Treatment patterns and outcomes in resectable early stage NSCLC: Interim analysis of a global real-world study.
Bibliographic record
Abstract
e18803 Background: Complete surgical resection is the preferred treatment for early stage NSCLC, with adjuvant chemotherapy as the standard of care in resected stage II/III and select stage IB NSCLC. Osimertinib, an epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI), is approved as adjuvant therapy in patients (pts) with resected stage IB–IIIA EGFR mutation-positive (EGFRm) NSCLC following results from the Phase III ADAURA trial. Understanding real-world clinical outcomes in early stage NSCLC, including EGFRm prevalence, will help inform unmet needs and further development of new treatment strategies in this population. We report interim results from a global non-interventional retrospective study of pts with resectable NSCLC using clinical data from medical records. Methods: Eligible pts (aged ≥18 yrs) had completely resected stage IA–IIIA NSCLC diagnosed between Jan 1, 2014 and Dec 31, 2017 with EGFR test results available and were followed to at least Dec 31, 2020. Primary endpoints included EGFRm prevalence, treatment patterns, and overall survival (OS); disease-free survival (DFS) was an exploratory endpoint estimated by Kaplan-Meier at predefined landmark timepoints. Results: Of 463 pts from 6 countries (31% from Taiwan, 21% Canada, 17% US, 13% Austria, 10% South Korea, 9% France), median age was 66 yrs (range: 33–86); 172 pts (37%) had stage IA NSCLC at initial diagnosis and 291 (63%) had stage IB–IIIA (22% IB, 13% IIA, 10% IIB, 18% IIIA). 213/463 pts (46%) were EGFRm (43% stage IA, 61% IB, 43% IIA, 26% IIB, 47% IIIA), of who 46% were from Taiwan, 21% South Korea, 14% Austria, 8% Canada, 7% US, and 4% France. In pts with EGFRm vs EGFR wild-type (wt) NSCLC, 84/213 (39%) and 83/250 (33%), respectively, received (neo)adjuvant therapy, of who 156/167 pts (93%) had stage IB–IIIA NSCLC. 106/156 pts (68%) had disease recurrence or death from time of surgery; recurrence rates were similar in pts with EGFRm vs EGFRwt NSCLC, though median DFS was longer in the EGFRm group (Table). Recurrence rates were high in both EGFRm and EGFTwt groups, with landmark DFS probability of 72% vs 77% at 12 mo and 29% vs 32% at 60 mo, respectively. Conclusions: In this real-world global study of surgically resected stage IA–IIIA NSCLC in pts who received an EGFR test, nearly half of the study cohort were EGFRm positive, of who 70% were treated in Taiwan/South Korea. The high rate of recurrence in pts with stage IB–IIIA NSCLC despite receiving (neo)adjuvant therapy reinforces the need for early diagnosis and EGFR testing to identify pts who might benefit from EGFR-targeted therapy, helping optimize clinical outcomes.[Table: see text]
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".