CTNI-75. EFFICACY AND SAFETY OF LAROTRECTINIB IN PATIENTS WITH TROPOMYOSIN RECEPTOR KINASE (TRK) FUSION PRIMARY CENTRAL NERVOUS SYSTEM (CNS) TUMORS: AN UPDATED ANALYSIS
Bibliographic record
Abstract
Abstract BACKGROUND Larotrectinib is a highly selective TRK inhibitor approved for tumor-agnostic use in patients with various tumor types, including primary CNS tumors. Here, we report the independent central review and updated data on patients with TRK fusion-positive primary CNS tumors. METHODS Patients with TRK fusion primary CNS tumors enrolled in two clinical trials (NCT02637687, NCT02576431) were included. Responses were independent review committee (IRC)-assessed. RESULTS As of July 2022, 41 patients were eligible for response assessment by IRC. The median age at enrollment was 11 years (range 1-79). Tumor histologic groups included: high-grade glioma (HGG; n=25), low-grade glioma (LGG; n=9), and other (n=7). Sixteen (39%) patients had received ≥ 2 prior systemic therapies. For all patients, objective response rate (ORR) was 22% (95% CI 11–38): one complete response, eight partial response, 20 stable disease, and 12 progressive disease. For pediatric patients (n=28), the ORR was 29% (95% CI 13–49). For pediatric patients with HGG and LGG, ORRs were 14% (95% CI 2–43) and 57% (95% CI 18–90), respectively. The disease control rates at 24 weeks were 54% (95% CI 37–69) and 71% (95% CI 51–87) for all patients and pediatric patients, respectively. Medians for time to response, duration of response, progression-free survival, and overall survival (OS) were 1.9 months, 12.2 months (95% CI 3.7–not estimable), 11.1 months (95% CI 3.6–19.8), and not reached, respectively. The 48-month OS rate was 52%. Treatment duration ranged from 1 to 50+ months. Treatment-related adverse events (TRAEs) were mostly Grade 1/2. No patients discontinued treatment due to TRAEs. CONCLUSION Larotrectinib demonstrated rapid, durable responses and a manageable safety profile in patients with TRK fusion primary CNS tumors. This supports the wider adoption of next-generation sequencing panels that include NTRK gene fusions when testing patients with CNS tumors.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".