, anticancer agents, and radiation, but the efficacy of CyberKnife-SRT remains unclear 13)
However, removal of the final 1%–2% of the contrast-enhancing tumor carries not only the greatest impact from an oncological point of view but also the greatest risk for neurological impairment, especially in glioblastomas adjacent to motor eloquent areas.
Prognostic markers in glioblastoma multiforme is complex. In addition to previously recognized prognostic variables such as age and Karnofsky performance score, tumor size, total resection and proliferative index were identified as predictors of survival in a series of patients with glioblastoma multiforme 15).
Many reports on glioblastoma multiforme discuss the prognostic impact of anatomical features such as cysts, necrotic changes, extent of edema or subependymal spread of tumor cells.
A merely anatomical analysis of the glioblastoma growth pattern cannot reliably provide prognostic information. The occurrence of most recurrences next to the resection margin and the high percentage of growing residual tumors underline the importance of complete resections 16).
Patients with tumours having small geometric heterogeneity and/or spherical rim widths had significantly better prognosis. These imaging biomarkers have a strong individual and combined prognostic value for GBM patients 17) 18).
Multi-channel MR image derived texture features, tumor shape, and volumetric features, and patient age were obtained for 163 GBM patients. In order to assess the impact of tumor shape features on OS prediction, two feature sets, with and without tumor shape features, were created. For the feature set with tumor shape features, the mean prediction error (MPE) was 14.6 days and its 95% confidence interval (CI) was 195.8 days. For the feature set excluding shape features, the MPE was 17.1 days and its 95% CI was observed to be 212.7 days. The coefficient of determination (R2) value obtained for the feature set with shape features was 0.92, while it was 0.90 for the feature set excluding shape features. Although marginal, inclusion of shape features improves OS prediction in GBM patients. The proposed OS prediction method using regression provides good accuracy and overcomes the limitations of GBM OS classification, like choosing data-derived or pre-decided thresholds to define the OS groups. Graphical abstract Two feature sets: with and without tumor shape features were extracted from T1-weighted contrast-enhanced, T2-weighted and FLAIR MRI. These feature sets were analyzed using the Mean Prediction Error (MPE) and its 95% Confidence Interval (CI) obtained from the Bland-Altman plot, along with the coefficient of determination (R2) value to assess the impact of tumor shape features on overall survival prediction of glioblastoma multiforme patients 19).
Neurologic status is one of the major prognostic factor; however, no consensus exists on a clinical index for predicting patient outcomes.
One proposed neurologic index enables significantly identifying glioblastoma patients receiving tumor resection with poor outcomes, independent of other common prognostic factors. Using the index provides a preoperative predictor of prognosis in glioblastoma patients receiving tumor resection 20).
In glioblastoma, progression-free survival (PFS) and overall survival (OS) are strongly correlated, indicating that PFS may be an appropriate surrogate for OS. Compared with OS, PFS offers earlier assessment and higher statistical power at the time of analysis 21).
Prior studies that have reported only the readmissions back to index hospitals are likely underestimating the true 30-day readmission rate. GBM patients who were readmitted within 30 days had significantly shorter survival than nonreadmitted patients. Future studies that attempt to decrease readmissions and evaluate the impact of reducing readmissions on patient outcomes are needed 22).
Several clinical studies have reported that valproic acid could prolong survival of GBM patients. However, the results of these studies are inconsistent.
A bibliographic search was performed in the EMBASE, MEDLINE, ClinicalTrials.gov and Cochrane Central Register of the Controlled Trials databases to identify potentially relevant articles or conference abstracts that investigated the effects of VPA on the outcome of glioma patients. Five observational studies were included.
Pooled estimates of the hazard ratio (HR) and 95% confidence intervals (CI) were calculated. The meta-analysis confirmed the benefit of using VPA (HR, 0.56; 95% CI, 0.44-0.71). Sub-group analysis shows that patients treated with VPA had a hazard ratio of 0.74 with a 95% confidence interval of 0.59-0.94 vs. patients treated by other-AEDs and a hazard ratio of 0.66 with a 95% confidence interval of 0.52-0.84 vs. patients treated by administration of non-AEDs. No heterogeneity was observed in the subset analysis.
The results suggest that glioblastoma patients may experience prolonged survival due to VPA administration. Sub-analysis confirmed the benefit of VPA use compared to a non-AEDs group and an other-AEDs group. Further RCTs of this subject should be performed 23).
The surface regularity obtained from high-resolution contrast-enhanced pretreatment volumetric T1-weighted MR images is a predictor of survival in patients with glioblastoma. It may help in classifying patients for surgery 24).