Crizotinib in Patients With MET-Amplified NSCLC
Bibliographic record
Abstract
INTRODUCTION: MET amplification is a rare, potentially actionable, primary oncogenic driver in patients with NSCLC. METHODS: The influence of MET amplification on the clinical activity of the ALK, ROS1, and MET inhibitor, crizotinib (250 mg twice daily), was examined in patients with NSCLC (NCT00585195) who were enrolled into high (≥4 MET-to-CEP7 ratio), medium (>2.2 to <4 MET-to-CEP7 ratio), or low (≥1.8 to ≤2.2 MET-to-CEP7 ratio) amplification categories. Retrospective next-generation sequencing profiling was performed on archival tumor tissue. End points included objective response rate (ORR), duration of response, and progression-free survival. RESULTS: A total of 38 patients with a MET-to-CEP7 ratio greater than or equal to 1.8 by local fluorescence in situ hybridization testing received crizotinib. All patients were response-assessable, among whom 21, 14, and 3 had high, medium, and low MET amplification, respectively. ORRs of 8 of 21 (38.1%), 2 of 14 (14.3%), and 1 of 3 (33.3%), median duration of response of 5.2, 3.8, and 12.2 months, and median progression-free survival values of 6.7, 1.9, and 1.8 months were observed for those with high, medium, and low MET amplification, respectively. MET amplification gene copy number greater than or equal to 6 was detected by next-generation sequencing in 15 of 19 (78.9%) analyzable patients. Of these 15 patients, objective responses were observed in six (40%), two of whom had concurrent MET exon 14 alterations. No responses were observed among five patients with concurrent KRAS, BRAF, or EGFR mutations. CONCLUSIONS: Patients with high-level, MET-amplified NSCLC responded to crizotinib with the highest ORR. Use of combined diagnostics for MET and other oncogenes may potentially identify patients most likely to respond to crizotinib.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 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".