A Canadian Perspective on Perioperative Systemic Therapy in Resectable Non-Small Cell Lung Cancer
Bibliographic record
Abstract
The management strategies in resectable non-small cell lung cancer (NSCLC) have changed over the last few years. Despite advancements in surgical techniques and conventional chemotherapy, patients with resectable NSCLC remained at high risk of future recurrence. Clinical trials have demonstrated improvements in response rates, pathological outcomes, and survival with the perioperative approach. Considering the findings of these landmark trials, there is a pressing need to contextualize and incorporate these global developments into the national practice framework. This review outlines key developments from recent clinical trials, with a focus on perioperative strategies in early-stage operable NSCLC from a Canadian perspective. We discuss the integration of checkpoint inhibitors in the perioperative setting for patients without actionable genomic alterations, adjuvant targeted therapies for EGFR and ALK mutant disease, and emerging tools such as ctDNA based minimal residual disease monitoring. The article also addresses the practical challenges of implementing these advances within the Canadian healthcare system, including systemic therapy approvals, barriers, and importance of multidisciplinary care to guide clinicians in optimizing patient outcomes.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 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".