Mutation testing, treatment patterns, and outcomes in patients with unresectable stage III EGFR-mutated non-small cell lung cancer treated with chemoradiotherapy: Final analysis of a global real–world study
Bibliographic record
Abstract
INTRODUCTION: In the phase III LAURA study, osimertinib after definitive chemoradiotherapy (CRT) demonstrated a statistically significant, clinically meaningful progression-free survival (PFS) benefit over placebo in patients with unresectable stage III epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC). Understanding real-world (rw) treatment patterns and clinical outcomes can help to measure the impact of new treatments. We report final results from a global, retrospective rw study of patients with unresectable stage III EGFR-mutated NSCLC treated with CRT. MATERIALS AND METHODS: Data were extracted from medical records of adults with unresectable stage III EGFR-mutated (Ex19del/L858R) NSCLC, diagnosed January 2016-December 2019, who received CRT as standard of care. The primary outcome was rwPFS. Secondary outcomes included mutation testing patterns and treatment patterns, rw time to next treatment or death (rwTTNTD) and overall survival (OS). Analyses are descriptive; time-to-event outcomes were estimated using Kaplan-Meier methods. RESULTS: Data were included from 172 patients; 59 % of patients harbored Ex19del and 41 % L858R; 76 % received concurrent CRT and 24 % sequential CRT. Overall, 78 %, 18 %, 3 %, and 1 % of patients received CRT alone, CRT plus durvalumab, CRT plus an EGFR-tyrosine kinase inhibitor (TKI) and CRT plus pembrolizumab, respectively, as their first treatment. Of patients who received subsequent treatment (n = 115), most received EGFR-TKIs (75 %; n = 86/115). In patients who received CRT alone as first treatment, median (95 % confidence interval) rwPFS, rwTTNTD, and OS were 6.7 (6.0-9.0), 11.4 (9.0-14.4), and 68.6 (60.9-not evaluable) months, respectively. CONCLUSION: In this rw study in patients with unresectable stage III EGFR-mutated NSCLC, CRT alone was the most common first treatment and EGFR-TKIs were the most common first subsequent treatment. OS was substantial despite relatively short rwPFS, which may be attributed to subsequent EGFR-TKIs. The findings highlight the unmet need for alternative treatments in this setting.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".