A phase III, randomized, open-label study of ASP8273 versus erlotinib or gefitinib in patients with advanced stage IIIB/IV non-small-cell lung cancer
Bibliographic record
Abstract
BACKGROUND: ASP8273, a novel, small molecule, irreversible tyrosine kinase inhibitor (TKI) specifically inhibits the epidermal growth factor receptor (EGFR) in patients with activating mutations or EGFR T790M resistance mutations. The current study examines the efficacy, safety, and tolerability of ASP8273 versus erlotinib or gefitinib in patients with non-small-cell lung cancer (NSCLC) with activating EGFR mutations not previously treated with an EGFR inhibitor. PATIENTS AND METHODS: This global, phase III, open-label, randomized study evaluated ASP8273 versus erlotinib/gefitinib in patients with locally advanced, metastatic, or unresectable stage IIIB/IV NSCLC with activating EGFR mutations. They were ineligible if they received prior chemotherapy for metastatic disease. The primary end point was progression-free survival (PFS), and secondary end points included overall survival, investigator-assessed PFS, best overall response rate (ORR), disease control rate, duration of response (DoR), and the safety/tolerability profile. RESULTS: Patients (n = 530) were randomized 1 : 1 to receive ASP8273 (n = 267) or erlotinib/gefitinib (n = 263). Patient demographics between both treatment groups were generally balanced. Median PFS was 9.3 months (95% CI 5.6-11.1 months) for patients receiving ASP8273 and 9.6 months (95% CI 8.8-NE) for the erlotinib/gefitinib group, with a hazard ratio of 1.611 (P = 0.992). The ORR in the ASP8273 group was 33% (95% CI 27.4-39.0) versus 47.9% (95% CI 41.7-54.1) in the erlotinib/gefitinib group. Median DoR was similar for both groups (9.2 months for ASP8273 versus 9.0 months for erlotinib/gefitinib). More grade ≥3 treatment-emergent adverse events (TEAEs) occurred in patients receiving ASP8273 than in those receiving erlotinib/gefitinib (54.7% versus 43.5%). An independent data monitoring committee carried out an interim safety analysis and recommended discontinuing the study due to toxicity and limited predicted efficacy of ASP8273 relative to erlotinib/gefitinib. CONCLUSIONS: First-line ASP8273 did not show improved PFS or equivalent toxicities versus erlotinib/gefitinib. CLINICALTRIAL.GOV NUMBER: NCT02588261.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".