The population-based impact of adjuvant chemotherapy (CTx) on outcomes in AJCC6 stage IB non-small cell lung cancer (NSCLC).
Bibliographic record
Abstract
8523 Background: Adjuvant CTx is the standard of care in stage II and IIIA NSCLC, but its value in AJCC6 stage IB NSCLC (T2N0M0) is unclear. Guidelines suggest consideration of adjuvant CTx for stage IB patients at high recurrence risk, but CTx use is variable. Prior population-based studies lacked NSCLC-specific survival (CSS) and key covariates such as health insurance status. Using a Canadian cohort with universal health care coverage and CSS data, we aimed to identify predictors of use and assess the real-world benefit of adjuvant CTx in stage IB NSCLC. Methods: We examined all patients who underwent surgery for T2N0M0 NSCLC in a large Canadian province between 2004 and 2015 and categorized cases based on receipt of adjuvant CTx within 6 months of curative resection. We identified predictors of CTx receipt with logistic regression. We also identified correlates of overall survival (OS) and CSS using Kaplan-Meier methods and Cox regression. Results: 967 patients met eligibility criteria. Median age was 68 (IQR 61-74) years at diagnosis, 455 (47%) were men, and 164 (17%) received adjuvant CTx. Sex, topology, and laterality were similar in patients treated with or without CTx. Lower age at diagnosis, lower Charlson Comorbidity Index, large cell histology, and tumor size ≥ 4 cm were associated with higher likelihood of CTx receipt (all p < 0.05). In the entire cohort and in the subset with ≥ 4 cm tumors, CTx improved OS but not DSS on univariate analysis. In both groups, CTx did not correlate with OS or DSS on multivariate analysis (Table). Conclusions: Adjuvant CTx does not improve survival in this real-world cohort of T2N0M0 NSCLC patients, even for patients with ≥ 4cm tumors, suggesting that it has a limited role in real-world practice. Univariate and multivariate survival analysis for stage IB NSCLC patients based on receipt of CTx. All patients ≥ 4 cm tumors CTx No CTx P CTx No CTx p mOS (months) [95% CI] 104 [67-114] 78 [69-86] 0.058 111 [85-137] 71 [55-87] 0.030 mCSS (months) [95% CI] 135 [NR] NR 0.491 135 [NR] NR 0.827 Adjusted HR for OS [95% CI] 0.93 [0.69-1.24] 0.598 0.73 [0.45-1.16] 0.177 Adjusted HR for CSS [95% CI] 1.20 [0.84-1.70] 0.316 0.92 [0.53-1.58] 0.754 m = median; HR = hazard ratio; NR = not reached.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".