Background Outcome of low-grade glioma (LGG, WHO grade II) is highly variable reflecting molecular heterogeneity of the disease. We compared two different single modality treatment strategies: standard radiotherapy (RT) versus primary temozolomide (TMZ) chemotherapy with the aim of tailoring treatment and identifying predictive molecular factors. Methods 477 patients (2005 – 2012, median FU 48 months) with a low-grade glioma (astrocytoma, oligoastrocytoma, oligodendroglioma, WHO grade II) with at least one high-risk feature (age > 40 years, progressive disease, tumor > 5 cm or crossing the midline, neurological symptoms (e.g. focal or mental deficits, increased intracranial pressure or intractable seizures)) were, after stratification by chromosome 1p-status, randomized to either conformal RT (50.4 Gy/28 fractions) or dose-dense TMZ (75 mg/m2 daily × 21 days, q28 days, max. 12 cycles). Random treatment allocation was performed online using a minimization technique. A planned analysis was performed after 246 progression events. All analyses are intent to treat. Primary clinical endpoint was progression-free survival (PFS), correlative analyses included molecular markers (1p/19q co-deletion, MGMT methylation status, IDH1+2 mutations). The trial has been registered at the European Trials Registry (EudraCT 2004-002714-11) and at ClinicalTrials.gov (NCT00182819). Findings Four hundred seventy-seven patients were randomized. Severe hematological toxicity occurred in 14% of TMZ-treated patients, infections in 3% of TMZ-treated patients, and 1% of RT-treated patients. Moderate to severe fatigue was recorded in 3% of patients in the RT group and 7% in the TMZ group. At a median follow-up of 48 months (IQR:31–56), median PFS was 39 months (IQR:16–46) in the TMZ arm and 46 months (IQR:19–48) in the RT group (hazard ratio 1.16, 95% CI, 0.9–1.5; p=0.22). Median OS has not been reached. Exploratory analyses identified treatment-dependent variation in outcome of molecular LGG subgroups (n=318). Interpretation There was no significant difference in outcome of the overall patient population treated with either radiotherapy alone or TMZ chemotherapy alone. Further data maturation is needed for overall survival analyses and evaluation of the full predictive impact of the molecular subtypes for individualized treatment choices. Funding Merck & Co, Swiss-Bridge Award 2011, Swiss Cancer League.

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Summary Background The role of temozolomide chemotherapy in newly diagnosed 1p/19q non-co-deleted anaplastic gliomas, which are associated with lower sensitivity to chemotherapy and worse prognosis than 1p/19q co-deleted tumours, is unclear. We assessed the use of radiotherapy with concurrent and adjuvant temozolomide in adults with non-co-deleted anaplastic gliomas. Methods This was a phase 3, randomised, open-label study with a 2 × 2 factorial design. Eligible patients were aged 18 years or older and had newly diagnosed non-co-deleted anaplastic glioma with WHO performance status scores of 0–2. The randomisation schedule was generated with the electronic EORTC web-based ORTA system. Patients were assigned in equal numbers (1:1:1:1), using the minimisation technique, to receive radiotherapy (59·4 Gy in 33 fractions of 1·8 Gy) alone or with adjuvant temozolomide (12 4-week cycles of 150–200 mg/m2 temozolomide given on days 1–5); or to receive radiotherapy with concurrent temozolomide 75 mg/m2 per day, with or without adjuvant temozolomide. The primary endpoint was overall survival adjusted for performance status score, age, 1p loss of heterozygosity, presence of oligodendroglial elements, and MGMT promoter methylation status, analysed by intention to treat. We did a planned interim analysis after 219 (41%) deaths had occurred to test the null hypothesis of no efficacy (threshold for rejection p<0·0084). This trial is registered with ClinicalTrials.gov, number NCT00626990. Findings At the time of the interim analysis, 745 (99%) of the planned 748 patients had been enrolled. The hazard ratio for overall survival with use of adjuvant temozolomide was 0·65 (99·145% CI 0·45–0·93). Overall survival at 5 years was 55·9% (95% CI 47·2–63·8) with and 44·1% (36·3–51·6) without adjuvant temozolomide. Grade 3–4 adverse events were seen in 8–12% of 549 patients assigned temozolomide, and were mainly haematological and reversible. Interpretation Adjuvant temozolomide chemotherapy was associated with a significant survival benefit in patients with newly diagnosed non-co-deleted anaplastic glioma. Further analysis of the role of concurrent temozolomide treatment and molecular factors is needed. Funding Schering Plough and MSD.

Radiomics relies on the extraction of a wide variety of quantitative image-based features to provide decision support. Magnetic resonance imaging (MRI) contributes to the personalization of patient care but suffers from being highly dependent on acquisition and reconstruction parameters. Today, there are no guidelines regarding the optimal pre-processing of MR images in the context of radiomics, which is crucial for the generalization of published image-based signatures. This study aims to assess the impact of three different intensity normalization methods (Nyul, WhiteStripe, Z-Score) typically used in MRI together with two methods for intensity discretization (fixed bin size and fixed bin number). The impact of these methods was evaluated on first-and second-order radiomics features extracted from brain MRI, establishing a unified methodology for future radiomics studies. Two independent MRI datasets were used. The first one (DATASET1) included 20 institutional patients with WHO grade II and III gliomas who underwent post-contrast 3D axial T1-weighted (T1w-gd) and axial T2-weighted fluid attenuation inversion recovery (T2w-flair) sequences on two different MR devices (1.5 T and 3.0 T) with a 1-month delay. Jensen-Shannon divergence was used to compare pairs of intensity histograms before and after normalization. The stability of first-order and secondorder features across the two acquisitions was analysed using the concordance correlation coefficient and the intra-class correlation coefficient. The second dataset (DATASET2) was extracted from the public TCIA database and included 108 patients with WHO grade II and III gliomas and 135 patients with WHO grade IV glioblastomas. The impact of normalization and discretization methods was evaluated based on a tumour grade classification task (balanced accuracy measurement) using five well-established machine learning algorithms. Intensity normalization highly improved the robustness of first-order features and the performances of subsequent classification models. For the T1w-gd sequence, the mean balanced accuracy for tumour grade classification was increased from 0.67 (95% CI 0.61-0.73) to 0.82 (95% CI 0.79-0.84, P = .006), 0.79 (95% CI 0.76-0.82, P = .021) and 0.82 (95% CI 0.80-0.85, P = .005), respectively, using the Nyul, WhiteStripe and Z-Score normalization methods compared to no normalization. The relative discretization makes unnecessary the use of intensity normalization for the second-order radiomics features. Even if the bin number for the discretization had a small impact on classification performances, a good compromise was obtained