Chemotherapy in Recurrent Advanced Non-Small-Cell Lung Cancer After Adjuvant Chemotherapy
Bibliographic record
Abstract
Introduction: Despite adjuvant systemic therapy in patients with completely resected non-small-cell lung cancer (NSCLC), many will subsequently relapse. We investigated treatment choices at relapse and assessed the effect of palliative platinum doublet systemic therapy in this population. Methods: With research ethics board approval, we performed a retrospective chart review of all patients with resected NSCLC who received adjuvant systemic therapy from January 2002 until December 2008 at our institution. The primary outcome was the response rate to first-line palliative systemic therapy among patients who relapsed. Results: We identified 176 patients who received adjuvant platinum doublet systemic therapy (82% received cisplatin–vinorelbine). In the 85 patients who relapsed (48%), median time to relapse was 18.5 months (95% confidence interval: 15 months to 21.3 months). Palliative systemic therapy was given in 43 patients. Of those 43 patients, 25 (58%) were re-challenged with platinum doublet systemic therapy, with a response rate of 29% compared with 18% in 18 patients who received other systemic therapy (p = 0.48). We observed a trend toward an increased clinical benefit rate (complete response + partial response + stable disease) in patients who were treated with a platinum doublet (67% vs. 41%, p = 0.12). Median overall survival (OS) from relapse was 15.3 months in patients receiving palliative systemic therapy and 7.8 months in those receiving best supportive care alone. Compared with patients treated with non-platinum regimens, the platinum-treated group experienced longer survival after relapse (18.4 months vs. 9.7 months, p = 0.041). Conclusions: In patients previously treated with adjuvant systemic therapy, re-treatment with platinum doublet chemotherapy upon relapse is feasible. Moreover, compared with patients receiving other first-line systemic therapy, patients receiving platinum doublets experienced higher response rates and significantly longer survival.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".