680. P02.06 MATTERHORN PCR BY REGION
Bibliographic record
Abstract
Abstract Background FLOT was established as a perioperative therapy for GC/GEJC following the Phase 2/3 FLOT4 study conducted in Germany, with a pCR rate of 16% (Al-Batran et al, Lancet Oncol 2016). The global MATTERHORN study (NCT04592913) showed a statistically significant improvement in pCR with perioperative D+FLOT vs placebo (P) + FLOT in GC/GEJC at first interim analysis (Janjigian et al, ESMO Congress 2023). Subgroup analyses by region and country were completed to assess pCR rates with FLOT and benefit of D+FLOT across the global study population. Methods Participants (pts) with resectable GC/GEJC were randomized 1:1 to D 1500 mg or P every 4 weeks (Q4W) on Day 1 plus FLOT Q2W on Days 1 and 15 for 4 cycles (2 doses of D or P and 4 doses of FLOT pre- and post-operative), followed by D 1500 mg or P on Day 1 Q4W for 10 further cycles. Randomization was stratified by Asia vs non-Asia. pCR (Modified Ryan; central review) was assessed in prespecified (Asia) and post hoc regional subgroups, including 6 countries with the highest numbers of randomized pts. Results Of 948 pts randomized globally, 180 (19%) were in Asia. pCR outcomes with FLOT in Asia were consistent with global outcomes. pCR rates were improved with D+FLOT vs P+FLOT in all regions (Asia, Europe, North America and South America; Table), despite some imbalances in baseline characteristics and numerical differences in pCR rates by geographic location. The pCR rate with P+FLOT in the German subgroup (13%; 95% CI, 6.1–23.0) was similar to that with FLOT in the FLOT4 study. Improvement in pCR with D+FLOT vs P+FLOT was observed across subgroups by country. Similar trends across regional subgroups were observed for combined complete and near-complete response rate. Conclusions In MATTERHORN, pCR was consistently improved with the addition of D to perioperative FLOT in GC/GEJC across geographic regions. The study is ongoing for the primary objective of event-free survival.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.186 | 0.036 |
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".