CTNI-58. EFFICACY AND SAFETY OF LAROTRECTINIB IN ADULT AND PEDIATRIC PATIENTS WITH TROPOMYOSIN RECEPTOR KINASE (TRK) FUSION-POSITIVE PRIMARY CENTRAL NERVOUS SYSTEM (CNS) TUMORS
Bibliographic record
Abstract
Abstract BACKGROUND NTRK gene fusions are oncogenic drivers in various CNS and non-CNS tumors. Larotrectinib is a first-in-class, highly selective TRK inhibitor approved for patients with TRK fusion cancer, with a 75% objective response rate (ORR) in 206 evaluable patients with various non-CNS cancers (Hong et al, ASCO 2021). We report data on patients with TRK fusion-positive primary CNS tumors. METHODS Patients with TRK fusion-positive primary CNS tumors in 2 clinical trials (NCT02637687, NCT02576431) were identified. Objective responses were investigator-assessed. RESULTS As of July 2020, 33 patients with TRK fusion-positive primary CNS tumors were identified (19 high-grade gliomas [HGG], 8 low-grade gliomas [LGG], 2 glioneuronal tumors, 2 neuroepithelial tumors, 1 CNS neuroblastoma, 1 small round blue cell tumor). Median age was 8.9 years (range 1.3-79.0). Patients were heavily pre-treated, with 45% having ≥ 2 prior systemic therapies. ORR was 30% (95% CI 16-49): 3 complete responses (all pediatric), 7 partial responses, 20 stable disease, and 3 progressive disease. ORR in patients with HGG and LGG were 26% (95% CI 9-51) and 38% (95% CI 9-76), respectively. Median time to response was 1.9 months. Responses were seen regardless of the number of prior systemic therapies. The 24-week disease control rate was 73% (95% CI 54-87). Median PFS was 18.3 months (95% CI 6.7-not estimable [NE]) and median overall survival (OS) was not reached (95% CI 16.9-NE) at a median follow-up of 16.5 months; 12-month OS rate was 85% (95% CI 71-99). Treatment duration ranged from 1.2 to 31.3+ months. Grade 3-4 treatment-related adverse events (TRAEs) occurred in 3 patients (9%). There were no treatment discontinuations due to TRAEs. CONCLUSIONS In patients with TRK fusion-positive CNS tumors, larotrectinib demonstrated rapid and durable responses, high disease control rate, and favorable safety regardless of age or number of prior systemic therapies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".