Efficacy of Brigatinib in Patients With Advanced ALK-Positive NSCLC Who Progressed on Alectinib or Ceritinib: ALK in Lung Cancer Trial of brigAtinib-2 (ALTA-2)
Bibliographic record
Abstract
INTRODUCTION: Brigatinib is a potent next-generation ALK tyrosine kinase inhibitor approved for treatment-naive and crizotinib-refractory advanced ALK-positive (ALK+) NSCLC. We evaluated brigatinib after other next-generation ALK tyrosine kinase inhibitors. METHODS: In this single-arm, phase 2, ALK in Lung Cancer Trial of brigAtinib-2 (NCT03535740), patients with advanced ALK+ NSCLC whose disease progressed on alectinib or ceritinib received brigatinib 180 mg once daily (after 7-d 90-mg lead-in). Primary end point was independent review committee (IRC)-assessed overall response rate (ORR). Circulating tumor DNA (ctDNA) was analyzed. RESULTS: Among 103 patients (data cutoff: September 30, 2020; median follow-up [range]: 10.8 [0.5-17.7] mo), confirmed IRC-ORR was 26.2% (95% confidence interval [CI]: 18.0-35.8), median duration of response, 6.3 months (95% CI: 5.6-not reached), and median progression-free survival (mPFS), 3.8 months (95% CI: 3.5-5.8). mPFS was 1.9 months (95% CI: 1.8-3.7) in patients with ctDNA-detectable baseline ALK fusion (n = 64). Among 86 patients who progressed on alectinib, IRC-ORR was 29.1% (95% CI: 19.8-39.9); mPFS was 3.8 months (95% CI: 1.9-5.4). Resistance mutations were present in 33.3% (26 of 78) of baseline ctDNA; 54% (14 of 26) of mutations were G1202R; 52% (33 of 64) of patients with detectable ALK fusion had EML4-ALK variant 3. Most common all-grade treatment-related adverse events were increased creatine phosphokinase (32%) and diarrhea (27%). The mean dose intensity of brigatinib (180 mg once daily) was 85.9%. CONCLUSIONS: In ALK in Lung Cancer Trial of brigAtinib-2, brigatinib was found to have a limited activity in patients with ALK+ NSCLC post-ceritinib or post-alectinib therapy. mPFS was longer with brigatinib in patients without baseline detectable plasma ALK fusion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| 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".