Background: The European Organisation for Research and Treatment of Cancer (EORTC) Group has developed a new multidimensional instrument measuring cancer-related fatigue to be used in conjunction with the quality of life core questionnaire (EORTC QLQ-C30). The module EORTC QLQ-FA13 assesses physical, cognitive, and emotional aspects of cancer-related fatigue. Methods: The methodology follows the EORTC guidelines for phase IV validation of modules. This paper focuses on the results of the psychometric validation of the factorial structure of the module. For validation and cross-validation confirmatory factor analysis (maximum likelihood estimation), intraclass correlation and Cronbach alpha for internal consistency were employed. The study involved an international multicenter collaboration of 11 European and non-European countries. Results: A total of 946 patients with various tumor diagnoses were enrolled. Based on the confirmatory factor analysis, we could approve the three-dimensional structure of the module. Removing one item and reassigning the factorial mapping of another item resulted in the EORTC QLQ-FA12. For the revised scale, we found evidence supporting good local (indicator reliability ≥ 0.60, factor reliability ≥ 0.82) and global model fit (GFI _t1|t2 = 0.965/0.957, CFI _t1|t2 = 0.976/0.972, RMSEA _t1|t2 = 0.060/0.069) for both measurement points. For each scale, test-retest reliability proved to be very good (intraclass correlation: R_t1-t2 = 0.905–0.921) and internal consistency proved to be good to high (Cronbach alpha = .79–.90). Conclusion: Based on the former phase III module, the multidimensional structure was revised as a phase IV module (EORTC FA12) with an improved scale structure. For a comprehensive validation of the EORTC FA12, further aspects of convergent and divergent validity as well as sensitivity to change should be determined.

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.

To update the digital online atlas for organs at risk (OARs) delineation in neuro-oncology based on high-quality computed tomography (CT) and magnetic resonance (MR) imaging with new OARs. In this planned update of the neurological contouring atlas published in 2018, ten new clinically relevant OARs were included, after thorough discussion between experienced neuro-radiation oncologists (RTOs) representing 30 European radiotherapy-oncology institutes. Inclusion was based on daily practice and research requirements. Consensus was reached for the delineation after critical review. Contouring was performed on registered CT with intravenous (IV) contrast (soft tissue & bone window setting) and 3 Tesla (T) MRI (T1 with gadolinium & T2 FLAIR) images of one patient (1 mm slices). For illustration purposes, delineation on a 7T MRI without IV contrast from a healthy volunteer was added. OARs were delineated by three experienced RTOs and a neuroradiologist based on the relevant literature. The presented update of the neurological contouring atlas was reviewed and approved by 28 experts in the field. The atlas is available online and includes in total 25 OARs relevant to neuro-oncology, contoured on CT and MRI T1 and FLAIR (3T & 7T). Three-dimensional (3D) rendered films are also available online. In order to further decrease inter- and intra-observer OAR delineation variability in the field of neuro-oncology, we propose the use of this contouring atlas in photon and particle therapy, in clinical practice and in the research setting. The updated atlas is freely available on www.cancerdata.org.

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.