Lung Adjuvant Cisplatin Evaluation: A Pooled Analysis by the LACE Collaborative Group
Bibliographic record
Abstract
PURPOSE: Several recent trials have shown a significant overall survival (OS) benefit from postoperative cisplatin-based chemotherapy in patients with non-small-cell lung cancer (NSCLC). The aim of the Lung Adjuvant Cisplatin Evaluation was to identify treatment options associated with a higher benefit or groups of patients who particularly benefit from postoperative chemotherapy. PATIENTS AND METHODS: Individual patient data were collected and pooled from the five largest trials (4,584 patients) of cisplatin-based chemotherapy in completely resected patients that were conducted after the 1995 NSCLC meta-analysis. The interactions between patient subgroups or treatment types and chemotherapy effect on OS were analyzed using hazard ratios (HRs) and log-rank tests stratified by trial. RESULTS: With a median follow-up time of 5.2 years, the overall HR of death was 0.89 (95% CI, 0.82 to 0.96; P = .005), corresponding to a 5-year absolute benefit of 5.4% from chemotherapy. There was no heterogeneity of chemotherapy effect among trials. The benefit varied with stage (test for trend, P = .04; HR for stage IA = 1.40; 95% CI, 0.95 to 2.06; HR for stage IB = 0.93; 95% CI, 0.78 to 1.10; HR for stage II = 0.83; 95% CI, 0.73 to 0.95; and HR for stage III = 0.83; 95% CI, 0.72 to 0.94). The effect of chemotherapy did not vary significantly (test for interaction, P = .11) with the associated drugs, including vinorelbine (HR = 0.80; 95% CI, 0.70 to 0.91), etoposide or vinca alkaloid (HR = 0.92; 95% CI, 0.80 to 1.07), or other (HR = 0.97; 95% CI, 0.84 to 1.13). Chemotherapy effect was higher in patients with better performance status. There was no interaction between chemotherapy effect and sex, age, histology, type of surgery, planned radiotherapy, or planned total dose of cisplatin. CONCLUSION: Postoperative cisplatin-based chemotherapy significantly improves survival in patients with 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 | 0.021 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.027 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".