Impact of concurrent chemotherapy with radiation therapy for elderly patients with newly diagnosed glioblastoma: a review of the National Cancer Data Base

Competing Risk Model to Determine the Prognostic Factors for Patients with Gliosarcoma

BACKGROUND

Gliosarcoma (GSM) is a highly aggressive variant of brain cancer with an extremely unfavorable prognosis. Prognosis is not feasible by traditional methods because of a lack of staging criteria, and the present study aims to screen more detailed demographic factors to predict the prognostic factors of the tumors.

METHODS

For this study, we extracted data of patients diagnosed with GSM from the SEER (Surveillance Epidemiology and End Results) database between 2000 and 2019. To account for the influence of competing risks, we used a Cumulative Incidence Function. Subsequently, univariate analysis was conducted to evaluate the individual variables under investigation. Specifically for patients with GSM, we generated cumulative risk curves for specific mortality outcomes and events related to competing risks. In addition, we used both univariate and multivariate Cox analysis to account for non-GSM-related deaths that may confound our research.

RESULTS

The competing risk model showed that age, marital status, tumor size, and adjuvant therapy were prognostic factors in GSM-related death. The analysis results showed that older age (60-70 years, ≥71 years) and larger tumor size (≥5.3 cm) significantly increased the risk of GSM-related death. Conversely, surgical intervention, chemotherapy, and being single were identified as protective factors against GSM-related death.

CONCLUSIONS

Our study using a competing risk model provided valuable insights into the prognostic factors associated with GSM-related death. Further research and clinical interventions targeted at minimizing these risk factors and promoting the use of protective measures may contribute to improved outcomes and reduced mortality for patients with GSM.

Prognostic nomogram models for predicting survival probability in elderly glioblastoma patients

PURPOSE

To investigate the prognostic factors of survival and develop a predictive nomogram model for elderly GBM patients.

METHODS

Elderly patients (> = 65 years) with histologically diagnosed GBM were extracted from the SEER database. Survival analysis of overall survival (OS) was performed by Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were used to determine independent prognostic factors and these factors were used to further construct the nomogram model.

RESULTS

A total of 9068 elderly GBM patients (5122 males and 3946 females) were included, with a median age of 72 years (65-96 years). All patients were divided randomly into the training group (n = 6044) and the validation group (n = 3024) by a ratio of 2:1. Cox regression analyses on OS showed eight independent prognostic factors (race, age, tumor side, tumor size, metastasis, surgery, radiotherapy, and chemotherapy) in the training cohort. Also, seven variables (except for race) were identified on CSS in the training group. By comprising these variables, the nomogram models on OS and CSS for predicting the 6-month, 1-year, and 2-year survival probability were constructed and exhibited moderate consistency, respectively. Then, they could be validated well in the validation cohort and by C-index, time-dependent ROC curve, calibration plot, and DCA curve.

CONCLUSIONS

Nomogram models on OS and CSS could provide an applicable tool to predict the survival probability and provide clinical references regarding treatment strategies and prognosis.

Therapeutic efficacy of 166Holmium siloxane in microbrachytherapy of induced glioblastoma in minipig tumor model

Glioblastoma is considered the most common malignant primary tumor of central nervous system. In spite of the current standard and multimodal treatment, the prognosis of glioblastoma is poor. For this reason, new therapeutic approaches need to be developed to improve the survival time of the glioblastoma patient. In this study, we performed a preclinical experiment to evaluate therapeutic efficacy of 166Ho microparticle suspension administered by microbrachytherapy on a minipig glioblastoma model. Twelve minipigs were divided in 3 groups. Minipigs had injections into the tumor, containing microparticle suspensions of either 166Ho (group 1; n = 6) or 165Ho (group 2; n = 3) and control group (group 3; n = 3). The survival time from treatment to euthanasia was 66 days with a good state of health of all minipigs in group 1. The median survival time from treatment to tumor related death were 8.6 and 7.3 days in groups 2 and control, respectively. Statistically, the prolonged life of group 1 was significantly different from the two other groups (p < 0.01), and no significant difference was observed between group 2 and control (p=0.09). Our trial on the therapeutic effect of the 166Ho microparticle demonstrated an excellent efficacy in tumor control. The histological and immunohistochemical analysis showed that the efficacy was related to a severe 166Ho induced necrosis combined with an immune response due to the presence of the radioactive microparticles inside the tumors. The absence of reflux following the injections confirms the safety of the injection device.

The Value of H2BC12 for Predicting Poor Survival Outcomes in Patients With WHO Grade II and III Gliomas

Purpose: Glioma is a common primary malignant brain tumor. Grade II (GII) gliomas are prone to develop into anaplastic grade III (GIII) gliomas, which indicate a higher malignancy and poorer survival outcome. This study aimed to satisfy the increasing demand for novel sensitive biomarkers and potential therapeutic targets in the treatment of GII and GIII gliomas.

Methods: A TCGA dataset was used to investigate the expression of H2BC12 mRNA in GII and GIII gliomas and its relation to clinical pathologic characteristics. Glioma tissues were collected to verify results from the TCGA dataset, and H2BC12 mRNA was detected by RT-qPCR. ROC analysis was employed to evaluate the classification power for GII and GIII. The significance of H2BC12 mRNA GII and GIII gliomas was also investigated. In addition, H2BC12 expression-related pathways were enriched by gene set enrichment analysis (GSEA). DNA methylation level and mutation of H2BC12 were analyzed by the UALCAN and CBioPortal databases, respectively.

Results: Based on the sample data from multiple databases and RT-qPCR, higher expression of H2BC12 mRNA was found in GII and GIII glioma tissue compared to normal tissue, which was consistent with a trend with our clinical specimen. H2BC12 mRNA had a better power in distinguishing between GII and GIII and yielded an AUC of 0.706 with a sensitivity of 76.9% and specificity of 81.8%. Meanwhile, high H2BC12 levels were associated with IDH status, 1p/19q codeletion, primary therapy outcome, and the histological type of gliomas. Moreover, the overall survival (OS), disease-specific survival (DSS), and progress-free interval (PFI) of GII glioma patients with higher levels of H2BC12 were shorter than those of patients with lower levels as well as GIII patients. In the multivariate analysis, a high H2BC12 level was an independent predictor for poor survival outcomes of gliomas. The Wnt or PI3K-AKT signaling pathways, DNA repair, cellular senescence, and DNA double-strand break repair were differentially activated in phenotypes that were positively associated with H2BC12. H2BC12 DNA methylation was high in TP53 nonmutant patients, and no H2BC12 mutation was observed in gliomas patients.

Conclusion: H2BC12 is a promising biomarker for the diagnosis and prognosis of patients with WHO grade II and III gliomas.

Utility of Administrative Databases and Big Data on Understanding Glioma Treatment—A Systematic Review

Background Gliomas are a heterogeneous group of tumors where large multicenter clinical and genetic studies have become increasingly popular in their understanding. We reviewed and analyzed the findings from large databases in gliomas, seeking to understand clinically relevant information.

Methods A systematic review was performed for gliomas studied using large administrative databases up to January 2020 (e.g., National Inpatient Sample [NIS], National Surgical Quality Improvement Program [NSQIP], and Surveillance, Epidemiology, and End Results Program [SEER], National Cancer Database [NCDB], and others).

Results Out of 390 screened studies, 122 were analyzed. Studies included a wide range of gliomas including low- and high-grade gliomas. The SEER database (n = 83) was the most used database followed by NCDB (n = 28). The most common pathologies included glioblastoma multiforme (GBM) (n = 67), with the next category including mixes of grades II to IV glioma (n = 31). Common study themes involved evaluation of descriptive epidemiological trends, prognostic factors, comparison of different pathologies, and evaluation of outcome trends over time. Persistent health care disparities in patient outcomes were frequently seen depending on race, marital status, insurance status, hospital volume, and location, which did not change over time. Most studies showed improvement in survival because of advances in surgical and adjuvant treatments.

Conclusions This study helps summarize the use of clinical administrative databases in gliomas research, informing on socioeconomic issues, surgical outcomes, and adjuvant treatments over time on a national level. Large databases allow for some study questions that would not be possible with single institution data; however, limitations remain in data curation, analysis, and reporting methods.

Mir-139-5p inhibits glioma cell proliferation and progression by targeting GABRA1

Glioma is an extremely aggressive malignant neoplasm of the central nervous system. MicroRNA (miRNA) are known to bind to specific target mRNA to regulate post-transcriptional gene expression and are, therefore, currently regarded as promising biomarkers for glioma diagnosis and prognosis. The aim of the present study was to examine the pathogenesis and potential molecular markers of glioma by comparing the differential expression of miRNA and mRNA between glioma tissue and peritumor brain tissue. We explored the impact of screened core miRNA and mRNA on cell proliferation, invasion, and migration of glioma. An miRNA expression profile dataset (GSE90603) and a transcriptome profile dataset (GSE90598) were downloaded from combined miRNA-mRNA microarray chips in the Gene Expression Omnibus (GEO) database. Overall, 59 differentially expressed miRNAs (DEMs) and 419 differentially expressed genes (DEGs) were identified using the R limma software package. FunRich software was used to predict DEM target genes and miRNA-gene pairs, and Perl software was used to find overlapping genes between DEGs and DEM target genes. There were 129 overlapping genes regulated by nine miRNAs between target genes of the DEMs and DEGs. The Chinese Glioma Genome Atlas(CGGA) was analyzed in order to identify miRNAs with diagnostic and prognostic significance. MiR-139-5p, miR-137, and miR-338-3p were validated to be significantly linked to prognosis in glioma patients. Finally, we validated that miR-139-5p affected glioma malignant biological behavior via targeting gamma-aminobutyric acid A receptor alpha 1(GABRA1) through rescue experiments. Low miR-139-5p expression was correlated with survival probability and World Health Organization (WHO) grade. MiR-139-5p overexpression inhibited cell proliferation, migration, and invasion of glioma in vitro. GABRA1 was identified as a functional downstream target of miR-139-5p. Decreased GABRA1 expression was related to similar biological roles as miR-139-5p overexpression while upregulation of GABRA1 effectively reversed the inhibition effects of miR-139-5p. These results demonstrate a novel axis for miR-139-5p/GABRA1 in glioma progression and provide potential prognostic predictors and therapeutic target for glioma patients.

Competing risk model to determine the prognostic factors and treatment strategies for elderly patients with glioblastoma

The prognostic factors and optimal treatment for the elderly patient with glioblastoma (GBM) were poorly understood. This study extracted 4975 elderly patients (≥ 65 years old) with histologically confirmed GBM from Surveillance, Epidemiology and End Results (SEER) database. Firstly, Cumulative incidence function and cox proportional model were utilized to illustrate the interference of non-GBM related mortality in our cohort. Then, the Fine-Gray competing risk model was applied to determine the prognostic factors for GBM related mortality. Age ≥ 75 years old, white race, size > 5.4 cm, frontal lobe tumor, and overlapping lesion were independently associated with more GBM related death, while Gross total resection (GTR) (HR 0.87, 95%CI 0.80-0.94, P = 0.010), radiotherapy (HR 0.64, 95%CI 0.55-0.74, P < 0.001), chemotherapy (HR 0.72, 95%CI 0.59-0.90, P = 0.003), and chemoRT (HR 0.43, 95%CI 0.38-0.48, P < 0.001) were identified as independently protective factors of GBM related death. Based on this, a corresponding nomogram was conducted to predict 3-, 6- and 12-month GBM related mortality, the C-index of which were 0.763, 0.718, and 0.694 respectively. The calibration curve showed that there was a good consistency between the predicted and the actual mortality probability. Concerning treatment options, GTR followed by chemoRT is suggested as optimal treatment. Radiotherapy and chemotherapy alone also provide moderate clinical benefits.

An Immune-Related Signature for Predicting the Prognosis of Lower-Grade Gliomas

Background

Lower-grade gliomas (LGGs) have more favorable outcomes than glioblastomas; however, LGGs often progress to process glioblastomas within a few years. Numerous studies have proven that the tumor microenvironment (TME) is correlated with the prognosis of glioma.

Methods

LGG RNA-Sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were extracted and then divided into training and testing cohorts, respectively. Immune-related differentially expressed genes (DEGs) were screened to establish a prognostic signature by a multivariate Cox proportional hazards regression model. The immune-related risk score and clinical information, such as age, sex, World Health Organization (WHO) grade, and isocitrate dehydrogenase 1 (IDH1) mutation, were used to independently validate and develop a prognostic nomogram. GO and KEGG pathway analyses to DEGs between immune-related high-risk and low-risk groups were performed.

Results

Sixteen immune-related genes were screened for establishing a prognostic signature. The risk score had a negative correlation with prognosis, with an area under the receiver operating characteristic (ROC) curve of 0.941. The risk score, age, grade, and IDH1 mutation were identified as independent prognostic factors in patients with LGGs. The hazard ratios (HRs) of the high-risk score were 5.247 [95% confidence interval (CI) = 3.060–8.996] in the multivariate analysis. A prognostic nomogram of 1-, 3-, and 5-year survival was established and validated internally and externally. Go and KEGG pathway analyses implied that immune-related biological function and pathways were involved in the TME.

Conclusion

The immune-related prognostic signature and the prognostic nomogram could accurately predict survival.

Treatment and surgical factors associated with longer-term glioblastoma survival: a National Cancer Database study

Background

Insufficient data exist to characterize factors associated with longer-term survival of glioblastoma (GBM). A population-based analysis of GBM longer-term survivors (LTS) in the United States was conducted to investigate the association between treatment, demographic, surgical factors, and longer-term survival.

Methods

From the National Cancer Database, GBM patients were identified using ICD-O-3 histology codes 9440-9442/3, 2005-2015 and were divided into routine (≤3 years) and longer-term (>3 years) overall survival (OS) groups. Univariable and multivariable logistic regression analysis was used to assess factors associated with longer-term survival. A subset analysis was performed to further investigate the association of extent of resection and treatment combinations on OS outcomes.

Results

A total of 93 036 patients with GBM met study criteria. Among these patients, 8484 were LTS and 84 552 were routine survivors (RS). When comparing LTS (OS of >3 years) with RS (OS of ≤3 years), younger age, insured status, metro/urban residence, treatment at academic facility, and fewer comorbidities were associated with longer-term survival. In addition, trimodality therapy (chemotherapy + radiation + surgery) was associated with having best odds of longer-term survival (odds ratio = 4.89, 95% confidence interval [3.58, 6.68]); 74% of LTS received such therapy compared with 51% of RS. Subset analysis revealed that total resection is only associated with longer-term survival status for those receiving trimodality therapy or surgery only.

Conclusions

In a population-based analysis, standard of care surgery and chemo radiation connote a survival advantage in GBM. Among those receiving standard of care, having a total resection is most beneficial for longer-term survival status.

Hypofractioned radiotherapy versus conventional radiotherapy for the treatment of multiform glioblastoma in adults over 70 years old

Aim:

Multiform glioblastoma (MG) represents 70% of all gliomas, with half of patients older than 65 years with median survival of 12–18 months, hypofractionation seeks to reduce the intensity and duration of treatment without impacting on survival rates. The objective was to determine the global survival and recurrence-free survival of adults over 70 years old with MG treated with hypofractionated radiotherapy and standard scheme. The review of patients older than 70 years treated with radiotherapy from 2013 to 2016 was performed.

Results:

Twenty-four patients were analysed, with a median follow-up of 239 days, and there is no difference in overall survival 12·3 versus 10·5 months (p = 0·55) and recurrence-free survival 8·3 versus 3·4 months (p = 0·48) between both schemes, conventional versus hypofractioanted, respectively.

Conclusion:

The results in this study show that hypofractionated scheme could be comparable in overall survival and recurrence-free survival to conventional fractionation, but a longer patients’ trial should be done.

The Misclassification of Diffuse Gliomas: Rates and Outcomes

PURPOSE

The integrated histopathologic and molecular diagnoses of the 2016 WHO classification of central nervous system tumors have revolutionized patient care by improving diagnostic accuracy and reproducibility; however, the frequency and consequences of misclassification of histologically diagnosed diffuse gliomas are unknown.

EXPERIMENTAL DESIGN

Patients with newly diagnosed ICD-O-3 (International Classification of Diseases) histologically encoded diffuse gliomas from 2010-2015 were identified from the National Cancer Database, the misclassification rates and overall survival (OS) of which were assessed by WHO grade and 1p/19q status. In addition, misclassification rates by isocitrate dehydrogenase (IDH), ATRX, and p53 statuses were examined in an analogous multi-institutional cohort of registry-encoded diffuse gliomas.

RESULTS

Of 74,718 patients with diffuse glioma, only 74.4% and 78.8% of molecularly characterized WHO grade II and III oligodendrogliomas were in fact 1p/19q-codeleted. In addition, 28.9% and 36.8% of histologically encoded grade II and III "oligoastrocytomas", and 6.3% and 8.8% of grade II and III astrocytomas had 1p/19q-codeletion, thus molecularly representing oligodendrogliomas if also IDH mutant. OS significantly depended on accurate WHO grading and 1p/19q status.

CONCLUSIONS

On the basis of 1p/19q, IDH, ATRX, and p53, the misclassification rates of histologically encoded oligodendrogliomas, astrocytomas, and glioblastomas are approximately 21%-35%, 6%-9%, and 9%, respectively; with significant clinical implications. Our findings suggest that when compared with historical histology-only classified data, in national registry, as well as, institutional databases, there is the potential for false-positive results in contemporary trials of molecularly classified diffuse gliomas, which could contribute to a seemingly positive phase II trial (based on historical comparison) failing at the phase III stage. Critically, findings from diffuse glioma clinical trials and historical cohorts using prior histology-only WHO schemes must be cautiously reinterpreted.

A Prognostic Signature for Lower Grade Gliomas Based on Expression of Long Non-Coding RNAs

Diffuse low-grade and intermediate-grade gliomas (together known as lower grade gliomas, WHO grade II and III) develop in the supporting glial cells of brain and are the most common types of primary brain tumor. Despite a better prognosis for lower grade gliomas, 70% of patients undergo high-grade transformation within 10 years, stressing the importance of better prognosis. Long non-coding RNAs (lncRNAs) are gaining attention as potential biomarkers for cancer diagnosis and prognosis. We have developed a computational model, UVA8, for prognosis of lower grade gliomas by combining lncRNA expression, Cox regression, and L1-LASSO penalization. The model was trained on a subset of patients in TCGA. Patients in TCGA, as well as a completely independent validation set (CGGA) could be dichotomized based on their risk score, a linear combination of the level of each prognostic lncRNA weighted by its multivariable Cox regression coefficient. UVA8 is an independent predictor of survival and outperforms standard epidemiological approaches and previous published lncRNA-based predictors as a survival model. Guilt-by-association studies of the lncRNAs in UVA8, all of which predict good outcome, suggest they have a role in suppressing interferon-stimulated response and epithelial to mesenchymal transition. The expression levels of eight lncRNAs can be combined to produce a prognostic tool applicable to diverse populations of glioma patients. The 8 lncRNA (UVA8) based score can identify grade II and grade III glioma patients with poor outcome, and thus identify patients who should receive more aggressive therapy at the outset.

National cancer database analysis of outcomes in pediatric glioblastoma

Glioblastoma in children is an aggressive disease with no defined standard therapy. We evaluated hospital‐based demographic and survival patterns obtained through the National Cancer Database to better characterize children with glioblastoma. Our study identified 1173 patients from 0 to 19 years of age between 1998 and 2011. Comparisons were made among demographics, clinical characteristics, treatment, and survival variables. Fifty‐four percent of patients were over 10 years of age. Approximately 80% of patients underwent either partial or complete resection. Adjuvant therapy was used variably, and its use increased with patient age. Forty‐eight percent of patients received the combination of surgery, radiation, and chemotherapy, and 4% did not receive any treatment. As expected, patients ≤5 years of age had better 5‐year survival than those ages 6–10 (P = 0.01) or 11–19 years (P = 0.0077). Other factors associated with poor survival included black race and central tumor location. Better outcomes were associated with treatment that included surgery, radiotherapy, and chemotherapy compared to any other treatment combinations. Radiotherapy had no impact on survival in the 0 to 10‐year‐old age group, but was associated with improved survival for patients 11–19 years. We report an extensive demographic and survival analysis of pediatric glioblastoma. The observed differences likely reflect variances in tumor biology and likelihood of treatment receipt. Improved survival was associated with the use of surgery, radiotherapy, and chemotherapy. Radiation therapy was not associated with survival in patients younger than 10 years of age.

Radiotherapy plus temozolomide in elderly patients with glioblastoma: a "real-life" report

Background

The optimization of the management for elderly glioblastoma patients is crucial given the demographics of aging in many countries. We report the outcomes for a “real-life” patient cohort (i.e. unselected) comprising consecutive glioblastoma patients aged 70 years or more, treated with different radiotherapy +/− temozolomide regimens.

Methods

From 2003 to 2016, 104 patients ≥ 70 years of age, consecutively treated by radiotherapy for glioblastoma, were included in this study. All patients were diagnosed with IDH-wild type glioblastoma according to pathological criteria.

Results

Our patient cohort comprised 51 female patients (49%) and 53 male. The median cohort age was 75 years (70–88), and the median Karnofsky performance status (KPS) was 70 (30–100). Five (5%) patients underwent macroscopic complete resection, 9 (9%) had partial resection, and 90 (86%), a stereotactic biopsy. The MGMT promoter was methylated in 33/73 cases (45%). Fifty-two (50%), 38 (36%), and 14 (14%) patients were categorized with RPA scores of III, IV, and I-II. Thirty-three (32%) patients received normofractionated radiotherapy (60 Gy, 30 sessions) with temozolomide (Stupp), 37 (35%) received hypofractionated radiotherapy (median dose 40 Gy, 15 sessions) with temozolomide (HFRT + TMZ), and 34 (33%) HFRT alone. Patients receiving only HFRT were significantly older, with lower KPSs. The median overall survival (OS; all patients) was 5.2 months. OS rates at 12, 18, and 24 months, were 19%, 12%, and 5%, respectively, with no statistical differences between patients receiving Stupp or HFRT + TMZ (P = 0.22). In contrast, patients receiving HFRT alone manifested a significantly shorter survival time (3.9 months vs. 5.9 months, P = 0.018). In multivariate analyses, the prognostic factors for OS were: i) the type of surgery (HR: 0.47 [0.26–0.86], P = 0.014), ii) RPA class (HR: 2.15 [1.17–3.95], P = 0.014), and iii) temozolomide use irrespective of radiotherapy schedule (HR: 0.54 [0.33–0.88], P < 0.02). MGMT promoter methylation was neither a prognostic nor a predictive factor.

Conclusions

These outcomes agree with the literature in terms of optimal surgery and the use of HFRT as a standard treatment for elderly GBM patients. Our study emphasizes the potential benefit of using temozolomide with radiotherapy in a real-life cohort of elderly GBM patients, irrespective of their MGMT status.

Geographic Variations in the Incidence of Glioblastoma and Prognostic Factors Predictive of Overall Survival in US Adults from 2004-2013

Objective: The purpose of this study was to evaluate variations in the regional incidence of glioblastoma in US adults in 2004-2013. Study Design and Setting: We evaluated 24,262 patients with primary glioblastoma. Data were categorized based on geographic regions that included different SEER registry sites as follows: (1) Northeast: Connecticut, New Jersey (3,977 patients); (2) South: Kentucky, Louisiana, Metropolitan Atlanta, Rural Georgia, Greater Georgia (excluding AT and RG) (5,212 patients); (3) North Central: Metropolitan Detroit, Iowa (2,320 patients); (4) West: Hawaii, New Mexico, Seattle (Puget Sound), Utah, San Francisco-Oakland SMSA, San Jose-Monterey, Los Angeles, Greater California (excluding SF, LA, and SJ), Alaska (12,753 patients). Results: Statistically significant differences in the rates of overall patient survival (P < 0.001) and the incidence of glioblastoma (24.31, 22.6, 20.35, 15.03 per 100,000/year in the South, Northeast, West, North Central regions, respectively) were identified between geographic regions. Multivariate Cox regression analysis demonstrated that overall survival was better in patients of Asian or Pacific Islander race. In addition, age, registry site, marital status, tumor laterality, histological classification, the extent of disease, tumor size, tumor extension, and treatment methods were identified as significant prognostic factors. Conclusion: Glioblastoma incidence is geographic region and race/ethnicity-dependent.