CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2012–2016

Ostrom, Quinn T.; Cioffi, Gino; Gittleman, Haley; Patil, Nirav; Waite, Kristin; Kruchko, Carol; Barnholtz‐Sloan, Jill S.

doi:10.1093/neuonc/noz150

Cited by 1,853 publications

(1,487 citation statements)

References 84 publications

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“…Demographic patterns were similar to adult GBM with males and whites representing the majority of cases [1,3,[18][19][20]. Blacks were associated with poorer survival outcomes compared to whites, which has also been found in population-based studies for adults with primary brain tumors and in many other cancers [21].…”

Section: Discussionmentioning

confidence: 75%

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National cancer database analysis of outcomes in pediatric glioblastoma

et al. 2018

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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.

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Section: Discussionmentioning

confidence: 75%

“…Brain and central nervous system tumors are one of the leading causes of cancer death in children [1][2][3]. Pediatric glioblastoma (pGBM) is an aggressive high-grade glioma associated with well-established genetic subtypes with varying incidence, location, and outcomes based on general age categories [4].…”

Section: Introductionmentioning

confidence: 99%

National cancer database analysis of outcomes in pediatric glioblastoma

et al. 2018

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“…Glioblastoma (GBM) is the most common primary malignant brain tumor, with an annual incidence of 11,000 cases in the U.S. and a median survival of 14-18 months despite aggressive therapies [1][2][3][4][5] . Currently, standard of care includes maximal safe surgical resection followed by concomitant radiation and chemotherapy with temozolomide 1 .…”

Section: Introductionmentioning

confidence: 99%

Metronomic capecitabine as an immune modulator in glioblastoma patients reduces myeloid-derived suppressor cells

Peereboom

Alban

Grabowski

et al. 2019

Preprint

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Background: Myeloid-derived suppressor cells (MDSCs) are elevated in glioblastoma (GBM) patient circulation, present in tumor tissue, and associated with poor prognosis. While low-dose chemotherapy reduces MDSCs in preclinical models, the use of this strategy to reduce MDSCs in GBM patients has yet to be evaluated. Methods:A phase 0/1 dose-escalation clinical trial was conducted in recurrent glioblastoma patients treated 5-7 days prior to surgery with low-dose chemotherapy via capecitabine followed by concomitant low-dose capecitabine and bevacizumab. Clinical outcomes, including progression-free and overall survival, were measured, along with safety and toxicity profiles. Over the treatment time course, circulating MDSC levels were measured by multi-parameter flow cytometry, and tumor tissue immune profiles were assessed via mass cytometry time-of-flight.Results: A total of 11 patients were enrolled across escalating dose cohorts of 150, 300, and 450 mg bid, with a progression-free survival of 5.8 months (range of 1.8-27.8 months) and an overall survival of 11.5 months (range of 3->28.0 months) from trial enrollment. No serious adverse events related to the drug combination were observed. Compared to pre-treatment baseline, circulating MDSCs were found to be higher after surgery in the 150 mg treatment arm and lower in the 300 mg and 450 mg treatment arms. Increased cytotoxic immune infiltration was observed after low-dose capecitabine compared to untreated GBM patients in the 300 mg and 450 mg treatment arms. Conclusions:Low-dose, metronomic capecitabine in combination with bevacizumab is well tolerated in GBM patients and was associated with a reduction in circulating MDSC levels and an increase in cytotoxic immune infiltration into the tumor microenvironment.

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“…Pediatric brain cancer has unfortunately surpassed leukemia to become the most common cause of death from cancer in children in the US (2). It is estimated that 2,940 new cases of childhood (0-14 age group) and adolescent (15)(16)(17)(18)(19) age group) primary malignant and non-malignant central nervous system (CNS) tumors will be diagnosed in the United States (US) in 2020 (3).…”

Section: Introductionmentioning

confidence: 99%

Diffusion Basis Spectrum Imaging with Deep Neural Network Differentiates Distinct Histology in Pediatric Brain Tumors

Ye¹,

Srinivasa²,

Lin³

et al. 2020

Preprint

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High-grade pediatric brain tumors constitute the highest mortality of cancer-death in children.While conventional MRI has been widely adopted for examining pediatric high-grade brain tumor clinically, accurate neuroimaging detection and differentiation of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in the clinical management of pediatric brain tumor. We employed a novel Diffusion Histology Imaging (DHI) approach that incorporates diffusion basis spectrum imaging (DBSI) and deep neural network. DHI aims to detect, differentiate, and quantify heterogenous areas in pediatric highgrade brain tumors, which include normal white matter (WM), densely cellular tumor (DC tumor), less densely cellular tumor (LDC tumor), infiltrating edge, necrosis, and hemorrhage. Distinct diffusion metric combination would thus indicate the unique distributions of each distinct tumor histology features. DHI, by incorporating DBSI metrics and the deep neural network algorithm, classified pediatric tumor histology with an overall accuracy of 83.3%. Receiver operating analysis (ROC) analysis suggested DHI's great capability in distinguishing individual tumor histology with AUC values (95%CI) of 0.983 (0.985-0.989), 0.961 (0.957-0.964), 0.993 (0.992-0.994), 0.953 (0.947-0.958), 0.974 (0.970-0.978) and 0.980 (0.977-0.983) for normal WM, DC tumor, LDCtumor, infiltrating edge, necrosis and hemorrhage, respectively. Our results suggest that DBSI-DNN, or DHI, accurately characterized and classified multiple tumor histologic features in pediatric high-grade brain tumors. If further validated in patients, the novel DHI might emerge as a favorable alternative to the current neuroimaging techniques to better guide biopsy and resection as well as monitor therapeutic response in patients with high-grade brain tumors.

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CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2012–2016

Cited by 1,853 publications

References 84 publications

National cancer database analysis of outcomes in pediatric glioblastoma

National cancer database analysis of outcomes in pediatric glioblastoma

Metronomic capecitabine as an immune modulator in glioblastoma patients reduces myeloid-derived suppressor cells

Diffusion Basis Spectrum Imaging with Deep Neural Network Differentiates Distinct Histology in Pediatric Brain Tumors

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