NFS-18. LOWER BODY SURFACE AREA IS ASSOCIATED WITH INCREASED LIKELIHOOD OF PLEXIFORM NEUROFIBROMA RESPONSE TO MEK INHIBITION
Bibliographic record
Abstract
Abstract BACKGROUND MEK inhibitors (MEKi) are altering the management approach for plexiform neurofibroma (PN), with high rates of treatment response to multiple MEKi. Despite these successes, a subset of PN fail to respond and little is known about the clinical features associated with treatment response. METHODS We performed a retrospective cohort study integrating clinical trial data (NCT01362803, NCT02407405, NCT02096471, NCT03231306, NCT03363217) to identify baseline clinical features associated with response of PN to MEKi. Partial response (PR) was defined as ≥20 percent reduction in tumor volume from baseline. RESULTS Of 232 eligible participants, adequate clinical trial and imaging data was available for 223 participants. In the primary analysis of 184 participants with central response evaluation, the median age was 15.2 years with a median tumor volume of 488 milliliters at clinical trial enrollment. One hundred and eighteen (64%) participants achieved a PR with median time to PR of 8 cycles. Thirty-five participants (19%) required a dose reduction prior to 6 cycles of therapy due to toxicity. Younger age and lower body surface area (BSA) were significantly associated with PR in univariate analysis while female sex and typical PN appearance (versus nodular) on imaging approached significance. In multivariable analysis, only lower BSA was significantly associated with response while typical PN appearance approached significance. In the multivariable analysis of pediatric participants treated per BSA-based dosing, lower BSA was the only feature significantly associated with PR. In the expanded analysis of all 223 participants, lower BSA and typical PN appearance were significantly associated with PR. CONCLUSION Lower BSA and typical appearance of PN were associated with PR to MEK inhibitors. Future studies of MEK inhibitor for PN should integrate tumor pharmacokinetic-pharmacodynamic analyses to prospectively explore the impact of BSA on treatment 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".