A Phase Ib Dose-Escalation Study of Encorafenib and Cetuximab with or without Alpelisib in Metastatic <i>BRAF</i> -Mutant Colorectal Cancer
Bibliographic record
Abstract
Abstract Preclinical evidence suggests that concomitant BRAF and EGFR inhibition leads to sustained suppression of MAPK signaling and suppressed tumor growth in BRAFV600E colorectal cancer models. Patients with refractory BRAFV600-mutant metastatic CRC (mCRC) were treated with a selective RAF kinase inhibitor (encorafenib) plus a monoclonal antibody targeting EGFR (cetuximab), with (n = 28) or without (n = 26) a PI3Kα inhibitor (alpelisib). The primary objective was to determine the maximum tolerated dose (MTD) or a recommended phase II dose. Dose-limiting toxicities were reported in 3 patients receiving dual treatment and 2 patients receiving triple treatment. The MTD was not reached for either group and the phase II doses were selected as 200 mg encorafenib (both groups) and 300 mg alpelisib. Combinations of cetuximab and encorafenib showed promising clinical activity and tolerability in patients with BRAF-mutant mCRC; confirmed overall response rates of 19% and 18% were observed and median progression-free survival was 3.7 and 4.2 months for the dual- and triple-therapy groups, respectively. Significance: Herein, we demonstrate that dual- (encorafenib plus cetuximab) and triple- (encorafenib plus cetuximab and alpelisib) combination treatments are tolerable and provide promising clinical activity in the difficult-to-treat patient population with BRAF-mutant mCRC. Cancer Discov; 7(6); 610–9. ©2017 AACR. See related commentary by Sundar et al., p. 558. This article is highlighted in the In This Issue feature, p. 539
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.002 | 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".