Impact of nirogacestat on pain, a key symptom in patients with desmoid tumors (DT): Results from the phase 3 DeFi study.
Bibliographic record
Abstract
11564 Background: Pain reduction is a key treatment goal in DT (aggressive fibromatosis): 60% of patients (pts) experience chronic pain. In the phase 3 DeFi trial, nirogacestat (NIRO; n = 70) significantly improved progression-free survival compared with placebo (PBO; n = 72) in pts with progressing DT (HR: 0.29 [95% CI, 0.15–0.55]; P< 0.001). Also as previously reported, NIRO significantly reduced pain severity by 1.50 points (on a 10-point scale) compared with PBO at cycle 10 (28-day cycles; P< 0.001) per the prespecified secondary endpoint of “worst pain” from the Brief Pain Inventory Short Form (BPI-SF). Additional aspects of pain were collected in DeFi to further characterize treatment impact and consistency across multiple pain assessment tools. Methods: In DeFi, pts completed 3 prespecified pain assessment tools through end of treatment: BPI-SF (worst pain), GOunder/Desmoid Tumor Research Foundation DEsmoid Symptom Scale (GODDESS-DTSS pain scale: worst pain, dull pain, shooting pain), European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire (QLQ-C30 pain scale: pain, pain interference with daily activities). Change from baseline (BL) in pain scores was compared between arms; analyses included mixed models for repeated measures to compare change from BL and stratified Cochran-Mantel-Haenszel to compare proportions of pts with clinically meaningful pain reduction (defined using prespecified thresholds) at cycle 10. Cycle 10 was preselected to allow adequate time for a treatment effect to be observed. Results: Statistically significant and clinically meaningful pain reductions were observed with NIRO compared with PBO at cycle 10 across all assessment tools; statistically significant differences between arms occurred as early as cycle 2 and were sustained throughout treatment. At cycle 10, NIRO reduced mean BL pain per GODDESS-DTSS (0–10 range) by 1.78 points (SE = 0.26) and PBO increased pain by 0.32 points (SE = 0.27; P< 0.001). At cycle 10, NIRO reduced mean BL pain per QLQ-C30 (0–100 range) by 22.05 points (SE = 3.38) and PBO increased pain by 7.19 points (SE = 3.64; P< 0.001). Clinically meaningful pain reduction (by ≥2.0 points) per BPI-SF worst pain (0–10 range) was achieved by 72% of pts with NIRO vs 29% of pts with PBO at cycle 10 ( P< 0.001). Per GODDESS-DTSS, clinically meaningful pain reduction (by ≥1.9 points) was achieved by 62% of pts with NIRO vs 19% of pts with PBO at cycle 10 ( P= 0.002). Conclusions: Rapid, sustained, and consistent reductions in different aspects of pain were observed with NIRO compared with PBO across multiple assessment tools in pts with DT. Furthermore, a significantly greater proportion of pts achieved clinically meaningful reductions in pain with NIRO than with PBO. As pain is the most commonly reported symptom, pain reduction should be a key clinical trial endpoint and a key treatment goal in DT. Clinical trial information: NCT03785964 .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".