RTID-06. THE PIVOTAL METIS (EF-25) STUDY OF TUMOR TREATING FIELDS (TTFIELDS) THERAPY FOR BRAIN METASTASES FROM NON-SMALL CELL LUNG CANCER (NSCLC) FOLLOWING RADIOSURGERY
Bibliographic record
Abstract
Abstract INTRODUCTION: TTFields are electric fields that disrupt processes necessary for cancer cell survival and can stimulate an antitumor immune response in preclinical NSCLC models. TTFields therapy is a noninvasive and locoregional treatment approved for glioblastoma, which has recently demonstrated a survival benefit when applied to the thorax with standard of care (SOC) systemic therapy in patients with metastatic NSCLC that progressed on/after platinum. Here we describe the pivotal METIS study (EF-25, NCT02831959) evaluating the efficacy and safety of TTFields therapy applied to brain metastases from NSCLC. TRIAL DESIGN: Patients (270) with 1–10 brain metastases from NSCLC will receive stereotactic radiosurgery (SRS), followed by 1:1 randomization to TTFields (NovoTTF-200M [150 kHz] applied to the head ≥ 18 h/day) with best SOC, or best SOC alone. Key inclusion criteria are life expectancy ≥ 3 months, a new diagnosis of 1 inoperable or 2–10 supra and/or infratentorial brain metastases from NSCLC, that are amenable to SRS. Patients who had prior whole brain radiotherapy, or have single operable, leptomeningeal, or recurrent brain metastases, certain genetic mutations, or severe comorbidities or contraindications, are not eligible. The primary endpoint is time to first intracranial progression. Secondary endpoints include time to neurocognitive failure, overall survival, radiological response rate, time to second intracranial progression, time to first/second intracranial progression by modified RECIST v1.1, rate of intracranial progression, time to distant progression, rate of cognitive decline, quality of life, neurocognitive failure-free survival, and safety. The study is powered at 80% (2-sided alpha of 0.05) to detect a hazard ratio of 0.57. In July 2021, an independent Data Monitoring Committee reviewed the study data and recommended continuation. The study includes 128 sites in Europe, Israel, mainland China, North America, and Hong Kong. The final patient was enrolled in March 2023.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".