NFB-08. TRAM-01: A Phase 2 study of trametinib for pediatric patients with neurofibromatosis type 1 and plexiform neurofibromas
Bibliographic record
Abstract
Abstract BACKGROUND: Plexiform neurofibromas (PN) are found in up to 50% of patients with neurofibromatosis type 1 (NF1). Trametinib has been used widely to treat PN but limited data has been reported on its efficacy within a clinical trial. METHODS: This ongoing multicenter phase II trial includes patients with pediatric low-grade glioma and PN. The primary objective for PN was to evaluate the overall response rate based on RECIST 1.1 criteria after daily oral trametinib administration for eighteen 28-day cycles. The volumes of PN were centrally quantified using a new semi-automatic 3D segmentation method. RESULTS: As of January 1, 2022, 45 patients with PN were enrolled in the study. Twenty-eight completed treatment and were available for analysis. For these patients, the median age was 11.4 years (range 0.7-19.8) including 16 males (57.1%). The majority did not receive prior systemic therapies (71.4%). The median volume of PN at baseline was 49.5 cm3 (range 2.6 to 469). Among the 28 patients, 25 (89.3%) completed 18 cycles as planned. One patient discontinued due to adverse reaction, one patient refused to continue treatment and one patient discontinued treatment based on physician decision. Median duration of treatment was 15.9 months (range 4.6 to 16.8). Median duration of follow-up was 29.7 months (range 17.7 to 38.1). A total of 32 PN were available for volumetric analysis. Using RECIST evaluation, the overall response rate was 24.1%. Volumetric assessment demonstrated an overall response rate of 60.7% and 62.5% of PN showed a decrease of more than 20% in volume. Median decrease in volume was -30% (range -93.5 to 14.3). Twenty-seven patients (93.1%) had durable response without progression (lasting ≥1 year). CONCLUSION: We report outcome and volumetric quantification of PN treated with trametinib within a large clinical trial. Based on the current results, trametinib appears effective and offers durable response.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".