Weekly paclitaxel and gemcitabine chemotherapy for metastatic non‐small cell lung carcinoma (NSCLC)
Bibliographic record
Abstract
BACKGROUND: The current dose-optimizing Phase II study evaluated the effect of weekly paclitaxel and gemcitabine on the response rate and survival of patients with non-small cell lung carcinoma (NSCLC) using dose modifications that permitted optimal treatment intensity. METHODS: Forty-five patients (40 with TNM Stage IV and 5 with TNM Stage IIIB NSCLC) were treated with gemcitabine at 1000 mg/m(2) via a 30-minute intravenous (i.v.) infusion and with paclitaxel at 100 mg/m(2) via a 60-minute i.v. infusion. The first 3 patients received chemotherapy on Days 1, 8, and 15 every 4 weeks; the next 42 patients, participating in the Phase II trial, received chemotherapy on Days 1 and 8 every 3 weeks. RESULTS: The 3 patients who received paclitaxel and gemcitabine on Days 1, 8, and 15 every 4 weeks tolerated the treatment poorly. One patient died suddenly after Day 15 treatment during the first cycle, and the other 2 patients discontinued the treatment because of unacceptable toxicity before the third cycle of chemotherapy. The next 42 patients, 40 of whom were evaluable, entered this trial between May 2000 and April 2001. They received paclitaxel at 100 mg/m(2) i.v. followed by gemcitabine at 1000 mg/m(2) i.v. on Days 1 and 8 every 3 weeks. Two patients (5%) achieved complete response, 20 (50%) achieved partial response, and 8 (20%) had stable disease. Median survival (MS) was 9.8 months; and 1-year survival was 35%. The 32 patients with performance status (PS) 0 or 1 had an MS of 11 months; the 8 patients with PS 2 had an MS of 3 months. Toxicity (especially hematologic toxicity, neuropathy, and alopecia) was minimal. CONCLUSION: A weekly paclitaxel and gemcitabine regimen that incorporated the authors' dose modifications resulted in good efficacy with minimal toxicity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".