Tumor-induced mortality in adult primary supratentorial glioblastoma multiforme with different age subgroups

Area-level socioeconomic status is positively correlated with glioblastoma incidence and prognosis in the United States

In the United States, an individual’s access to resources, insurance status, and wealth are critical social determinants that affect both the risk and outcomes of many diseases. One disease for which the correlation with socioeconomic status (SES) is less well-characterized is glioblastoma (GBM), a devastating brain malignancy. The aim of this study was to review the current literature characterizing the relationship between area-level SES and both GBM incidence and prognosis in the United States. A query of multiple databases was performed to identify the existing data on SES and GBM incidence or prognosis. Papers were filtered by relevant terms and topics. A narrative review was then constructed to summarize the current body of knowledge on this topic. We obtained a total of three papers that analyze SES and GBM incidence, which all report a positive correlation between area-level SES and GBM incidence. In addition, we found 14 papers that focus on SES and GBM prognosis, either overall survival or GBM-specific survival. Those studies that analyze data from greater than 1,530 patients report a positive correlation between area-level SES and individual prognosis, while those with smaller study populations report no significant relationship. Our report underlines the strong association between SES and GBM incidence and highlights the need for large study populations to assess SES and GBM prognosis to ideally guide interventions that improve outcomes. Further studies are needed to determine underlying socio-economic stresses on GBM risk and outcomes to identify opportunities for intervention.

Unraveling the peripheral and local role of inflammatory cytokines in glioblastoma survival

Glioblastoma (GBM) is a life-threatening disease that presents high morbidity and mortality. The standardized treatment protocol results in a global survival of less than three years in the majority of cases. Immunotherapies have gained wide recognition in cancer treatment; however, GBM has an immunosuppressive microenvironment diminishing the possible effectiveness of this therapy. In this sense, investigating the inflammatory settings and the tumoral nature of GBM patients are an important goal to create an individual plan of treatment to improve overall survival rate and quality of life of these patients. Thirty-two patients who underwent surgical resection of GBM were included in this study. Tumor samples and 10 mL of peripheral blood were collected and immediately frozen. TNF-a, IL-1a and IL-4 were evaluated in the tumor and TNF-a, IL-1a and TGF-b in the plasma by Luminex assay. Immunohistochemistry analysis to determine immune celular profile was done, including immunohistochemistry for CD20, CD68 and CD3. Three cases were excluded. Tumor topography, tumor nature, and tumor volume reconstructions were accurately analyzed by T1-weighted, T2-weighted, and FLAIR magnetic resonance imaging. We found that GBM patients with below median peripheral levels of TNF-a and IL-1a had a decreased survival rate when compared to above median patients. On the other hand, patients with below median peripheral levels of TGF-b increased overall survival rate. Intratumoral IL-1a above median was associated with higher number of macrophages and fewer with B cells. Furthermore, plasmatic TNF-a levels were correlated with intratumoral TNF-a levels, suggesting that peripheral cytokines are related to the tumoral microenvironment. Even though tumor size has no difference regarding survival rate, we found a negative correlation between intratumoral IL-4 and tumor size, where larger tumors have less IL-4 expression. Nevertheless, the tumoral nature had a significant effect in overall survival rate, considering that infiltrative tumors showed decreased survival rate and intratumoral TNF-a. Moreover, expansive tumors revealed fewer macrophages and higher T cells. In multiple variation analyzes, we demonstrated that infiltrative tumors and below median peripheral IL-1a expression represent 3 times and 5 times hazard ratio, respectively, demonstrating a poor prognosis. Here we found that peripheral cytokines had a critical role as prognostic tools in a small cohort of GBM patients.

Optimizing Postoperative Adjuvant Therapy in Elderly Patients with Newly Diagnosed Glioblastoma: Single-Institution Audit of Clinical Outcomes from a Tertiary-Care Comprehensive Cancer Center in India

BACKGROUND

There is lack of consensus regarding optimal adjuvant therapy in elderly glioblastoma (GBM). We have been treating elderly (≥60 years) GBM patients with normofractionated or hypofractionated radiotherapy (RT) plus temozolomide (TMZ) based on Karnofsky performance status (KPS). Herein we report clinical outcomes in this cohort treated at our institute using this approach.

METHODS

Medical records of elderly GBM patients (≥60 years) treated between 2013 and 2017 with either normofractionated RT (59.4-60 Gy/30-33 fractions/6-6.5 weeks) or hypofractionated RT (35 Gy/10 fractions/2 weeks) plus TMZ were reviewed retrospectively. Outcomes of interest included progression-free survival (PFS), overall survival (OS), and ≥grade 3 myelotoxicity. Time-to-event outcomes were analyzed with Kaplan-Meier methods, compared using log-rank test, and reported as point estimates with 95% confidence interval (CI).

RESULTS

The normofractionated cohort (n = 126) was characterized by a higher proportion of patients younger than age 65 years, KPS ≥70, methylated O⁶-methylguanine DNA methyltransferase (MGMT), and receiving adjuvant TMZ including extended adjuvant TMZ (>6 cycles) compared with the hypofractionated cohort (n = 20), confirming selection bias. At a median follow-up of 13 months, 1-year Kaplan-Meier estimates of PFS and OS were 43% (95% CI: 36%-52%) and 56% (95% CI: 48%-64%), yielding median PFS and OS of 11.0 months and 13.1 months, respectively. Higher KPS, methylated MGMT, normofractionated RT, and extended adjuvant TMZ emerged as favorable prognostic factors. TMZ was well tolerated with a low risk of ≥grade 3 myelotoxicity.

CONCLUSIONS

Our single-institution clinical audit confirms poor survival in elderly GBM with suboptimal performance status but demonstrates acceptably fair outcomes in patients with preserved KPS comparable with the nonelderly cohort.

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.

Optimizing management of the elderly patient with glioblastoma: Survival prediction online tool based on BC Cancer Registry real-world data

BACKGROUND

Glioblastoma (GBM) is associated with fatal outcomes and devastating neurological presentations especially impacting the elderly. Management remains controversial and representation in clinical trials poor. We generated 2 nomograms and a clinical decision making web tool using real-world data.

METHODS

Patients ≥60 years of age with histologically confirmed GBM (ICD-O-3 histology codes 9440/3, 9441/3, and 9442/3) diagnosed 2005-2015 were identified from the BC Cancer Registry (n = 822). Seven hundred and twenty-nine patients for which performance status was captured were included in the analysis. Age, performance and resection status, administration of radiation therapy (RT), and chemotherapy were reviewed. Nomograms predicting 6- and 12-month overall survival (OS) probability were developed using Cox proportional hazards regression internally validated by c-index. A web tool powered by JavaScript was developed to calculate the survival probability.

RESULTS

Median OS was 6.6 months (95% confidence interval [CI] 6-7.2 months). Management involved concurrent chemoradiation (34%), RT alone (42%), and chemo alone (2.3%). Twenty-one percent of patients did not receive treatment beyond surgical intervention. Age, performance status, extent of resection, chemotherapy, and RT administration were all significant independent predictors of OS. Patients <80 years old who received RT had a significant survival advantage, regardless of extent of resection (hazard ratio range from 0.22 to 0.60, CI 0.15-0.95). A nomogram was constructed from all 729 patients (Harrell's Concordance Index = 0.78 [CI 0.71-0.84]) with a second nomogram based on subgroup analysis of the 452 patients who underwent RT (Harrell's Concordance Index = 0.81 [CI 0.70-0.90]). An online calculator based on both nomograms was generated for clinical use.

CONCLUSIONS

Two nomograms and accompanying web tool incorporating commonly captured clinical features were generated based on real-world data to optimize decision making in the clinic.

GLIMPSE: a glioblastoma prognostication model using ensemble learning-a surveillance, epidemiology, and end results study

Purpose

Glioblastoma is one of the most common and aggressive brain tumors in the world with a poor prognosis. A glioblastoma prognostication model has the potential to improve the cancer's standard of care. No other paper has looked at using ensemble learning with a population database to predict multiple binary glioblastoma survival outcomes.

Methods

We utilized ensemble learning to design, build, and test a prognostication system for glioblastoma for short-, intermediate- and long-term survival, based on various clinical features. We used the population database SEER which covers 17 different registries. The most important prognostic features were identified and used as a clinical feature set. The statistical feature set was determined using Random Forests. The accuracy, sensitivity, specificity, area under the receiver operating characteristic (AUROC), positive predictive value (PPV), and negative predictive value (NPV) were reported.

Results

Statistically-determined feature sets had the best performance. All the top models for short, intermediate, and long-term survival were random forests. With regards to short-term survival, top model had metrics AUROC = 0.937, accuracy = 86%, specificity = 88%, sensitivity = 85%, NPV = 85%, and PPV = 87%. For long-term survival, the top model had AUROC = 0.893, accuracy = 81%, specificity = 79%, sensitivity = 83%, NPV = 82%, and PPV = 79%. The top intermediate-term survival prediction had AUROC ≥ 0.780 and the other metrics were at least 70%.

Conclusions

Our ensemble models were high-performing and achieved AUROCs as high as 0.94, highlighting the importance of balancing, using ensemble techniques and statistical feature selection. Our models can potentially be used by clinicians after external validation.

Gene Therapy, A Novel Therapeutic Tool for Neurological Disorders: Current Progress, Challenges and Future Prospective

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Neurological disorders are one of the major threat for health care system as they put enormous socioeconomic burden. All aged populations are susceptible to one or other neurological problems with symptoms of neuroinflammation, neurodegeneration and cognitive dysfunction. At present, available pharmacotherapeutics are insufficient to treat these diseased conditions and in most cases, they provide only palliative effect. It was also found that the molecular etiology of neurological disorders is directly linked with the alteration in genetic makeup, which can be inherited or triggered by the injury, environmental toxins and by some existing disease. Therefore, to take care of this situation, gene therapy has emerged as an advanced modality that claims to permanently cure the disease by deletion, silencing or edition of faulty genes and by insertion of healthier genes. In this modality, vectors (viral and non-viral) are used to deliver targeted gene into a specific region of the brain via various routes. At present, gene therapy has shown positive outcomes in complex neurological disorders, such as Parkinson's disease, Alzheimer's disease, Huntington disease, Multiple sclerosis, Amyotrophic lateral sclerosis and in lysosomal storage disease. However, there are some limitations such as immunogenic reactions non-specificity of viral vectors and a lack of effective biomarkers to understand the efficacy of therapy. Considerable progress has been made to improve vector design, gene selection and targeted delivery. This review article deals with the current status of gene therapy in neurological disorders along with its clinical relevance, challenges and future prospective.

Optimal adjuvant therapy in elderly glioblastoma: results from a systematic review and network meta-analysis

BACKGROUND

There exists lack of consensus worldwide regarding the most optimal adjuvant therapy regimen in elderly patients with newly-diagnosed glioblastoma (GBM).

PURPOSE

To identify the most optimal adjuvant therapy regimen in elderly GBM patients through systematic review and network meta-analysis.

METHODS

Prospective trials randomly assigning elderly GBM patients post-operatively to any adjuvant therapy regimen were included. The primary outcome measure was overall survival. Numbers of events, patients at-risk, and censored patients for survival were estimated from Kaplan-Meier survival curves in the interval of 0-12 months. The total person-time at risk and the mortality × 100 person-months was also estimated. The relative ranking probability of each treatment and rankograms were used to estimate the hierarchy of each intervention in terms of overall survival. The mean rank values and the surface under the cumulative ranking (SUCRA) curves were also calculated.

RESULTS

A systematic literature search identified 1278 abstracts, that were screened to retrieve full-text manuscripts of potentially eligible articles. After detailed assessment, data from 1569 patients in 7 randomized controlled trials (RCTs) treated with one of following regimens was extracted and analyzed: normofractionated radiotherapy (RT) delivered over 5.5-6 weeks; moderately hypofractionated RT (2-3 weeks) either alone or in combination with temozolomide or bevacizumab; extremely hypofractionated RT (1-week); temozolomide monotherapy; and best supportive care alone. In terms of overall survival, moderately hypofractionated RT (3-weeks) with concurrent and adjuvant temozolomide emerged as the best and second-best adjuvant therapy option with 81% probability and 99.1% probability respectively. Using SUCRA, the surface area for moderately hypofractionated RT (3-weeks) with concurrent and adjuvant temozolomide reached almost 100%, confirming it as the best intervention. As expected, best supportive care alone was ranked as the worst treatment strategy.

CONCLUSION

Moderately hypofractionated RT (3-weeks) with concurrent and adjuvant temozolomide is the most optimal and preferred adjuvant therapeutic regimen in elderly GBM.