Phase II COLET study: Atezolizumab (A) + cobimetinib (C) + paclitaxel (P)/nab-paclitaxel (nP) as first-line (1L) treatment (tx) for patients (pts) with locally advanced or metastatic triple-negative breast cancer (mTNBC).
Bibliographic record
Abstract
1013 Background: COLET showed that the addition of C (MEK1/2 inhibitor) to P resulted in an increased ORR (38%; Brufsky, SABCS 2017); IMpassion130 demonstrated clinical benefit with the combination of PD-L1 inhibitor A and nP as 1L tx for pts with mTNBC (Schmid, N Engl J Med, 2018). We investigated the efficacy and safety of A + C + P/nP in pts with mTNBC, as this combination may target multiple cancer immune escape mechanisms simultaneously. Methods: In the multi-stage, multi-cohort Phase II COLET study, pts with histologically confirmed mTNBC were randomized 1:1 to receive 1L tx with A 840 mg IV (d1, d15) + C 60 mg qd (d3-d23) + P 80 mg/m 2 IV (d1, d8, d15; cohort 2) or + nP 100 mg/m 2 (d1, d8, d15; cohort 3) in 28-day cycles until progression or toxicity. The primary endpoint (EP) was confirmed ORR per investigator-assessed RECIST 1.1. Additional EPs were DOR, PFS, OS, safety and exploratory efficacy by PD-L1 status. Results: As of 10 Aug 2018 (6.5-mo median follow-up), 63 and 62 pts were evaluable for efficacy and safety, respectively. In cohorts 2 and 3, 21 pts (66%) and 20 pts (65%) had received neo/adjuvant taxane tx, 9 pts (28%) and 6 pts (19%) had a disease-free interval of ≤12 mo, respectively. All pts had ≥1 AE; 69% and 70% had Gr 3-5 AEs and 47% and 43% had serious AEs in cohorts 2 and 3, respectively. Efficacy data for all pts and by PD-L1 expression on tumor-infiltrating immune cells (IC ≥1%; PD-L1+) are summarized in the Table. Conclusions: ORRs were similar between the A + C + P arm and A + C + nP arm. Numerically higher ORR and PFS were observed in pts with PD-L1+ disease. The combination’s safety profile was consistent with the known individual safety profiles, and A did not increase toxicity. Clinical trial information: NCT02322814. [Table: see text]
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".