Real‐world outcomes of neoadjuvant chemoimmunotherapy in patients with nonsmall cell lung cancer: Predictors of surgery, pathologic complete response, and event‐free survival
Bibliographic record
Abstract
BACKGROUND: Trials of neoadjuvant chemoimmunotherapy (chemoIO) have changed the standard of care for resectable nonsmall cell lung cancer (NSCLC). This study characterizes the outcomes of off-trial patients who received treatment with neoadjuvant chemoIO. METHODS: The authors analyzed records of patients with stage IB-III NSCLC who received neoadjuvant chemoIO with an intent to proceed to surgical resection at three US academic institutions. Clinical, demographic, and pathologic factors were incorporated in univariable and multivariable regression models to identify associations with outcomes (resection status, pathologic complete response [pCR], and subsequent event-free survival [EFS]) after standard-of-care neoadjuvant chemoIO. RESULTS: Analyses included 115 patients, of whom 63% had stage III disease, 77% completed three cycles of chemoIO, and 78% underwent surgical resection. Ages older than 72 years versus 64 years and younger were associated with not proceeding to surgery in univariable (p = .006) and multivariable (p = .014) regression analyses. Nineteen patients (17%) had tumors with a pCR, and 34 (30%) had a major pathologic response. Positive programmed death-ligand 1 (PD-L1) expression (≥50%; vs. negative PD-L1 expression: odds ratio, 12.1; 95% confidence interval, 2.0-73.7; p = .007) and KRAS mutations (vs. wild-type KRAS: odds ratio, 3.9; 95% confidence interval, 1.07-14.4; p = .039) were associated with a higher probability of pCR in univariable analysis. The median event-free survival was not reached and did not differ among subgroups stratified by key clinical variables. CONCLUSIONS: The results from this study confirm the trial experience of high pCR rates after neoadjuvant chemoIO. This supports the use of chemoIO irrespective of KRAS mutation status, PD-L1 expression, and histology, but suggests that this approach may be less suitable for older patients.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".