The dawn of a new era, adjuvant EGFR inhibition in resected non-small cell lung cancer
Bibliographic record
Abstract
Background: Adjuvant platinum-based chemotherapy is standard of care for patients with resected stage IIA/B or IIIA NSCLC. Overall survival is suboptimal due to the high metastatic potential of early-stage NSCLC and there is substantial clinical need for additional efficacious adjuvant treatment options. Methods: PubMed (all time to 4 February 2021) and related conference databases were searched using the key search terms ‘NSCLC’ AND ‘Adjuvant’ AND ‘EGFR inhibitor’ OR respective aliases. Results: The literature search identified five adjuvant phase III trials of EGFR inhibitors in early NSCLC. The earlier BR19 and RADIANT trials failed to demonstrate statistically significant improvements in either OS or DFS for gefitinib and erlotinib, respectively, compared with placebo in patients with EGFR mutation-unselected NSCLC. Three subsequent phase III trials, ADAURA, CTONG1104, and IMPACT, were conducted in EGFR-mutant NSCLC. IMPACT showed no statistically significant DFS benefit for adjuvant gefitinib, and although CTONG1104 did report improved DFS for gefitinib (HR = 0.56, p = 0.001), this benefit was not enduring, resulting in comparable 5-year DFS rates. Statistically significant and clinically meaningful DFS benefits were observed in ADAURA for osimertinib compared with placebo in patients with stage IB-IIIA and II-IIIA disease (7th Edition Staging), and these benefits, coupled with a meaningful improvement in 2-year CNS DFS and favorable HRQoL, make osimertinib an important new treatment option for the adjuvant treatment of EGFR exon 19 deletion or exon 21 L858R-mutated stage II-IIIA NSCLC (UICC/AJCC 8th Edition Staging), with final mature OS data eagerly awaited. Conclusion: Adjuvant osimertinib used alone or following platinum-based chemotherapy is now recommended in patients with stage II-IIIA EGFR-mutated NSCLC.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".