Surgically resectable nonsmall cell lung cancer: a contemporary approach
Bibliographic record
Abstract
New treatment paradigms for resectable nonsmall cell lung cancer (NSCLC), with an emphasis on personalised care and a multidisciplinary approach, have significantly improved patient outcomes. The incorporation of immune checkpoint inhibitors into neoadjuvant, perioperative and adjuvant treatment algorithms is reshaping the standard of care for resectable NSCLC. Adjuvant targeted therapy trials have also paved the way for a much-needed personalised approach for patients with actionable genomic alterations. Innovative surgical techniques and judicious use of postoperative radiotherapy may mitigate the toxicity associated with a multimodality approach. Amid the many new treatment options, questions remain about the best approach to consider for each patient. Measurement of minimal residual disease and achievement of pathological complete response are emerging biomarkers of interest to help further refine treatment selection. This review summarises the current management of resectable NSCLC, focusing on ongoing and recent advances in surgical approaches, the role of postoperative radiotherapy and the rapidly changing field of systemic therapies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".