Efficacy of Metronomic Vinorelbine in Elderly Patients with Advanced Non-Small-Cell Lung Cancer and Poor Performance Status
Bibliographic record
Abstract
BACKGROUND: Metronomic chemotherapy-administration of low-dose chemotherapy-allows for a prolonged treatment duration and minimizes toxicity for unfit patients diagnosed with advanced non-small-cell lung cancer (nsclc). METHODS: Oral metronomic vinorelbine at 30 mg thrice weekly was given to 35 chemotherapy-naïve patients who were elderly and vulnerable to toxicity and who had been diagnosed with advanced nsclc. RESULTS: Median age in this male-predominant cohort (29:6) was 76 years (range: 65-86 years). Histology was squamous cell carcinoma in 21 patients and adenocarcinoma in 14. There were no complete responses and 9 partial responses, for an overall response rate of 26%. Stable disease was seen in 15 patients (43%), and 11 patients (31%) had progressive disease. The 1-year survival rate was 34%, and the 2-year survival rate was 8%. The survival analysis showed a median progression-free survival duration of 4 months (range: 2-15 months) and an overall survival duration of 7 months (range: 3-24 months). CONCLUSIONS: Metronomic vinorelbine had an acceptable efficacy and safety profile in elderly patients with multiple comorbidities who had been diagnosed with advanced nsclc. Metronomic vinorelbine could be a treatment option for elderly patients with poor performance status who are unfit for platinum-based chemotherapy and intravenous single-agent chemotherapy, and who are not candidates for combination modalities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".