Osimertinib then chemotherapy in EGFR-mutated lung cancer with osimertinib third-line rechallenge (OCELOT).
Bibliographic record
Abstract
TPS9160 Background: The results of the FLAURA study established osimertinib as the new first-line standard of care for patients with the two ‘common’ types of epidermal growth factor receptor mutation-positive (EGFR+) advanced non-small-cell lung cancer (aNSCLC). Second-line (2L) treatment is typically platinum pemetrexed chemotherapy and the standard third-line (3L) treatment is docetaxel throughout much of the globe, which has a modest response rate of 7 – 15%. Previously, when first generation (1G) EGFR tyrosine kinase inhibitor (TKIs) were standard of care in the first-line setting, a number of prospective and retrospective studies examined 3L rechallenge with the same 1G EGFR TKI following 2L chemotherapy, with varying levels of success. Osimertinib is a well-tolerated EGFR TKI which is active against the T790M resistance mutation, which would have limited the efficacy of rechallenge with 1G EGFR TKIs. Methods: This is a multicentered international phase II investigator-initiated study of osimertinib in the 3L rechallenge of patients with EGFR+ aNSCLC, following 1L treatment with osimertinib and 2L therapy with platinum pemetrexed chemotherapy. A maximum of 255 patients will be enrolled. Patients with ‘common’ EGFR exon 19 deletions or L858R mutations will enroll at the start of 2L chemotherapy or 3L osimertinib rechallenge. The primary objective is 3L objective response rate (ORR) in the first 100 evaluable patients, according to RECIST 1.1. Secondary objectives include disease control rate (DCR), progression free survival (PFS), time to treatment failure, overall survival and toxicity for 3L osimertinib rechallenge. Exploratory objectives include assessment of osimertinib resistance based on serial ctDNA samples collected from all participants. The OCELOT study, NCT04335292, is actively enrolling participants. Clinical trial information: NCT04335292 .
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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) | 0.000 | 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) | 0.003 | 0.001 |
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".