HGG-18. Long-term efficacy and safety of larotrectinib in paediatric patients with tropomyosin receptor kinase (TRK) fusion-positive primary central nervous system (CNS) tumours
Bibliographic record
Abstract
Abstract INTRODUCTION: Neurotrophic tyrosine receptor kinase (NTRK) gene fusions are oncogenic drivers in various tumours. Larotrectinib, a highly selective TRK inhibitor, demonstrated an objective response rate (ORR) of 75% across 206 evaluable patients with various non-primary CNS cancers (Hong et al, ASCO 2021). We report long-term data on larotrectinib-treated paediatric patients with TRK fusion-positive primary CNS tumours. METHODS: Patients aged <18 years with TRK fusion-positive primary CNS tumours enrolled in two clinical trials (NCT02637687, NCT02576431) were included. Larotrectinib was administered at 100 mg/m2 (maximum: 100 mg) twice-daily. Response was investigator-assessed per RECIST v1.1 and RANO. RESULTS: As of July 2021, 28 patients with TRK fusion-positive primary CNS tumours were enrolled, including 14 high-grade and eight low-grade gliomas. Median age at enrolment was 7.0 years (range 1.0–17.0). Twenty-three patients (82%) received prior systemic therapy and 12 (43%) received prior radiotherapy. The ORR was 39% (95% confidence interval [CI] 22–59): three complete responses, eight partial responses, 15 stable disease and two progressive disease. The 24-week disease control rate was 82% (95% CI 63–94). Median duration of response (DoR) was not reached; median follow-up was 25.6 months. Median progression-free survival was 21.9 months (95% CI 9.2–not estimable). Median overall survival (OS) was not reached; median follow-up was 27.6 months. DoR and OS 24-month rates were 53% and 71%, respectively. Treatment duration ranged from 1.0 to 39.0+ months. Treatment-related adverse events (TRAEs) were mostly Grade 1–2. Grade 3–4 events occurred in three patients (increased gamma-glutamyltransferase, hyperglycaemia, hypernatraemia, hyponatraemia and neutropaenia). No patients discontinued treatment due to TRAEs. Fourteen patients progressed on treatment; four continued treatment post-progression for ≥4 weeks. CONCLUSION: Larotrectinib demonstrated high disease control rate, durable responses and a manageable safety profile. These results support testing for NTRK gene fusions in paediatric patients with primary CNS tumours.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".