Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Glioblastoma (GBM) is known to use both local and systemic immunosuppressive strategies. One such strategy is the expression of the immune checkpoint protein programmed cell death ligand-1 (PD-L1) by both tumor cells and tumor-associated immune cells. Recent phase III trials using IgG4 antibodies targeting PD-1, the ligand for PD-L1, failed to show any benefit. Avelumab is an IgG1 monoclonal antibody targeting PD-L1. In contrast to the previously tested immune checkpoint inhibitors, it can directly bind tumor cells and immune cells expressing PD-L1 and can induce antibody-dependent cellular cytotoxicity. METHODS: We conducted a single center, open label, phase II study where avelumab 10 mg/kg IV Q2W was added concurrently to the first monthly temozolomide cycle in patients with newly diagnosed GBM. Immunohistochemical analyses were performed on surgery samples. The primary objective was safety. Secondary objectives were efficacy outcomes according to the immunotherapy Response Assessment in Neuro Oncology criteria, progression free survival (PFS), and overall survival (OS). Exploratory objectives aimed at determining prognostic biomarkers. RESULTS: Thirty patients were started on therapy and two were lost to follow-up. Median follow-up time (reverse Kaplan-Meier) was 41.7 months (IQR: 28.3-43.4). Three (10.0%) patients had a related or possibly related treatment emergent adverse event that lead to transient or permanent discontinuation of avelumab. Eight (26.7%) patients had one or more immune-related adverse events, and 8 (26.7%) patients had an infusion-related reaction. The overall response rate was 23.3%, median PFS was 9.7 months, and the median OS was 15.3 months. No pretreatment biomarkers showed any predictive value. CONCLUSIONS: The addition of avelumab to standard therapy in patients with GBM was not associated with any new safety signal. There was no apparent improvement in OS. TRIAL REGISTRATION: NCT03047473 Registered February 9, 2017.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it