Entrectinib in children and young adults with solid or primary CNS tumors harboring <i>NTRK</i>, <i>ROS1</i>, or <i>ALK</i> aberrations (STARTRK-NG)
Bibliographic record
Abstract
BACKGROUND: Entrectinib is a TRKA/B/C, ROS1, ALK tyrosine kinase inhibitor approved for the treatment of adults and children aged ≥12 years with NTRK fusion-positive solid tumors and adults with ROS1 fusion-positive non-small-cell lung cancer. We report an analysis of the STARTRK-NG trial, investigating the recommended phase 2 dose (RP2D) and activity of entrectinib in pediatric patients with solid tumors including primary central nervous system tumors. METHODS: STARTRK-NG (NCT02650401) is a phase 1/2 trial. Phase 1, dose-escalation of oral, once-daily entrectinib, enrolled patients aged <22 years with solid tumors with/without target NTRK1/2/3, ROS1, or ALK fusions. Phase 2, basket trial at the RP2D, enrolled patients with intracranial or extracranial solid tumors harboring target fusions or neuroblastoma. Primary endpoints: phase 1, RP2D based on toxicity; phase 2, objective response rate (ORR) in patients harboring target fusions. Safety-evaluable patients: ≥1 dose of entrectinib; response-evaluable patients: measurable/evaluable baseline disease and ≥1 dose at RP2D. RESULTS: At data cutoff, 43 patients, median age of 7 years, were response-evaluable. In phase 1, 4 patients experienced dose-limiting toxicities. The most common treatment-related adverse event was weight gain (48.8%). Nine patients experienced bone fractures (20.9%). In patients with fusion-positive tumors, ORR was 57.7% (95% CI 36.9-76.7), median duration of response was not reached, and median (interquartile range) duration of treatment was 10.6 months (4.2-18.4). CONCLUSIONS: Entrectinib resulted in rapid and durable responses in pediatric patients with solid tumors harboring NTRK1/2/3 or ROS1 fusions.
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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 | 0.001 |
| 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) | 0.002 | 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".