CTNI-04. 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 observed 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. Patients received daily oral trametinib (MEK inhibitor) for eighteen 28-day cycles. The volumes of PN were centrally quantified using a new semi-automatic 3D segmentation method. RESULTS As of May 15, 2022, 46 patients with PN were enrolled in the study and the recruitment was completed for this study arm. Thirty-four completed treatment and were available for analysis. For these patients, the median age was 10.5 years (range 0.7-19.8). The median volume of PN at baseline was 51cm3 (range 2.6 to 487.6). Among the 34 patients, 28 (82.4%) completed 18 cycles as planned. Two patients discontinued due to adverse reaction, three patients refused to continue treatment and one patient discontinued treatment based on physician decision. Median duration of treatment was 16.8 months (range 2.8 to 16.8). Median duration of follow-up was 30.4 months (range 8.2 to 42). A total of 38 PN were available for volumetric analysis. Using RECIST evaluation, the overall response rate was 13.1%. Volumetric assessment demonstrated an overall response rate of 64.7% (22/34 patients), and 65.8% (25/38 PN) of PN showed a decrease of more than 20% in volume. Median volume change was -30% (range -93.5 to 14.3). Thirty-one patients (91.1%) had durable response without progression (lasting ≥ 1 year). After discontinuation of treatment, one patient underwent surgery and three patients resumed MEK inhibitor. CONCLUSION We report outcome and volumetric quantification of PN treated with trametinib within a large clinical trial. Based on the current results, trametinib is 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".