Sequencing of therapy following first-line afatinib in patients with EGFR mutation-positive non-small cell lung cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: With the availability of several epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs), sequential therapy could potentially render EGFR mutation-positive non-small cell lung cancer a chronic disease in some patients. In this retrospective analysis of EGFR mutation-positive (Del19/L858R) patients receiving first-line afatinib in LUX-Lung 3, 6, and 7, we assessed uptake of, and outcomes following, subsequent therapies including the third-generation EGFR TKI, osimertinib. METHODS: Post-progression therapy data were prospectively collected during follow-up. Molecular testing of tumours at progression/discontinuation of afatinib was not mandatory. Duration of subsequent therapies, and survival following osimertinib, were calculated with Kaplan-Meier estimates. RESULTS: Among 553 patients who discontinued first-line afatinib, second-, third- and fourth-line therapy was administered in 394 (71%), 265 (48%), and 156 (28%) patients. The most common post-progression therapy was platinum-based chemotherapy (46%). Thirty-seven patients received subsequent osimertinib, 10 as second-line treatment. Median progression-free survival on afatinib in these 37 patients was 21.9 months. Median duration of osimertinib therapy was 20.2 months; median overall survival was not reached after a median follow-up of 4.7 years. CONCLUSIONS: Most patients treated with first-line afatinib received subsequent therapy. Although limited by sample size, enrichment, and a retrospective nature, data from patients who received sequential afatinib and osimertinib are encouraging, warranting further investigation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it