CTNI-10. RANDOMIZED PIVOTAL STUDY OF BLOOD-BRAIN BARRIER (BBB) DISRUPTION USING EXABLATE MODEL 4000 WITH STANDARD OF CARE (SOC) THERAPY IN NON-SMALL CELL LUNG CANCER (NSCLC) BRAIN METASTASES: LIMITLESS TRIAL
Bibliographic record
Abstract
Abstract BACKGROUND NSCLC is the most common cause of brain metastases. The Exablate focused ultrasound with circulating microbubble resonators uses the concept of real-time imaging to treat small target spots focusing energy through the skull in noninvasive manner, thereby disrupting the BBB. There is preclinical evidence of synergy of FUS-mediated BBB with immunotherapy beyond improved drug delivery due to BBB disruption (BBBD). METHODS LIMITLESS is a prospective, multi-center, randomized, two-arm, controlled, pivotal clinical trial to evaluate the safety and efficacy of additional targeted BBB disruption using Exablate Model 4000 for the treatment of NSCLC brain metastases in subjects who are undergoing planned pembrolizumab monotherapy compared to Pembrolizumab alone in 2:1 randomization. The inclusion criteria include age ≥ 18 years, KPS ≥ 70, NSCLC (EGFR and ALK negative) with up to 3 brain metastases, one of which meets the RANO-BM criteria for measurable Disease (1 cm x 1 cm) with normal organ function. The primary endpoint is to test superiority of Exablate BBBD targeted to their brain metastases over the standard of care without Exablate BBBD as determined by Objective Response Rate (ORR) based on RANO- BM by 6 months. The secondary endpoints include best objective response rate and time to response for brain metastases by treatment arm. Other end points include progression-free survival (PFS), overall survival (OS), Intracranial and extracranial PFS, quality of life assessments. The Bayesian design statistical analysis will assume superior ORR of 60% in Exablate group compared to 30% in SOC group for a total sample size of 96 subjects (64 subjects in Exablate and 32 in SOC) for 80% power using a two-sided Pearson's Chi-Square test with alpha = 0.05. For the upper-bound estimate ORR of 45% in Exablate group and 30% in SOC group will need 369 subjects (246 subjects in Exablate and 123 in SOC).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".