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Purpose: VEGF is upregulated in glioblastoma and may contribute to immunosuppression. We performed a phase II study of pembrolizumab alone or with bevacizumab in recurrent glioblastoma., Patients and Methods: Eighty bevacizumab-naïve patients with recurrent glioblastoma were randomized to pembrolizumab with bevacizumab (cohort A, n = 50) or pembrolizumab monotherapy (cohort B, n = 30). The primary endpoint was 6-month progression-free survival (PFS-6). Assessed biomarkers included evaluation of tumor programmed death-ligand 1 expression, tumor-infiltrating lymphocyte density, immune activation gene expression signature, and plasma cytokines. The neurologic assessment in neuro-oncology (NANO) scale was used to prospectively assess neurologic function., Results: Pembrolizumab alone or with bevacizumab was well tolerated but of limited benefit. For cohort A, PFS-6 was 26.0% [95% confidence interval (CI), 16.3-41.5], median overall survival (OS) was 8.8 months (95% CI, 7.7-14.2), objective response rate (ORR) was 20%, and median duration of response was 48 weeks. For cohort B, PFS-6 was 6.7% (95% CI, 1.7-25.4), median OS was 10.3 months (95% CI, 8.5-12.5), and ORR was 0%. Tumor immune markers were not associated with OS, but worsened OS correlated with baseline dexamethasone use and increased posttherapy plasma VEGF (cohort A) and mutant IDH1 , unmethylated MGMT , and increased baseline PlGF and sVEGFR1 levels (cohort B). The NANO scale contributed to overall outcome assessment., Conclusions: Pembrolizumab was ineffective as monotherapy and with bevacizumab for recurrent glioblastoma. The infrequent radiographic responses to combinatorial therapy were durable. Tumor immune biomarkers did not predict outcome. Baseline dexamethasone use and tumor MGMT warrant further study as potential biomarkers in glioblastoma immunotherapy trials., (©2020 American Association for Cancer Research.)

Background: Although survival statistics in patients with glioblastoma multiforme (GBM) are well-defined at the group level, predicting individual patient survival remains challenging because of significant variation within strata., Objective: To compare statistical and machine learning algorithms in their ability to predict survival in GBM patients and deploy the best performing model as an online survival calculator., Methods: Patients undergoing an operation for a histopathologically confirmed GBM were extracted from the Surveillance Epidemiology and End Results (SEER) database (2005-2015) and split into a training and hold-out test set in an 80/20 ratio. Fifteen statistical and machine learning algorithms were trained based on 13 demographic, socioeconomic, clinical, and radiographic features to predict overall survival, 1-yr survival status, and compute personalized survival curves., Results: In total, 20 821 patients met our inclusion criteria. The accelerated failure time model demonstrated superior performance in terms of discrimination (concordance index = 0.70), calibration, interpretability, predictive applicability, and computational efficiency compared to Cox proportional hazards regression and other machine learning algorithms. This model was deployed through a free, publicly available software interface (https://cnoc-bwh.shinyapps.io/gbmsurvivalpredictor/)., Conclusion: The development and deployment of survival prediction tools require a multimodal assessment rather than a single metric comparison. This study provides a framework for the development of prediction tools in cancer patients, as well as an online survival calculator for patients with GBM. Future efforts should improve the interpretability, predictive applicability, and computational efficiency of existing machine learning algorithms, increase the granularity of population-based registries, and externally validate the proposed prediction tool., (Copyright © 2019 by the Congress of Neurological Surgeons.)

We aimed to determine whether intake of pesticide residues from fruits and vegetables was associated with glioma. Within 3 prospective cohorts from 1998–2016—the Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), and Health Professionals Follow-up Study—we computed multivariable-adjusted hazard ratios (MVHRs) and 95% confidence intervals (CI) for glioma by quintiles of intake of low- and high-pesticide-residue fruits and vegetables using Cox proportional hazards regression. Fruits and vegetables were categorized as high or low residue using a validated method based on pesticide surveillance data. We confirmed 275 glioma cases across 2,745,862 person-years. A significant association was observed between intake of high-residue fruits and vegetables and glioma in NHS (MVHR = 2.99, 95% CI: 1.38, 6.44 comparing highest with lowest quintile, P for trend = 0.02). This was not identified in NHSII (MVHR = 0.52, 95% CI: 0.19, 1.45, P for trend = 0.20) or Health Professionals Follow-up Study (MVHR = 1.01, 95% CI: 0.42, 2.45, P for trend = 0.39). No significant associations were observed by intake of low-residue fruits and vegetables; overall intake was not significantly associated with glioma in any cohort. We found no evidence for an inverse relationship of fruit and vegetable intake with glioma. Although limited in power, this study suggests a possible association between fruit-and-vegetable pesticide residue intake and risk of glioma that merits further study. [ABSTRACT FROM AUTHOR]

Background Glioblastoma (GB) is the most common and most lethal primary malignant brain tumor. Extent of surgical resection is one of the most important prognostic factors associated with improved survival. Historically, patients living in nonmetropolitan counties in the United States have limited access to optimal treatment and health care services. The aim of this study is to determine whether there is an association between urbanicity and surgical treatment patterns among US patients with primary GB. Methods Cases with histologically confirmed, primary GB diagnosed between 2005 and 2015 were obtained from the Central Brain Tumor Registry of the United States (CBTRUS) in collaboration with the Centers for Disease Control and Prevention, and the National Cancer Institute. Multivariable logistic regression models were constructed to assess the association between urbanicity and receipt of surgical treatment (gross total resection [GTR]/subtotal resection [STR] vs biopsy only/none) and extent of resection (GTR vs STR), adjusted for age at diagnosis, sex, race, US regional division, and primary tumor site. Results Patients residing in nonmetropolitan counties were 7% less likely to receive surgical treatment (odds ratio [OR] = 0.93, 95% CI: 0.89-0.96, P <.0001). Among those who received surgical treatment, metropolitan status was not significantly associated with receiving GTR vs STR (OR = 0.99, 95% CI: 0.94-1.04, P =.620). Conclusions Among US patients with GB, urbanicity is associated with receipt of surgical treatment, but among patients who receive surgery, urbanicity is not associated with extent of resection. These results point to potential differences in access to health care for those in nonmetropolitan areas that warrant further exploration. [ABSTRACT FROM AUTHOR]

Tea and coffee have antioxidant and neuroprotective effects. Observational studies suggest that tea and coffee intake may reduce cancer risk, but data on glioma risk are inconclusive. We evaluated the association between tea, coffee and caffeine intake and glioma risk in the female Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII) and the male Health Professionals Follow‐Up Study (HPFS). Cumulative intake was derived from validated quadrennial food frequency questionnaires. Glioma cases were confirmed by medical record review. Multivariable‐adjusted hazard ratios of glioma by beverage intake category were estimated using Cox proportional hazards models. We documented 554 incident cases of glioma (256 in NHS, 87 in NHSII and 211 in HPFS). Compared to <1 cup/week, higher tea consumption was borderline inversely associated with glioma risk in pooled cohorts (hazard ratio [HR] = 0.73, 95% confidence interval [CI]: 0.49–1.10 for >2 cups/day, p‐trend = 0.05), but not in women (HR = 0.74, 95% CI: 0.47–1.18 for >2 cups/day, p‐trend = 0.11) or men (HR = 0.70, 95% CI: 0.30–1.60 for >2 cups/day, p‐trend = 0.30) separately. Overall, we observed no significant associations between caffeinated, decaffeinated or total coffee intake and glioma risk. There were no material differences in the results with baseline values, 8‐year lagged responses, or when limited to glioblastoma (n = 362). In three large prospective cohort studies, tea intake was borderline inversely associated with glioma risk. No significant associations were observed for coffee intake and glioma risk. These results merit further exploration in prospective studies. What's new? Few lifestyle factors have been associated with glioma risk. Nonetheless, intake of coffee and tea, owing to potential neuroprotective and antioxidant effects, are of particular interest as lifestyle factors that defend against glioma. Here, the authors analyzed data from food frequency questionnaires and medical records from three large prospective cohort studies in the United States to assess the relationship between tea and coffee intake and glioma risk. Analyses show that tea intake has a marginal inverse association with glioma risk. Meanwhile, caffeinated or decaffeinated coffee intake and total coffee consumption had no impact on risk. [ABSTRACT FROM AUTHOR]

Background: Multiple studies have reported higher rates of glioma in areas with higher socioeconomic status (SES) but to the authors' knowledge have not stratified by other factors, including race/ethnicity or urban versus rural location.Methods: The authors identified the average annual age-adjusted incidence rates and calculated hazard ratios for death for gliomas of various subtypes, stratified by a county-level index for SES, race/ethnicity, US region, and rural versus urban status.Results: Rates of glioma were highest in counties with higher SES (rate ratio, 1.18; 95% CI, 1.15-1.22 comparing the highest with the lowest quintiles [P < .001]). Stratified by race/ethnicity, higher rates in high SES counties persisted for white non-Hispanic individuals. Stratified by rural versus urban status, differences in incidence by SES were more pronounced among urban counties. Survival was higher for residents of high SES counties after adjustment for age and extent of surgical resection (hazard ratio, 0.82; 95% CI, 0.76-0.87 comparing the highest with the lowest quintile of SES [P < .001]). Survival was higher among white Hispanic, black, and Asian/Pacific Islander individuals compared with white non-Hispanic individuals, after adjustment for age, SES, and extent of surgical resection, and when restricted to those individuals with glioblastoma who received radiation and chemotherapy.Conclusions: The incidence of glioma was higher in US counties of high compared with low SES. These differences were most pronounced among white non-Hispanic individuals and white Hispanic individuals residing in urban areas. Better survival was observed in high SES counties, even when adjusting for extent of surgical resection, and when restricted to those who received radiation and chemotherapy for glioblastoma. Differences in incidence and survival were associated with SES and race, rather than rural versus urban status. [ABSTRACT FROM AUTHOR]

Purpose: Recent studies have suggested height as a risk factor for glioma, but less is known regarding body mass index (BMI) or other anthropomorphic measures. We evaluated the association between body habitus and risk of glioma.Methods: We evaluated the association of measures of height, BMI, waist circumference, and somatotypes with risk of glioma in two prospective cohorts, the Nurses' Health Study and the Health Professionals Follow-Up Study.Results: We documented 508 incident cases of glioma (321 glioblastoma [GBM]). In both cohorts, we found no significant association between adult BMI or waist circumference and risk of glioma, with pooled HR for BMI of 1.08 (95% CI 0.85-1.38 comparing ≥ 30 to < 25 kg/m2) and for waist circumference of 1.05 (95% CI 0.80-1.37 highest vs. lowest quintile). Higher young adult BMI (at age 18 in NHS and 21 in HPFS) was associated with modestly increased risk of glioma in the pooled cohorts (pooled HR 1.35, 95% CI 1.06-1.72 comparing ≥ 25 kg/m2 vs. less; HR 1.34 for women and 1.37 for men). Analysis of body somatotypes suggested reduced risk of glioma among women with heavier body types at all ages this measure was assessed (HRs ranging from 0.52 to 0.65 comparing highest tertile to lowest tertile), but no significant association among men. Height was associated with increased risk of glioma among women (HR 1.09, 95% CI 1.04-1.14 per inch), but not significantly among men. Within the 8 years prior to diagnosis, cases had no material weight loss compared to non-cases. All results were similar when limited to GBM.Conclusion: Adult BMI and waist circumference were not associated with glioma. Higher BMI at age 21 for men and at age 18 for women was modestly associated with risk in the pooled cohort. Based on body somatotypes, however, women with heavier body types during childhood and young adulthood may be at lower risk of glioma, although this association was not observed later in life with measurements of BMI. Greater height was associated with increased risk, and the trend was more pronounced in women. [ABSTRACT FROM AUTHOR]