Epidemiology of adult meningioma: Report from the Dutch Brain Tumour Registry (2000-2019).

BACKGROUND AND PURPOSE: Meningiomas are the most common primary tumours of the central nervous system. This study aimed to provide comprehensive nationwide estimates on the incidence, prevalence and prognostic impact of meningioma diagnosis in the Netherlands. METHODS: Adult patients diagnosed with meningioma in 2000-2019 were selected from the Dutch Brain Tumour Registry (DBTR), part of the Netherlands Cancer Registry (NCR). Time trends in age-adjusted incidence and prevalence rates were evaluated using the estimated annual percentage change (EAPC). Relative survival rates were calculated using the Pohar Perme estimator. Case completeness of the DBTR/NCR was estimated through record linkage with one of the Dutch neuro-oncology centres. RESULTS: From a total of 23,454 cases of meningioma, 11,306 (48.2%) were histologically confirmed and 12,148 (51.8%) were radiological diagnoses. Over time, the incidence of diagnosis increased from 46.9 per 1,000,000 inhabitants (European Standardized Rate [ESR]) to 107.3 (EAPC 4.7%, p < 0.01), with an increase in the incidence of radiological diagnoses from 14.0 to 70.2 per 1,000,000 ESR (EAPC 9.1%, p < 0.01). The prevalence of meningioma was estimated at 1012/1,000,000 on 1 January 2020, with almost 17,800 individuals having had a diagnosis of meningioma. Relative survival rate at 10 years for grade 1 meningiomas was 91.0% (95% confidence interval [CI] 89.4%-92.3%), 71.3% (95% CI 66.8%-75.2%) for grade 2 meningiomas and 36.4% (95% CI 27.3%-45.6%) for grade 3 meningiomas. Local case completeness was estimated at 97.6% for histologically confirmed meningiomas and 84.5% for radiological diagnoses. CONCLUSION: With a near-complete registry, meningioma prevalence was estimated at over 1000 per 1,000,000 inhabitants.

Prognostic and Predictive Value of Integrated Qualitative and Quantitative Magnetic Resonance Imaging Analysis in Glioblastoma.

Glioblastoma (GBM) is the most malignant primary brain tumor for which no curative treatment options exist. Non-invasive qualitative (Visually Accessible Rembrandt Images (VASARI)) and quantitative (radiomics) imaging features to predict prognosis and clinically relevant markers for GBM patients are needed to guide clinicians. A retrospective analysis of GBM patients in two neuro-oncology centers was conducted. The multimodal Cox-regression model to predict overall survival (OS) was developed using clinical features with VASARI and radiomics features in isocitrate dehydrogenase (IDH)-wild type GBM. Predictive models for IDH-mutation, 06-methylguanine-DNA-methyltransferase (MGMT)-methylation and epidermal growth factor receptor (EGFR) amplification using imaging features were developed using machine learning. The performance of the prognostic model improved upon addition of clinical, VASARI and radiomics features, for which the combined model performed best. This could be reproduced after external validation (C-index 0.711 95% CI 0.64-0.78) and used to stratify Kaplan-Meijer curves in two survival groups (p-value < 0.001). The predictive models performed significantly in the external validation for EGFR amplification (area-under-the-curve (AUC) 0.707, 95% CI 0.582-8.25) and MGMT-methylation (AUC 0.667, 95% CI 0.522-0.82) but not for IDH-mutation (AUC 0.695, 95% CI 0.436-0.927). The integrated clinical and imaging prognostic model was shown to be robust and of potential clinical relevance. The prediction of molecular markers showed promising results in the training set but could not be validated after external validation in a clinically relevant manner. Overall, these results show the potential of combining clinical features with imaging features for prognostic and predictive models in GBM, but further optimization and larger prospective studies are warranted.

Chloroquine combined with concurrent radiotherapy and temozolomide for newly diagnosed glioblastoma: a phase IB trial.

Treatment of glioblastoma xenografts with chloroquine results in macroautophagy/autophagy inhibition, resulting in a reduction of tumor hypoxia and sensitization to radiation. Preclinical data show that EGFRvIII-expressing glioblastoma may benefit most from chloroquine because of autophagy dependency. This study is the first to explore the safety, pharmacokinetics and maximum tolerated dose of chloroquine in combination with radiotherapy and concurrent daily temozolomide in patients with a newly diagnosed glioblastoma. This study is a single-center, open-label, dose-finding phase I trial. Patients received oral chloroquine daily starting one week before the course of chemoradiation (temozolomide 75 mg/m2/d) until the end of radiotherapy (59.4 Gy/33 fractions). Thirteen patients were included in the study (n = 6: 200 mg, n = 3: 300 mg, n = 4: 400 mg chloroquine). A total of 44 adverse events, possibly related to chloroquine, were registered including electrocardiogram QTc prolongation, irreversible blurred vision and nausea/vomiting resulting in cessation of temozolomide or delay of adjuvant cycles. The maximum tolerated dose was 200 mg chloroquine. Median overall survival was 16 months (range 2-32). Median survival was 11.5 months for EGFRvIII- patients and 20 months for EGFRvIII+ patients. A daily dose of 200 mg chloroquine was determined to be the maximum tolerated dose when combined with radiotherapy and concurrent temozolomide for newly diagnosed glioblastoma. Favorable toxicity and promising overall survival support further clinical studies.Abbreviations: AE: adverse events; CQ: chloroquine; DLT: dose-limiting toxicities; EGFR: epidermal growth factor receptor; GBM: glioblastoma; HCQ: hydroxychloroquine; IDH1/2: isocitrate dehydrogenase (NADP(+)) 1/2; MTD: maximum tolerated dose; CTC: National Cancer Institute Common Toxicity Criteria; MGMT: O-6-methylguanine-DNA methyltransferase; OS: overall survival; po qd: per os quaque die; SAE: serious adverse events; TMZ: temozolomide; WHO: World Health Organization.

Noninvasive Glioblastoma Testing: Multimodal Approach to Monitoring and Predicting Treatment Response.

Glioblastoma is the most aggressive adult primary brain tumor which is incurable despite intensive multimodal treatment. Inter- and intratumoral heterogeneity poses one of the biggest barriers in the diagnosis and treatment of glioblastoma, causing differences in treatment response and outcome. Noninvasive prognostic and predictive tests are highly needed to complement the current armamentarium. Noninvasive testing of glioblastoma uses multiple techniques that can capture the heterogeneity of glioblastoma. This set of diagnostic approaches comprises advanced MRI techniques, nuclear imaging, liquid biopsy, and new integrated approaches including radiogenomics and radiomics. New treatment options such as agents targeted at driver oncogenes and immunotherapy are currently being developed, but benefit for glioblastoma patients still has to be demonstrated. Understanding and unraveling tumor heterogeneity and microenvironment can help to create a treatment regime that is patient-tailored to these specific tumor characteristics. Improved noninvasive tests are crucial to this success. This review discusses multiple diagnostic approaches and their effect on predicting and monitoring treatment response in glioblastoma.