Background Elderly patients with glioblastoma are perceived to face a poor prognosis with perceptions surrounding older age and a relative lack of randomized data contributing. This study evaluated survival prognosticators in elderly glioblastoma patients to more accurately guide their treatment. Materials and methods The records of 169 elderly (≥70 years) patients with a new diagnosis of glioblastoma who had undergone neurosurgical intervention were retrospectively examined for patient sex, age, performance status, comorbidities, MGMT promoter methylation, surgical intervention and chemoradiation regime. The adjusted survival impact of these factors was determined using Cox proportional hazards model and used to devise a two-stage scoring system to estimate patient survival at the stage of surgical (Elderly Glioblastoma Surgical Score, EGSS) and oncological management (Elderly Glioblastoma Oncological Score, EGOS). Results The median overall survival (mOS) of the cohort was 28.8 weeks. Gross-total and subtotal resection were associated with improved survival compared to biopsy alone (respective mOS 65.3 and 28.1 vs 15.7 weeks, p<0.001). Hypofractionated radiotherapy (40Gy in 15 fractions) with Temozolomide was non-inferior to the Stupp protocol, p=0.72. Exploratory subgroup analysis revealed a significant benefit of Temozolomide-based approaches in MGMT-methylated patients as well as a trend towards improved survival in MGMT-unmethylated patients. Our EGSS and EGOS scores successfully estimated survival in this retrospective cohort with 65% and 73% accuracy. Conclusions Where appropriate and safe, elderly glioblastoma patients may benefit from surgical resection and combined chemoradiotherapy with Temozolomide. The proposed EGSS and EGOS scores take into account important prognostic factors to help guide which patients should receive such treatment.

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The dorsal anterior cingulate cortex (dACC) is a key node in the human salience network. It has been ascribed motor, pain-processing and affective functions. However, the dynamics of information flow in this complex region and how it responds to inputs remain unclear and are difficult to study using non-invasive electrophysiology. The area is targeted by neurosurgery to treat neuropathic pain. During deep brain stimulation surgery, we recorded local field potentials from this region in humans during a decision-making task requiring motor output. We investigated the spatial and temporal distribution of information flow within the dACC. We demonstrate the existence of a distributed network within the anterior cingulate cortex where discrete nodes demonstrate directed communication following inputs. We show that this network anticipates and responds to the valence of feedback to actions. We further show that these network dynamics adapt following learning. Our results provide evidence for the integration of learning and the response to feedback in a key cognitive region.