Long-term Outcomes of Induction Carboplatin and Gemcitabine Followed by Concurrent Radiotherapy With Low-dose Paclitaxel and Gemcitabine for Stage III Non–small-cell Lung Cancer
Bibliographic record
Abstract
Background Standard treatment for unresectable stage III non–small-cell lung cancer (NSCLC) is concurrent chemo-radiation (CRT). A regimen of induction carboplatin and gemcitabine followed by CRT was developed at the McGill University Health Centre to prevent delays in treatment initiation. We report the long-term outcomes with this regimen based on a pooled analysis of both protocol patients from a phase II study and nonprotocol patients. Methods and Materials Outcomes and toxicity data were retrieved for 142 patients with stage III NSCLC: 43 patients treated on protocol between January 2003 and November 2004, and 101 patients treated off-protocol between December 2004 and August 2013. Patients received 2 cycles of carboplatin with an area under the curve of 5 intravenously (IV) on day 1 and gemcitabine 1000 mg/m 2 IV on days 1 and 8 every 3 weeks, followed on day 50 by CRT, 60 Gy/30 over 6 weeks, concomitantly with 2 cycles of paclitaxel 50 mg/m 2 IV and gemcitabine 100 mg/m 2 IV on days 1 and 8 every 3 weeks. Results The median overall survival was 23.2 months. With a median follow-up of 23.8 months, the 3-, 4-, and 5-year overall survival was 38%, 30%, and 26%, respectively. The median and 5-year progression-free survival rates were 12.5 months and 25%, respectively. Rates of grade ≥ 3 hematologic, esophageal, and respiratory toxicity were 20%, 10%, and 10%, respectively. Forty-eight patients received further lines of chemotherapy. Conclusion The present analysis affirms the favorable toxicity profile of this novel induction chemotherapy, without apparent compromise in clinical outcomes, when compared with regimens using immediate concurrent CRT.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".